40. Multi-agent Systems#
In this notebook we see how easy it is to work with multi-agent systems. We will study two open-source repos, Crew AI and Agno.
References:
https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/
Examples to complement the ones below: https://docs.crewai.com/examples/example
A nice introduction to ideas about agents, “You Should Write an Agent”: https://fly.io/blog/everyone-write-an-agent
from google.colab import drive
drive.mount('/content/drive') # Add My Drive/<>
import os
os.chdir('drive/My Drive')
os.chdir('Books_Writings/NLPBook/')
Mounted at /content/drive
%%capture
import numpy as np
import pandas as pd
import os
import textwrap
def p80(text):
print(textwrap.fill(text, 80))
return None
40.1. Crew AI#
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Installing collected packages: pypika, durationpy, appdirs, uv, tomli-w, tomli, requests, regex, pytube, python-docx, pyproject_hooks, pypdfium2, pymupdf, pydantic-core, pybase64, portalocker, Pillow, overrides, opentelemetry-proto, onnxruntime, jsonref, json5, json-repair, jmespath, jiter, httpx-sse, google-re2, bcrypt, backoff, aiosqlite, aiofiles, youtube-transcript-api, tiktoken, rich, pydantic, posthog, pendulum, opentelemetry-exporter-otlp-proto-common, build, textual, sse-starlette, pydantic-settings, pdfminer.six, lance-namespace-urllib3-client, kubernetes, cel-python, pdfplumber, opentelemetry-exporter-otlp-proto-http, opentelemetry-exporter-otlp-proto-grpc, mcp, lance-namespace, instructor, lancedb, crewai-core, chromadb, crewai-cli, crewai, crewai-tools
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
google-colab 1.0.0 requires requests==2.32.4, but you have requests 2.34.2 which is incompatible.
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try:
import pydantic
except ImportError:
os.system('!pip install pydantic --quiet')
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%run keys.ipynb
40.2. Application: Marketing Analysts#
https://docs.crewai.com/en/concepts/tools
import os
from crewai import Agent, Task, Crew
# Importing crewAI tools
from crewai_tools import (
DirectoryReadTool,
FileReadTool,
SerperDevTool,
WebsiteSearchTool
)
# Set up API keys, if needed
# os.environ["SERPER_API_KEY"] = "Your Key" # serper.dev API key
# os.environ["OPENAI_API_KEY"] = "Your Key"
# Instantiate tools
docs_tool = DirectoryReadTool(directory='./blog-posts')
file_tool = FileReadTool()
search_tool = SerperDevTool()
# web_rag_tool = WebsiteSearchTool()
# Create agents
researcher = Agent(
role='Market Research Analyst',
goal='Provide up-to-date market analysis of the AI industry',
backstory='An expert analyst with a keen eye for market trends.',
# tools=[search_tool, web_rag_tool],
tools=[search_tool],
verbose=True
)
writer = Agent(
role='Content Writer',
goal='Craft engaging blog posts about the AI industry',
backstory='A skilled writer with a passion for technology.',
tools=[docs_tool, file_tool],
verbose=True
)
# Define tasks
research = Task(
description='Research the latest trends in the AI industry and provide a summary.',
expected_output='A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.',
agent=researcher
)
write = Task(
description='Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.',
expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.',
agent=writer,
output_file='blog-posts/new_post.md' # The final blog post will be saved here
)
# Assemble a crew with planning enabled
crew = Crew(
agents=[researcher, writer],
tasks=[research, write],
verbose=True,
planning=True, # Enable planning feature
)
import asyncio
# Execute tasks
await crew.kickoff_async()
╭─────────────────────────────────────────── 🚀 Crew Execution Started ───────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: 81b70ca7-00ba-4a47-90c2-3fe4a8622e99 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[2026-07-16 18:28:36][INFO]: Planning the crew execution
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Based on these tasks summary: │ │ Task Number 1 - Research the latest trends in the AI industry and provide a summary. │ │ "task_description": Research the latest trends in the AI industry and provide a summary. │ │ "task_expected_output": A summary of the top 3 trending developments in the AI industry with │ │ a unique perspective on their significance. │ │ "agent": Market Research Analyst │ │ "agent_goal": Provide up-to-date market analysis of the AI industry │ │ "task_tools": [SerperDevTool(name='Search the internet with Serper', description='Tool Name: │ │ search_the_internet_with_serper\nTool Arguments: {\n "description": "Input for SerperDevTool.",\n │ │ "properties": {\n "search_query": {\n "description": "Mandatory search query you want to use to │ │ search the internet",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to search the internet with a search_query. Supports │ │ different search types: \'search\' (default), \'news\'', env_vars=[EnvVar(name='SERPER_API_KEY', │ │ description='API key for Serper', required=True, default=None)], args_schema=<class │ │ 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, base_url='https://google.serper.dev', │ │ n_results=10, save_file=False, search_type='search', country='', location='', locale='', │ │ tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool')] │ │ "agent_tools": [name='Search the internet with Serper' description='Tool Name: │ │ search_the_internet_with_serper\nTool Arguments: {\n "description": "Input for SerperDevTool.",\n │ │ "properties": {\n "search_query": {\n "description": "Mandatory search query you want to use to │ │ search the internet",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to search the internet with a search_query. Supports │ │ different search types: \'search\' (default), \'news\'' env_vars=[EnvVar(name='SERPER_API_KEY', │ │ description='API key for Serper', required=True, default=None)] args_schema=<class │ │ 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 base_url='https://google.serper.dev' │ │ n_results=10 save_file=False search_type='search' country='' location='' locale='' │ │ tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool'] │ │ Task Number 2 - Write an engaging blog post about the AI industry, based on the research │ │ analysts summary. Draw inspiration from the latest blog posts in the directory. │ │ "task_description": Write an engaging blog post about the AI industry, based on the research │ │ analysts summary. Draw inspiration from the latest blog posts in the directory. │ │ "task_expected_output": A 4-paragraph blog post formatted in markdown with engaging, │ │ informative, and accessible content, avoiding complex jargon. │ │ "agent": Content Writer │ │ "agent_goal": Craft engaging blog posts about the AI industry │ │ "task_tools": [DirectoryReadTool(name='List files in directory', description='Tool Name: │ │ list_files_in_directory\nTool Arguments: {\n "description": "Input for DirectoryReadTool.",\n "properties": │ │ {},\n "title": "FixedDirectoryReadToolSchema",\n "type": "object",\n "additionalProperties": false,\n │ │ "required": []\n}\nTool Description: A tool that can be used to list ./blog-posts\'s content.', env_vars=[], │ │ args_schema=<class │ │ 'crewai_tools.tools.directory_read_tool.directory_read_tool.FixedDirectoryReadToolSchema'>, │ │ result_schema=None, description_updated=False, cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0>, result_as_answer=False, max_usage_count=None, current_usage_count=0, │ │ directory='./blog-posts', │ │ tool_type='crewai_tools.tools.directory_read_tool.directory_read_tool.DirectoryReadTool'), │ │ FileReadTool(name="Read a file's content", description='Tool Name: read_a_files_content\nTool Arguments: {\n │ │ "description": "Input for FileReadTool.",\n "properties": {\n "file_path": {\n "description": │ │ "Mandatory file full path to read the file",\n "title": "File Path",\n "type": "string"\n },\n │ │ "start_line": {\n "default": 1,\n "description": "Line number to start reading from (1-indexed)",\n │ │ "title": "Start Line",\n "type": "integer"\n },\n "line_count": {\n "default": null,\n │ │ "description": "Number of lines to read. If None, reads the entire file",\n "title": "Line Count",\n │ │ "type": "integer"\n }\n },\n "required": [\n "file_path",\n "start_line",\n "line_count"\n │ │ ],\n "title": "FileReadToolSchema",\n "type": "object",\n "additionalProperties": false\n}\nTool │ │ Description: A tool that reads the content of a file. To use this tool, provide a \'file_path\' parameter │ │ with the path to the file you want to read. Optionally, provide \'start_line\' to start reading from a │ │ specific line and \'line_count\' to limit the number of lines read.', env_vars=[], args_schema=<class │ │ 'crewai_tools.tools.file_read_tool.file_read_tool.FileReadToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, file_path=None, │ │ tool_type='crewai_tools.tools.file_read_tool.file_read_tool.FileReadTool')] │ │ "agent_tools": [name='List files in directory' description='Tool Name: │ │ list_files_in_directory\nTool Arguments: {\n "description": "Input for DirectoryReadTool.",\n "properties": │ │ {},\n "title": "FixedDirectoryReadToolSchema",\n "type": "object",\n "additionalProperties": false,\n │ │ "required": []\n}\nTool Description: A tool that can be used to list ./blog-posts\'s content.' env_vars=[] │ │ args_schema=<class 'crewai_tools.tools.directory_read_tool.directory_read_tool.FixedDirectoryReadToolSchema'> │ │ result_schema=None description_updated=False cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0> result_as_answer=False max_usage_count=None current_usage_count=0 directory='./blog-posts' │ │ tool_type='crewai_tools.tools.directory_read_tool.directory_read_tool.DirectoryReadTool', name="Read a file's │ │ content" description='Tool Name: read_a_files_content\nTool Arguments: {\n "description": "Input for │ │ FileReadTool.",\n "properties": {\n "file_path": {\n "description": "Mandatory file full path to │ │ read the file",\n "title": "File Path",\n "type": "string"\n },\n "start_line": {\n │ │ "default": 1,\n "description": "Line number to start reading from (1-indexed)",\n "title": "Start │ │ Line",\n "type": "integer"\n },\n "line_count": {\n "default": null,\n "description": │ │ "Number of lines to read. If None, reads the entire file",\n "title": "Line Count",\n "type": │ │ "integer"\n }\n },\n "required": [\n "file_path",\n "start_line",\n "line_count"\n ],\n │ │ "title": "FileReadToolSchema",\n "type": "object",\n "additionalProperties": false\n}\nTool Description: A │ │ tool that reads the content of a file. To use this tool, provide a \'file_path\' parameter with the path to │ │ the file you want to read. Optionally, provide \'start_line\' to start reading from a specific line and │ │ \'line_count\' to limit the number of lines read.' env_vars=[] args_schema=<class │ │ 'crewai_tools.tools.file_read_tool.file_read_tool.FileReadToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 file_path=None │ │ tool_type='crewai_tools.tools.file_read_tool.file_read_tool.FileReadTool'] │ │ Create the most descriptive plan based on the tasks descriptions, tools available, and agents' goals for │ │ them to execute their goals with perfection. │ │ ID: 08fecb74-22c7-46e2-8d08-c4115b46ceb2 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Based on these tasks summary: │ │ Task Number 1 - Research the latest trends in the AI industry and provide a summary. │ │ "task_description": Research the latest trends in the AI industry and provide a summary. │ │ "task_expected_output": A summary of the top 3 trending developments in the AI industry with │ │ a unique perspective on their significance. │ │ "agent": Market Research Analyst │ │ "agent_goal": Provide up-to-date market analysis of the AI industry │ │ "task_tools": [SerperDevTool(name='Search the internet with Serper', description='Tool Name: │ │ search_the_internet_with_serper\nTool Arguments: {\n "description": "Input for SerperDevTool.",\n │ │ "properties": {\n "search_query": {\n "description": "Mandatory search query you want to use to │ │ search the internet",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to search the internet with a search_query. Supports │ │ different search types: \'search\' (default), \'news\'', env_vars=[EnvVar(name='SERPER_API_KEY', │ │ description='API key for Serper', required=True, default=None)], args_schema=<class │ │ 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, base_url='https://google.serper.dev', │ │ n_results=10, save_file=False, search_type='search', country='', location='', locale='', │ │ tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool')] │ │ "agent_tools": [name='Search the internet with Serper' description='Tool Name: │ │ search_the_internet_with_serper\nTool Arguments: {\n "description": "Input for SerperDevTool.",\n │ │ "properties": {\n "search_query": {\n "description": "Mandatory search query you want to use to │ │ search the internet",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to search the internet with a search_query. Supports │ │ different search types: \'search\' (default), \'news\'' env_vars=[EnvVar(name='SERPER_API_KEY', │ │ description='API key for Serper', required=True, default=None)] args_schema=<class │ │ 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 base_url='https://google.serper.dev' │ │ n_results=10 save_file=False search_type='search' country='' location='' locale='' │ │ tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool'] │ │ Task Number 2 - Write an engaging blog post about the AI industry, based on the research │ │ analysts summary. Draw inspiration from the latest blog posts in the directory. │ │ "task_description": Write an engaging blog post about the AI industry, based on the research │ │ analysts summary. Draw inspiration from the latest blog posts in the directory. │ │ "task_expected_output": A 4-paragraph blog post formatted in markdown with engaging, │ │ informative, and accessible content, avoiding complex jargon. │ │ "agent": Content Writer │ │ "agent_goal": Craft engaging blog posts about the AI industry │ │ "task_tools": [DirectoryReadTool(name='List files in directory', description='Tool Name: │ │ list_files_in_directory\nTool Arguments: {\n "description": "Input for DirectoryReadTool.",\n "properties": │ │ {},\n "title": "FixedDirectoryReadToolSchema",\n "type": "object",\n "additionalProperties": false,\n │ │ "required": []\n}\nTool Description: A tool that can be used to list ./blog-posts\'s content.', env_vars=[], │ │ args_schema=<class │ │ 'crewai_tools.tools.directory_read_tool.directory_read_tool.FixedDirectoryReadToolSchema'>, │ │ result_schema=None, description_updated=False, cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0>, result_as_answer=False, max_usage_count=None, current_usage_count=0, │ │ directory='./blog-posts', │ │ tool_type='crewai_tools.tools.directory_read_tool.directory_read_tool.DirectoryReadTool'), │ │ FileReadTool(name="Read a file's content", description='Tool Name: read_a_files_content\nTool Arguments: {\n │ │ "description": "Input for FileReadTool.",\n "properties": {\n "file_path": {\n "description": │ │ "Mandatory file full path to read the file",\n "title": "File Path",\n "type": "string"\n },\n │ │ "start_line": {\n "default": 1,\n "description": "Line number to start reading from (1-indexed)",\n │ │ "title": "Start Line",\n "type": "integer"\n },\n "line_count": {\n "default": null,\n │ │ "description": "Number of lines to read. If None, reads the entire file",\n "title": "Line Count",\n │ │ "type": "integer"\n }\n },\n "required": [\n "file_path",\n "start_line",\n "line_count"\n │ │ ],\n "title": "FileReadToolSchema",\n "type": "object",\n "additionalProperties": false\n}\nTool │ │ Description: A tool that reads the content of a file. To use this tool, provide a \'file_path\' parameter │ │ with the path to the file you want to read. Optionally, provide \'start_line\' to start reading from a │ │ specific line and \'line_count\' to limit the number of lines read.', env_vars=[], args_schema=<class │ │ 'crewai_tools.tools.file_read_tool.file_read_tool.FileReadToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, file_path=None, │ │ tool_type='crewai_tools.tools.file_read_tool.file_read_tool.FileReadTool')] │ │ "agent_tools": [name='List files in directory' description='Tool Name: │ │ list_files_in_directory\nTool Arguments: {\n "description": "Input for DirectoryReadTool.",\n "properties": │ │ {},\n "title": "FixedDirectoryReadToolSchema",\n "type": "object",\n "additionalProperties": false,\n │ │ "required": []\n}\nTool Description: A tool that can be used to list ./blog-posts\'s content.' env_vars=[] │ │ args_schema=<class 'crewai_tools.tools.directory_read_tool.directory_read_tool.FixedDirectoryReadToolSchema'> │ │ result_schema=None description_updated=False cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0> result_as_answer=False max_usage_count=None current_usage_count=0 directory='./blog-posts' │ │ tool_type='crewai_tools.tools.directory_read_tool.directory_read_tool.DirectoryReadTool', name="Read a file's │ │ content" description='Tool Name: read_a_files_content\nTool Arguments: {\n "description": "Input for │ │ FileReadTool.",\n "properties": {\n "file_path": {\n "description": "Mandatory file full path to │ │ read the file",\n "title": "File Path",\n "type": "string"\n },\n "start_line": {\n │ │ "default": 1,\n "description": "Line number to start reading from (1-indexed)",\n "title": "Start │ │ Line",\n "type": "integer"\n },\n "line_count": {\n "default": null,\n "description": │ │ "Number of lines to read. If None, reads the entire file",\n "title": "Line Count",\n "type": │ │ "integer"\n }\n },\n "required": [\n "file_path",\n "start_line",\n "line_count"\n ],\n │ │ "title": "FileReadToolSchema",\n "type": "object",\n "additionalProperties": false\n}\nTool Description: A │ │ tool that reads the content of a file. To use this tool, provide a \'file_path\' parameter with the path to │ │ the file you want to read. Optionally, provide \'start_line\' to start reading from a specific line and │ │ \'line_count\' to limit the number of lines read.' env_vars=[] args_schema=<class │ │ 'crewai_tools.tools.file_read_tool.file_read_tool.FileReadToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 file_path=None │ │ tool_type='crewai_tools.tools.file_read_tool.file_read_tool.FileReadTool'] │ │ Create the most descriptive plan based on the tasks descriptions, tools available, and agents' goals for │ │ them to execute their goals with perfection. │ │ Agent: Task Execution Planner │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective │ │ internally as: identify the top 3 most current and materially important trends in the AI industry, not just │ │ general news. Prioritize developments that are both recent and industry-shaping. │ │ 2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search │ │ query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry │ │ developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest. │ │ 3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise │ │ adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is │ │ balanced and not overly dependent on one type of development. │ │ 4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across │ │ multiple sources, since trends supported by several independent reports are more likely to be truly │ │ significant. │ │ 5. For each candidate trend, capture the following: what is happening, why it is trending now, which │ │ companies or sectors are involved, and what the broader implication is for the AI industry. │ │ 6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, │ │ technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined │ │ significance rather than simply recency. │ │ 7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short │ │ explanation of why it matters, and a unique perspective on its significance. The unique perspective should │ │ connect the trend to a broader business or societal implication, such as competitive advantage, cost │ │ structure changes, trust and compliance, or shifts in product design. │ │ 8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and │ │ keep terminology current. Remove redundant or weakly supported claims. │ │ 9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with │ │ each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and │ │ grounded in evidence. │ │ ID: 8baecd28-ea9a-4b66-99fe-643c8af9530a │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Task: Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective │ │ internally as: identify the top 3 most current and materially important trends in the AI industry, not just │ │ general news. Prioritize developments that are both recent and industry-shaping. │ │ 2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search │ │ query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry │ │ developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest. │ │ 3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise │ │ adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is │ │ balanced and not overly dependent on one type of development. │ │ 4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across │ │ multiple sources, since trends supported by several independent reports are more likely to be truly │ │ significant. │ │ 5. For each candidate trend, capture the following: what is happening, why it is trending now, which │ │ companies or sectors are involved, and what the broader implication is for the AI industry. │ │ 6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, │ │ technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined │ │ significance rather than simply recency. │ │ 7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short │ │ explanation of why it matters, and a unique perspective on its significance. The unique perspective should │ │ connect the trend to a broader business or societal implication, such as competitive advantage, cost │ │ structure changes, trust and compliance, or shifts in product design. │ │ 8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and │ │ keep terminology current. Remove redundant or weakly supported claims. │ │ 9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with │ │ each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and │ │ grounded in evidence. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#1) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'latest AI industry trends 2026 news'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#2) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'model innovation in AI 2026'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#5) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'AI regulation and governance latest'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#4) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'AI infrastructure and chips development 2026'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#3) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'enterprise adoption of AI latest'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#6) ─────────────────────────────────────────╮ │ │ │ Tool: search_the_internet_with_serper │ │ Args: {'search_query': 'AI agents and automation advancements 2026'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'model innovation in AI 2026', 'type': 'search', 'num': 10, 'engine': │ │ 'google'}, 'organic': [{'title': 'The 2026 AI Index Report | Stanford HAI', 'link': │ │ 'https://hai.stanford.edu/ai-index/2026-ai-index-report', 'snippet': 'Industry produced over 90% of notable │ │ frontier models in 2025, and several of those models now meet or exceed human baselines on PhD-level science │ │ questions, ...', 'position': 1}, {'title': 'The new AI race: Enterprise innovation in 2026', 'link': │ │ 'https://www.youtube.com/watch?v=s3SHPOByMTY', 'snippet': 'OpenAI confirms ads are coming to ChatGPT, raising │ │ questions about trust, economics and the future of AI product models. Next, Claude Code is ...', 'position': │ │ 2}, {'title': 'Top AI Trends Shaping Business and Innovation in 2026', 'link': │ │ 'https://london.theaisummit.com/ai-trends-in-2026/', 'snippet': 'AI trends of 2026, from agentic systems to │ │ scaling enterprise AI. Agentic AI systems are making autonomous decisions across your operations. Multimodal │ │ models ...', 'position': 3}, {'title': 'The New AI Business Model Making Millions in 2026', 'link': │ │ 'https://medium.com/write-a-catalyst/the-new-ai-business-model-making-millions-in-2026-94fa3434429e', │ │ 'snippet': 'At its core, this new model is about creating AI-powered stores — digital shops or revenue │ │ engines that sell automated products, services, or ...', 'position': 4}, {'title': 'AI Transformation 2026: │ │ 26 Predictions Redefining CX, EX ...', 'link': │ │ 'https://www.linkedin.com/pulse/ai-transformation-2026-26-predictions-redefining-cx-ex-saltz-gulko-twspf', │ │ 'snippet': 'By 2026, expect a surge of “citizen innovators” – front-line staff, marketers, operations │ │ managers – using easy AI tools to solve problems and ...', 'position': 5}, {'title': 'AI Trends for 2026: │ │ From Experimentation to Scalable ...', 'link': 'https://www.youtube.com/watch?v=vK0HL9kF8JI', 'snippet': '5 │ │ key AI trends shaping 2026: Agentic AI and autonomous agents The future of work: human–AI–robot collaboration │ │ Governance, security, and trust ...', 'position': 6}, {'title': 'AI-based Business Model Innovation 2026', │ │ 'link': 'https://www.innoman.fi/en/blog/ai-based-business-model-innovation-2026/', 'snippet': 'The business │ │ model has three main entities: value proposition, value capture and value creation. A value proposition is a │ │ promise to the ...', 'position': 7}, {'title': '10 AI Trends for 2026 Businesses Must Watch', 'link': │ │ 'https://thoughtminds.ai/blog/10-ai-trends-for-2026-what-businesses-must-watch-for-this-year', 'snippet': │ │ 'the newest AI innovations include autonomous agents, multimodal intelligence, edge computing, and even │ │ industry-specific models.', 'position': 8}, {'title': 'Action items for AI decision makers in 2026', 'link': │ │ 'https://mitsloan.mit.edu/ideas-made-to-matter/action-items-ai-decision-makers-2026', 'snippet': "1. Agentic │ │ AI isn't ready for prime time — yet · 2. The AI bubble will deflate, with economic ramifications · 3. │ │ Generative AI should become an ...", 'position': 9}], 'peopleAlsoAsk': [{'question': 'What are the new AI │ │ models coming in 2026?', 'snippet': 'New AI model releases planned in April 2026\n\nThe next major expected │ │ releases are Claude Mythos (Anthropic, timing uncertain), Grok 5 (xAI, Q2 2026), and GPT-5.5 (OpenAI, likely │ │ mid-2026). Prediction markets suggest Claude Mythos is the most likely April release.Apr 1, 2026', 'title': │ │ 'New AI Model Releases News | April, 2026 (STARTUP EDITION)', 'link': │ │ 'https://blog.mean.ceo/new-ai-model-releases-news-april-2026/#:~:text=New%20AI%20model%20releases%20planned%2 │ │ 0in%20April%202026,-The%20most%20current&text=The%20next%20major%20expected%20releases,the%20most%20likely%20 │ │ April%20release.'}, {'question': 'What is the AI innovation in 2026?', 'snippet': 'One of the defining trends │ │ of 2026, Agentic AI are systems capable of reasoning, planning, and executing tasks independently. Compared │ │ to their traditional counterparts, agentic AI systems can reach their goals by completing multiple steps, │ │ using various tools, and in any environment.Feb 4, 2026', 'title': '10 AI Trends for 2026 Businesses Must │ │ Watch - ThoughtMinds', 'link': │ │ 'https://thoughtminds.ai/blog/10-ai-trends-for-2026-what-businesses-must-watch-for-this-year#:~:text=One%20of │ │ %20the%20defining%20trends,tools%2C%20and%20in%20any%20environment.'}, {'question': 'What is a $900000 AI │ │ job?', 'snippet': 'A $900,000 AI job typically refers to a high-level position in artificial intelligence, │ │ such as senior machine learning engineer, AI research director, or executive roles, which offer compensation │ │ including salary, bonuses, and stock options.', 'title': 'Q: What is a $900000 AI job? - ZipRecruiter', │ │ 'link': │ │ 'https://www.ziprecruiter.com/e/Remote-Meta-Ai-What-is-a-900000-AI-job#:~:text=A%20%24900%2C000%20AI%20job%20 │ │ typically,%2C%20bonuses%2C%20and%20stock%20options.'}, {'question': 'Which AI model will grow most in │ │ popularity in 2026?', 'snippet': "Model 1: Multimodal Transformers. Multimodal Transformers represent a │ │ breakthrough in AI's ability to process and analyze diverse data types simultaneously. These models combine │ │ text, images, audio, and sensor inputs into a unified framework, enabling systems to understand context │ │ across modalities.Feb 10, 2026", 'title': 'Top 10 New AI Models to Explore in 2026 - Newline', 'link': │ │ 'https://www.newline.co/@Dipen/top-10-new-ai-models-to-explore-in-2026--b4ca6fcf#:~:text=into%20existing%20te │ │ chnologies.-,Model%201%3A%20Multimodal%20Transformers,to%20understand%20context%20across%20modalities.'}], │ │ 'relatedSearches': [{'query': 'Business model innovation in ai 2026'}, {'query': 'Hai 2026 ai index report'}, │ │ {'query': 'State of AI in 2026'}, {'query': 'AI models PDF'}, {'query': 'Public opinion of AI'}, {'query': │ │ 'AI hallucination rates 2026'}, {'query': 'AI competitiveness by country'}, {'query': 'AI power Index'}], │ │ 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'AI regulation and governance latest', 'type': 'search', 'num': 10, │ │ 'engine': 'google'}, 'organic': [{'title': 'AI governance trends: How regulation, collaboration, and skills │ │ demand are ...', 'link': 'https://www.weforum.org/stories/2024/09/ai-governance-trends-to-watch/', 'snippet': │ │ 'AI is transforming industries and there is a growing demand for innovative solutions and trained │ │ professionals to address governance needs ...', 'position': 1}, {'title': 'Regulating Under Uncertainty: │ │ Governance Options for Generative AI', 'link': │ │ 'https://cyber.fsi.stanford.edu/content/regulating-under-uncertainty-governance-options-generative-ai', │ │ 'snippet': 'The AI Act regulates AI systems based on risk levels and use cases, particularly in sensitive │ │ sectors. The Act categorizes risks based on the “intended” use of ...', 'position': 2}, {'title': 'AI Watch: │ │ Global regulatory tracker - United States', 'link': │ │ 'https://www.whitecase.com/insight-our-thinking/ai-watch-global-regulatory-tracker-united-states', 'snippet': │ │ 'Currently, there is no comprehensive federal legislation or regulations in the US that regulate the │ │ development of AI or specifically prohibit ...', 'position': 3}, {'title': 'Co-Governance and the Future of │ │ AI Regulation', 'link': │ │ 'https://harvardlawreview.org/print/vol-138/co-governance-and-the-future-of-ai-regulation/', 'snippet': 'The │ │ traditional top-down tack to regulation may stifle innovation and creativity and stop AI from realizing its │ │ transformative potential. But ...', 'position': 4}, {'title': 'Navigating the AI regulatory landscape: │ │ Balancing innovation, ...', 'link': 'https://www.tandfonline.com/doi/full/10.1080/20954816.2025.2569584', │ │ 'snippet': 'by G Perboli · 2025 · Cited by 20 — The current landscape of fragmented AI governance risks │ │ exacerbating global inequalities, creating regulatory arbitrage opportunities, and undermining efforts', │ │ 'position': 5}, {'title': 'Summary of Artificial Intelligence 2025 Legislation', 'link': │ │ 'https://www.ncsl.org/technology-and-communication/artificial-intelligence-2025-legislation', 'snippet': │ │ 'This webpage covers key legislation introduced during the 2025 legislative session related to AI issues │ │ generally.', 'position': 6}, {'title': 'AI Regulations around the World - 2026', 'link': │ │ 'https://www.mindfoundry.ai/blog/ai-regulations-around-the-world?hs_amp=true', 'snippet': "AI regulations │ │ worldwide are changing rapidly. This piece outlines the global regulatory landscape in 2025 and why it's │ │ important that we understand it.", 'position': 7}, {'title': 'Regulating Artificial Intelligence: U.S. and │ │ International Approaches and ...', 'link': 'https://www.congress.gov/crs-product/R48555', 'snippet': 'No │ │ federal legislation establishing broad regulatory authorities for the development or use of AI or │ │ prohibitions on AI has been enacted.', 'position': 8}, {'title': 'Webinar Future of AI Regulation and │ │ Governance', 'link': 'https://www.youtube.com/watch?v=W6GTupMJ5x8', 'snippet': 'AI regulation and governance │ │ is at a crossroads. A debate rages about whether current laws are too strict; efforts to halt or │ │ weaken\xa0...', 'position': 9}], 'relatedSearches': [{'query': 'Artificial Intelligence laws and │ │ regulations'}, {'query': 'Ai regulation and governance latest 2022'}, {'query': 'AI regulations around the │ │ world'}, {'query': 'Ai regulation debate'}, {'query': 'Regulating under uncertainty governance options for │ │ generative ai'}, {'query': 'Ai regulation in the us trump'}], 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'AI agents and automation advancements 2026', 'type': 'search', 'num': 10, │ │ 'engine': 'google'}, 'organic': [{'title': 'AI Trends 2026: Quantum, Agentic AI & Smarter Automation', │ │ 'link': 'https://www.youtube.com/watch?v=zt0JA5rxdfM', 'snippet': 'define AI in 2026? 🚀 Martin Keen & Aaron │ │ Baughman explore groundbreaking trends like Agentic AI, cloud computing, automation, and quantum ...', │ │ 'position': 1}, {'title': 'Future of AI Agents: Top Trends in 2026', 'link': │ │ 'https://www.blueprism.com/resources/blog/future-ai-agents-trends/', 'snippet': "In 2026, agentic automation │ │ will redraw the enterprise map. The question is no longer capability, it's control. The future won't belong │ │ to those ...", 'position': 2}, {'title': 'AI agent trends 2026 report', 'link': │ │ 'https://cloud.google.com/resources/content/ai-agent-trends-2026', 'snippet': 'Our new report reveals the 5 │ │ top trends in agentic AI that can help transform businesses, for 2026 and beyond. agents improve customer │ │ service, code quality, ...', 'position': 3}, {'title': 'AI agents for automation in 2026, sorted by use case. │ │ Not a ...', 'link': │ │ 'https://www.reddit.com/r/AI_Agents/comments/1szfsq4/ai_agents_for_automation_in_2026_sorted_by_use/', │ │ 'snippet': 'AI agents for automation in 2026, sorted. If your automation needs are tightly centered on │ │ commerce workflows order sync, inventory updates, ...', 'position': 4}, {'title': 'The 2026 Guide to AI │ │ Agents', 'link': 'https://www.ibm.com/think/ai-agents', 'snippet': 'In this comprehensive guide, you will │ │ find a collection of AI agent-related content such as educational explainers, hands-on tutorials, podcast │ │ episodes and ...', 'position': 5}, {'title': 'AI Agents Market Size, Share And Trends Report, 2026-2033', │ │ 'link': 'https://www.grandviewresearch.com/industry-analysis/ai-agents-market-report', 'snippet': 'The AI │ │ agents market size was valued at $7.6 billion in 2025, projected to grow from $10.9 billion in 2026 to $182.9 │ │ billion by 2033, at a CAGR of 49.6%', 'position': 6}, {'title': '2026: The Real Year of AI Agents & AI │ │ Automation', 'link': 'https://smartstudios.io/blog/2026-the-real-year-of-ai-agents-ai-automation/', │ │ 'snippet': 'In 2026, AI-powered platforms are becoming part of everyday operations across marketing, sales, │ │ HR, operations, and more. Some systems help move data between ...', 'position': 7}, {'title': 'Top 13 Agentic │ │ AI Trends to Watch in 2026', 'link': 'https://www.firecrawl.dev/blog/agentic-ai-trends', 'snippet': 'AI │ │ agents are making it dramatically more accessible and capable. The browser automation market is expected to │ │ grow 45% year-over-year, driven ...', 'position': 8}], 'relatedSearches': [{'query': 'Ai agents and │ │ automation advancements 2026 pdf'}, {'query': 'AI agent trends 2026 pdf'}, {'query': 'Google AI agent trends │ │ 2026'}, {'query': 'Ai agents trends 2026'}, {'query': 'AI agents 2026'}, {'query': '2026 State of AI agents │ │ report'}, {'query': 'Future of AI in 2026'}, {'query': 'AI 2026 predictions'}], 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'enterprise adoption of AI latest', 'type': 'search', 'num': 10, 'engine': │ │ 'google'}, 'organic': [{'title': 'The State of AI in the Enterprise - 2026 AI report', 'link': │ │ 'https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-i │ │ n-the-enterprise.html', 'snippet': 'Improving productivity and efficiency top the list of benefits achieved │ │ from enterprise AI adoption so far, with two-thirds (66%) of organizations reporting ...', 'position': 1}, │ │ {'title': 'AI Adoption by the Numbers: Where Enterprise AI is Actually Working', 'link': │ │ 'https://www.linkedin.com/pulse/ai-adoption-numbers-where-enterprise-actually-working-kimberly-tan-mygwf', │ │ 'snippet': 'Based on our analysis, 29% of the Fortune 500 and ~19% of the Global 2000 are live, paying │ │ customers of a leading AI startup.', 'position': 2}, {'title': 'AI adoption by small and medium-sized │ │ enterprises (EN)', 'link': │ │ 'https://www.oecd.org/content/dam/oecd/en/publications/reports/2025/12/ai-adoption-by-small-and-medium-sized- │ │ enterprises_9c48eae6/426399c1-en.pdf', 'snippet': 'between 2020 and 2024, the share of businesses with 10 │ │ employees or more using AI increased from 5.6% to 14% across OECD Member countries', 'position': 3}, │ │ {'title': 'State of AI: Enterprise Adoption & Growth Trends', 'link': │ │ 'https://www.databricks.com/blog/state-ai-enterprise-adoption-growth-trends', 'snippet': 'The state of AI in │ │ 2024 shows enterprise adoption accelerating with 11x more production models, 377% growth in vector databases, │ │ and 76% of ...', 'position': 4}, {'title': 'The state of enterprise AI', 'link': │ │ 'https://openai.com/index/the-state-of-enterprise-ai-2025-report/', 'snippet': 'Adoption is accelerating and │ │ deepening · Growth is rapid across industries and geographies · Workers report measurable value from using │ │ AI.', 'position': 5}, {'title': 'Top 10 trends in AI adoption for enterprises in 2025', 'link': │ │ 'https://www.glean.com/perspectives/enterprise-insights-from-ai', 'snippet': 'The enterprise AI market has │ │ exploded from $24 billion in 2024 to a projected $150-200 billion by 2030, with compound annual growth rates │ │ ...', 'position': 6}], 'relatedSearches': [{'query': 'Deloitte State of AI in the Enterprise'}, {'query': │ │ 'State of AI in the enterprise - 2026 Deloitte'}, {'query': 'Deloitte State of AI in the enterprise 2025'}, │ │ {'query': 'Deloitte AI scandal'}, {'query': 'Deloitte State of AI report 2026'}, {'query': 'Openai enterprise │ │ ai report'}], 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'AI infrastructure and chips development 2026', 'type': 'search', 'num': │ │ 10, 'engine': 'google'}, 'organic': [{'title': 'Key Trends Shaping the Semiconductor Industry in 2026', │ │ 'link': 'https://www.edge-ai-vision.com/2026/04/key-trends-shaping-the-semiconductor-industry-in-2026/', │ │ 'snippet': "Physical AI will grow faster than data AI in 2026—here's the evidence. The next wave of AI chip │ │ demand will come from AI embedded in physical ...", 'position': 1}, {'title': '[Expert POV] The real │ │ battleground in the AI semiconductor ...', 'link': 'https://news.skhynix.com/2026-expert-column-series-ep3/', │ │ 'snippet': 'Beginning in 2026, however, AI is expected to expand more deeply into the physical world, │ │ diversifying into AI transformation (AX) models3 and ...', 'position': 2}, {'title': 'The AI Inference Pivot: │ │ Why 2026 Could Be The Most ...', 'link': 'https://www.youtube.com/watch?v=1xTCgdX7A_8', 'snippet': 'Robert │ │ Maire of Semiconductor Advisors discusses the key themes and trends that will drive the chip sector in │ │ 2026.', 'position': 3}, {'title': 'AI in Semiconductor Industry: What Will Drive 2026 Growth', 'link': │ │ 'https://www.crispidea.com/ai-in-semiconductor-industry-2026/', 'snippet': 'In 2026, AI chips account for │ │ roughly 50% of revenue but less than 0.2% of total unit volume. This is because high-end AI accelerators │ │ (like ...', 'position': 4}, {'title': 'After a Year of Blistering Growth, AI Chip Makers Get ...', 'link': │ │ 'https://www.wsj.com/tech/ai/after-a-year-of-blistering-growth-ai-chip-makers-get-ready-for-bigger-2026-d9f62 │ │ dbd', 'snippet': 'Semiconductor companies achieved over $400 billion in combined sales in 2025, driven by AI │ │ growth, with 2026 projected to be even larger.', 'position': 5}, {'title': 'AI to Reshape the Global │ │ Technology Landscape in 2026 ...', 'link': │ │ 'https://www.prnewswire.com/news-releases/ai-to-reshape-the-global-technology-landscape-in-2026-says-trendfor │ │ ce-302626789.html', 'snippet': "PRNewswire/ -- TrendForce has identified 10 key technology trends that will │ │ define the tech industry's evolution in 2026.", 'position': 6}, {'title': 'AI Infrastructure in 2026: │ │ Challenges, Reality & Enterprise ...', 'link': 'https://www.youtube.com/watch?v=qHbgWP8ynSM', 'snippet': 'Rob │ │ Hirschfeld, CEO … 2026 holds for companies building AI factories, trying to exit VMware, and navigating the │ │ hype around agentic AI.', 'position': 7}, {'title': 'Top 10 AI Infrastructure Stocks to Buy in 2026', 'link': │ │ 'https://bingx.com/en/learn/article/top-ai-infrastructure-stocks-to-buy-chip-manufacturing-and-design-leaders │ │ ', 'snippet': 'Leading hyperscalers and technology conglomerates are projected to spend nearly $700 billion │ │ in 2026 alone on AI data centers, high-speed ...', 'position': 8}], 'peopleAlsoAsk': [{'question': 'What are │ │ the latest AI developments 2026?', 'snippet': '', 'title': '', 'link': ''}, {'question': 'What makes AI │ │ infrastructure production ready in 2026?', 'snippet': 'In 2026, production-ready AI infrastructure is not │ │ defined by just compute scale alone. It is defined by repeatable deployment, governed lifecycle, measurable │ │ quality, resilient operations, and predictable economics.Feb 11, 2026', 'title': 'What Makes AI │ │ Infrastructure Truly Production-Ready in 2026 - Gruve', 'link': │ │ 'https://gruve.ai/blog/what-makes-ai-infrastructure-production-ready-in-2026/#:~:text=In%202026%2C%20producti │ │ on%2Dready%20AI,resilient%20operations%2C%20and%20predictable%20economics.'}, {'question': 'Which companies │ │ are building AI chips?', 'snippet': 'The Top Six AI Chip Manufacturers in the World in 2025\n___Taiwan │ │ Semiconductor Manufacturing Company (TSMC) Headquarters: Hsinchu, Taiwan. ...\n___Samsung Foundry (Samsung │ │ Electronics) ...\n___GlobalFoundries. ...\n___Semiconductor Manufacturing International Corporation (SMIC) │ │ ...\n___United Microelectronics Corporation (UMC) ...\n___Intel Foundry Services (IFS)', 'title': 'The List │ │ of the Top Six AI Chip Manufacturers in 2025 - CubeFabs', 'link': │ │ 'https://cubefabs.com/resources/the-top-ai-chip-manufacturers-in-2025'}, {'question': 'What is the 30% rule │ │ in AI?', 'snippet': '', 'title': '', 'link': ''}], 'relatedSearches': [{'query': 'Manus ai sold to meta'}, │ │ {'query': 'Facebook buys AI company'}, {'query': 'Manus ai stock price'}, {'query': 'Wsj Meta Manus'}, │ │ {'query': "Five things to know about nvidia's $20 billion licensing deal"}, {'query': 'Nvidia deals'}, │ │ {'query': 'Meta manus acquisition price'}, {'query': 'Meta buys AI startup'}], 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#6) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_the_internet_with_serper │ │ Output: {'searchParameters': {'q': 'latest AI industry trends 2026 news', 'type': 'search', 'num': 10, │ │ 'engine': 'google'}, 'organic': [{'title': "What's next in AI: 7 trends to watch in 2026", 'link': │ │ 'https://news.microsoft.com/source/features/ai/whats-next-in-ai-7-trends-to-watch-in-2026/', 'snippet': │ │ 'Seven AI trends to watch in 2026 will make AI a true partner — boosting teamwork, security, research │ │ momentum and infrastructure efficiency.', 'position': 1}, {'title': 'AI Trends 2026', 'link': │ │ 'https://www.infotech.com/research/ss/ai-trends-2026', 'snippet': 'Five AI trends will shape IT in 2026 · 1. │ │ Foundational AI principles will rewrite organizational DNA · 2. From copilots to vibe coding: AI will │ │ continue to ...', 'position': 2}, {'title': 'The trends that will shape AI and tech in 2026', 'link': │ │ 'https://www.ibm.com/think/news/ai-tech-trends-predictions-2026', 'snippet': 'Reporter Anabelle Nicoud spoke │ │ to several experts across AI, security, quantum and beyond to better understand where tech will take us in │ │ 2026.', 'position': 3}, {'title': 'Five Trends in AI and Data Science for 2026', 'link': │ │ 'https://sloanreview.mit.edu/article/five-trends-in-ai-and-data-science-for-2026/', 'snippet': "From the AI │ │ bubble to GenAI's rise as an organizational tool, these are the 2026 AI trends to watch. Explore new data and │ │ advice from AI experts ...", 'position': 4}, {'title': 'The 9 AI Trends that Will Define 2026 (Researched & │ │ Ranked)', 'link': 'https://www.youtube.com/watch?v=tJS_ycc2lNs&vl=en', 'snippet': 'From autonomous AI agents │ │ and reasoning models to AI-driven discovery, hardware breakthroughs, and workforce disruption, these trends │ │ reveal', 'position': 5}, {'title': 'Top AI Trends for 2026: Key Innovations Reshaping Modern ...', 'link': │ │ 'https://talent500.com/blog/ai-trends-2026-for-business-growth/', 'snippet': '1. Generative AI for Content │ │ and Code Creation 2. AI-Powered Automation at Scale 3. Hyper-Personalized Customer Experiences 4. AI in │ │ Decision ...', 'position': 6}, {'title': 'Top Technology Trends 2026: The AI Era Redefined by Humans', │ │ 'link': 'https://sigmatechnology.com/articles/tech-trends-in-2026-signals-not-noise/', 'snippet': 'AI │ │ expected to surpass USD 6 trillion for the first time, as enterprises shift their focus from proof-of-concept │ │ AI to full-scale, secure ...', 'position': 7}, {'title': 'Top 6 AI Trends That Will Define 2026 (backed by │ │ data)', 'link': 'https://www.youtube.com/watch?v=B23W1gRT9eY', 'snippet': 'This video covers six trends │ │ backed by data from McKinsey, Stanford, #OpenAI, and Epoch AI, with specific steps you can take for each one. │ │ a\xa0...', 'position': 8}, {'title': 'Top AI Trends in 2026: How Ready Are You?', 'link': │ │ 'https://fptsoftware.com/resource-center/blogs/top-ai-trends-in-2026', 'snippet': 'Top AI Trends in 2026: How │ │ Ready Are You? · AI agents will increase productivity for employees at all levels · AI infrastructure becomes │ │ smarter.', 'position': 9}], 'peopleAlsoAsk': [{'question': 'What are the new AI trends in 2026?', 'snippet': │ │ '', 'title': '', 'link': ''}, {'question': 'Is AI going to boom in 2026?', 'snippet': 'AI hype has been │ │ unstoppable for years — but now 2026 is starting to feel eerily similar to past tech bubbles. The world is │ │ spending trillions on AI infrastructure, models, and agents, and forecasts expect over $2.5 trillion in AI │ │ spending this year alone.Feb 1, 2026', 'title': '', 'link': ''}, {'question': 'What are the three new AI │ │ breakthroughs shaping 2026?', 'snippet': 'Among the most influential trends driving innovation and disruption │ │ are agentic AI, physical AI, and sovereign AI. Each presents new opportunities and challenges for │ │ organizations and individuals.Jul 18, 2025', 'title': '', 'link': ''}, {'question': 'What are the biggest │ │ trends in AI right now?', 'snippet': '', 'title': '', 'link': ''}], 'relatedSearches': [{'query': 'Latest ai │ │ industry trends 2026 news today'}, {'query': 'Latest ai industry trends 2026 news pdf'}, {'query': 'AI 2026 │ │ predictions'}, {'query': 'AI agent trends 2026 pdf'}, {'query': 'AI trends 2026'}, {'query': 'New AI │ │ technology 2026'}, {'query': 'Latest AI technology news'}, {'query': 'Latest trends in AI technology'}, │ │ {'query': 'AI trends on social media'}, {'query': 'Latest AI trend photo'}], 'credits': 1} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'latest AI industry trends 2026 news', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': "What's next in AI: 7 trends to watch in 2026", 'link': 'https...
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'model innovation in AI 2026', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': 'The 2026 AI Index Report | Stanford HAI', 'link': 'https://hai.stanfo...
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'enterprise adoption of AI latest', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': 'The State of AI in the Enterprise - 2026 AI report', 'link': 'ht...
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'AI regulation and governance latest', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': 'AI governance trends: How regulation, collaboration, and skil...
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'AI infrastructure and chips development 2026', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': 'Key Trends Shaping the Semiconductor Industry in 202...
Tool search_the_internet_with_serper executed with result: {'searchParameters': {'q': 'AI agents and automation advancements 2026', 'type': 'search', 'num': 10, 'engine': 'google'}, 'organic': [{'title': 'AI Trends 2026: Quantum, Agentic AI & Smarter Automati...
[Finalize] todos_count=0, todos_with_results=0
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Market Research Analyst │ │ │ │ Final Answer: │ │ Based on a comprehensive review of recent and high-quality sources from industry reports, news, expert │ │ analyses, and market forecasts about the AI industry trends in 2026, the top 3 most materially important and │ │ current trends shaping the AI landscape are: │ │ │ │ --- │ │ │ │ 1. Agentic AI and Autonomous AI Agents Redefining Enterprise Automation │ │ Description: Agentic AI systems, capable of autonomous decision-making, multi-step reasoning, and independent │ │ task execution, are becoming pivotal in enterprise automation and operational transformation. │ │ Why it Matters: Unlike traditional AI models that respond to direct prompts, agentic AI acts proactively with │ │ goal-oriented behavior, taking over complex workflows and freeing human workers from routine cognitive tasks. │ │ This leap enables a new class of productivity tools and automated services that scale enterprise capabilities │ │ significantly. │ │ Unique Perspective: The rise of agentic AI signals a foundational shift in how businesses view automation—not │ │ just as a cost-saving measure but as a strategic lever for competitive advantage. By deploying AI agents that │ │ collaborate seamlessly with humans across departments like marketing, sales, HR, and operations, companies │ │ can reengineer workflows for agility and innovation, potentially outpacing competitors locked in older │ │ automation paradigms. │ │ │ │ --- │ │ │ │ 2. Rapid Enterprise Adoption and Market Expansion of AI Across Industries │ │ Description: AI adoption in enterprises is accelerating rapidly, with significant growth in AI-powered │ │ production models, vector databases, and tailored industry applications boosting operational efficiency and │ │ innovation at scale. │ │ Why it Matters: Recent data indicate that a substantial portion of Fortune 500 and Global 2000 companies are │ │ live, paying customers of leading AI startups, driving the enterprise AI market from tens of billions in 2024 │ │ toward projected valuations exceeding $150-200 billion by 2030. Productivity gains and measurable business │ │ value reported by workers underscore AI's transitioning role from exploratory technology to essential │ │ business infrastructure. │ │ Unique Perspective: This trend reflects a maturing AI market where technology adoption correlates directly │ │ with strategic importance. Enterprises that embed AI deeply into their processes—not just experimental or │ │ siloed use—are likely to reshape cost structures and innovation cycles. This embeds AI as a core driver of │ │ digital transformation, amplifying organizational intelligence and responsiveness to market changes. │ │ │ │ --- │ │ │ │ 3. Evolution of AI Regulation, Governance, and Responsible AI Practices │ │ Description: Global regulatory efforts, governance frameworks, and industry collaborations are evolving │ │ rapidly to address risks associated with AI deployment, including ethical use, transparency, data privacy, │ │ and risk-based oversight tailored to AI’s complexity and impact. │ │ Why it Matters: As AI technologies proliferate, regulatory bodies worldwide are crafting nuanced approaches │ │ rather than blanket bans. The emergence of risk-category-based AI Acts (e.g., in the EU) and calls for │ │ co-governance models that balance innovation and safety highlight the critical need for frameworks ensuring │ │ AI’s trustworthy and equitable use. Governance is increasingly central to AI’s sustainable integration in │ │ business and society. │ │ Unique Perspective: The AI regulatory landscape transformation is not merely about compliance costs but an │ │ enabler of long-term AI adoption and public trust. Companies leading in responsible AI governance could gain │ │ reputational benefits and reduce operational risks, while jurisdictions pioneering balanced AI regulations │ │ might attract greater AI investments and innovation. This trend underscores the interplay between │ │ technological advancement and societal values shaping AI’s future trajectory. │ │ │ │ --- │ │ │ │ In summary, 2026 stands out as a landmark year where the convergence of autonomous AI capabilities, │ │ widespread enterprise integration, and emerging regulatory clarity collectively reshape the AI industry. This │ │ triad drives not only technological sophistication but also profound strategic implications for │ │ competitiveness, operational model innovation, and trust-building in AI adoption. These trends are supported │ │ by multiple independent reports and market analyses, reflecting their broad impact and scalability potential │ │ across sectors. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective │ │ internally as: identify the top 3 most current and materially important trends in the AI industry, not just │ │ general news. Prioritize developments that are both recent and industry-shaping. │ │ 2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search │ │ query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry │ │ developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest. │ │ 3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise │ │ adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is │ │ balanced and not overly dependent on one type of development. │ │ 4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across │ │ multiple sources, since trends supported by several independent reports are more likely to be truly │ │ significant. │ │ 5. For each candidate trend, capture the following: what is happening, why it is trending now, which │ │ companies or sectors are involved, and what the broader implication is for the AI industry. │ │ 6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, │ │ technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined │ │ significance rather than simply recency. │ │ 7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short │ │ explanation of why it matters, and a unique perspective on its significance. The unique perspective should │ │ connect the trend to a broader business or societal implication, such as competitive advantage, cost │ │ structure changes, trust and compliance, or shifts in product design. │ │ 8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and │ │ keep terminology current. Remove redundant or weakly supported claims. │ │ 9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with │ │ each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and │ │ grounded in evidence. │ │ Agent: Market Research Analyst │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Write an engaging blog post about the AI industry, based on the research analysts summary. Draw │ │ inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary │ │ carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the │ │ factual backbone of the blog post. │ │ 2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most │ │ relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude. │ │ 3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for │ │ recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and │ │ whether the writing uses examples, analogies, or plain-language explanations. │ │ 4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the │ │ new post original. Note phrases, pacing, and formatting conventions that improve readability without copying │ │ content. │ │ 5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging │ │ hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three │ │ with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves │ │ the reader with a clear takeaway. │ │ 6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English │ │ explanations, and when technical terms are necessary, define them briefly in context so the post remains │ │ approachable to a general audience. │ │ 7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs │ │ should inform and explain the trends clearly, and the final paragraph should synthesize the implications for │ │ businesses, creators, or everyday users. │ │ 8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained │ │ phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or │ │ dense industry jargon. │ │ 9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it │ │ reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments │ │ drawn from the analyst summary and inspired by the directory’s best examples. │ │ 10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and │ │ maintains a polished blog voice consistent with the examples reviewed from the directory. │ │ ID: bfe7e7e8-7003-402f-844b-6a56b5e12d51 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: Content Writer │ │ │ │ Task: Write an engaging blog post about the AI industry, based on the research analysts summary. Draw │ │ inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary │ │ carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the │ │ factual backbone of the blog post. │ │ 2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most │ │ relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude. │ │ 3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for │ │ recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and │ │ whether the writing uses examples, analogies, or plain-language explanations. │ │ 4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the │ │ new post original. Note phrases, pacing, and formatting conventions that improve readability without copying │ │ content. │ │ 5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging │ │ hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three │ │ with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves │ │ the reader with a clear takeaway. │ │ 6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English │ │ explanations, and when technical terms are necessary, define them briefly in context so the post remains │ │ approachable to a general audience. │ │ 7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs │ │ should inform and explain the trends clearly, and the final paragraph should synthesize the implications for │ │ businesses, creators, or everyday users. │ │ 8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained │ │ phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or │ │ dense industry jargon. │ │ 9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it │ │ reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments │ │ drawn from the analyst summary and inspired by the directory’s best examples. │ │ 10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and │ │ maintains a polished blog voice consistent with the examples reviewed from the directory. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#1) ─────────────────────────────────────────╮ │ │ │ Tool: list_files_in_directory │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#1) ─────────────────────────────────────────╮ │ │ │ Tool: read_a_files_content │ │ Args: {'file_path': './blog-posts/ai-industry-2025-insights.md', 'start_line': 1, 'line_count': 20} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#2) ─────────────────────────────────────────╮ │ │ │ Tool: read_a_files_content │ │ Args: {'file_path': './blog-posts/future-of-ai-enterprise.md', 'start_line': 1, 'line_count': 20} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#1) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: list_files_in_directory │ │ Output: File paths: │ │ -/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool list_files_in_directory executed with result: File paths:
-/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md...
Tool read_a_files_content executed with result: Error: File not found at path: blog-posts/ai-industry-2025-insights.md...
Tool read_a_files_content executed with result: Error: File not found at path: blog-posts/future-of-ai-enterprise.md...
╭─────────────────────────────────────── ✅ Tool Execution Completed (#2) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: read_a_files_content │ │ Output: Error: File not found at path: blog-posts/future-of-ai-enterprise.md │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#2) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: read_a_files_content │ │ Output: Error: File not found at path: blog-posts/ai-industry-2025-insights.md │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool list_files_in_directory executed with result (from cache): File paths:
-/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md...
╭──────────────────────────────────────── 🔧 Tool Execution Started (#2) ─────────────────────────────────────────╮ │ │ │ Tool: list_files_in_directory │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────── ✅ Tool Execution Completed (#2) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: list_files_in_directory │ │ Output: File paths: │ │ -/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#3) ─────────────────────────────────────────╮ │ │ │ Tool: read_a_files_content │ │ Args: {'file_path': '/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md', 'start_line': 1, │ │ 'line_count': 50} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool read_a_files_content executed with result: # AI Industry Trends in 2024: A Transformative Shift in Technology and Business
The AI landscape in 2024 is undergoing a profound transformation, marked by rapid growth and new paradigms in intellige...
╭─────────────────────────────────────── ✅ Tool Execution Completed (#3) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: read_a_files_content │ │ Output: # AI Industry Trends in 2024: A Transformative Shift in Technology and Business │ │ │ │ The AI landscape in 2024 is undergoing a profound transformation, marked by rapid growth and new paradigms in │ │ intelligence and autonomy. At the forefront is agentic AI—autonomous systems capable of independently │ │ executing complex tasks across digital and physical realms. This technology is swiftly evolving from a │ │ supplementary assistant into a central driver of operational efficiency and innovation. Enterprises across │ │ commerce, manufacturing, and governance are adopting these AI agents to streamline workflows and make smarter │ │ decisions, signaling a shift in how work gets done. This transition holds huge implications for productivity │ │ and competitiveness, as companies that harness trustworthy and capable agentic AI stand to redefine market │ │ leadership in the coming decade. │ │ │ │ Foundational AI models remain the bedrock of this revolution, serving as versatile platforms powering an │ │ array of applications. In 2024, there is a growing emphasis on transparency, open competition, and ethical │ │ deployment of these vast models. The rise of powerful open-source alternatives alongside proprietary systems │ │ spurs a dynamic ecosystem that fosters innovation while challenging traditional market power structures. This │ │ environment encourages more accessible and diverse AI tools, though it also calls for vigilant oversight to │ │ manage risks like bias and safety. The evolving interplay between openness and control in foundation models │ │ is shaping not only technological progress but also the regulatory and policy framework guiding AI’s future. │ │ │ │ Supporting these advancements is the rapidly expanding AI infrastructure ecosystem, encompassing specialized │ │ chips, cloud platforms, and data centers optimized for AI workloads. This backbone is critical to scaling AI │ │ applications from research prototypes to real-world impact. Infrastructure investments are skyrocketing, │ │ reflecting the capital-intensive nature of AI development and deployment. Leading tech players are racing to │ │ secure control over hardware supply chains and develop more efficient, powerful computing resources. These │ │ trends underscore the strategic importance of AI infrastructure in driving cost-effective innovation, │ │ determining where AI capabilities flourish geographically, and influencing global technology leadership amid │ │ complex geopolitical dynamics. │ │ │ │ Together, these trends paint a picture of a maturing AI industry that integrates cutting-edge autonomy, │ │ foundational model evolution, and robust infrastructure growth. For businesses, creators, and policymakers, │ │ understanding and engaging with this intertwined landscape is essential to unlocking AI’s full potential. The │ │ rapid commercialization of agentic AI, coupled with a push for transparency and open competition in │ │ foundation models, all powered by a deepening infrastructure base, sets the stage for an AI-powered future │ │ that is more dynamic, inclusive, and impactful than ever before. The journey ahead promises not just │ │ technological breakthroughs but also a reimagining of how innovation shapes society and markets worldwide. │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[Finalize] todos_count=0, todos_with_results=0
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Content Writer │ │ │ │ Final Answer: │ │ ```markdown │ │ # The AI Industry in 2026: Autonomous Agents, Enterprise Growth, and Responsible Innovation │ │ │ │ Artificial intelligence is no longer just a buzzword or a futuristic idea—it has become a transformative │ │ force reshaping how businesses operate and innovate. In 2026, three powerful trends are driving this change: │ │ the rise of autonomous AI agents that act independently to automate complex workflows, the rapid adoption of │ │ AI across industries as it shifts from experimental to essential infrastructure, and the evolution of │ │ thoughtful regulation and governance to ensure AI is used responsibly. Together, these trends paint a future │ │ where AI is both a strategic partner for enterprises and a trusted technology for society. │ │ │ │ At the forefront is agentic AI, a new breed of intelligent systems designed to make decisions, learn from │ │ experience, and complete multi-step tasks without constant human input. Unlike traditional AI that reacts to │ │ direct commands, these autonomous agents proactively manage workflows across departments like marketing, │ │ sales, and operations, freeing professionals from routine cognitive work. This shift is more than just saving │ │ time or cutting costs—it represents a fundamental rethinking of automation as a source of competitive │ │ advantage. Companies deploying these AI agents are poised to innovate and respond to market changes faster, │ │ setting new standards for agility and productivity. │ │ │ │ Simultaneously, AI adoption is booming in enterprises worldwide, with major companies integrating AI deeply │ │ into their operations rather than using it in isolated pilots. This broader deployment includes sophisticated │ │ production models, industry-specific AI tools, and advanced data systems such as vector databases that boost │ │ decision-making speed and accuracy. This maturity in AI use is reflected in soaring market valuations and │ │ measurable productivity improvements reported by workers. AI is fast becoming the backbone of business │ │ innovation and digital transformation, helping organizations optimize costs, accelerate product development, │ │ and stay ahead of competitors in a rapidly changing landscape. │ │ │ │ Lastly, as AI’s impact grows, so too does the need for robust regulation and ethical governance. Across the │ │ globe, governments and industry groups are crafting frameworks that balance encouraging innovation with │ │ minimizing risks like bias, privacy breaches, and misuse. New laws categorize AI applications based on their │ │ risk, creating tailored rules that protect users while allowing beneficial technologies to flourish. │ │ Responsible AI governance is no longer just a compliance issue—it’s a competitive differentiator that builds │ │ public trust and attracts investment. As businesses advance AI adoption aligned with ethical standards, they │ │ lay the groundwork for sustainable growth and long-term societal benefits. │ │ │ │ Overall, the AI industry in 2026 is entering a dynamic phase where autonomous capabilities, widespread │ │ enterprise integration, and careful regulation converge. This combination not only advances technology but │ │ also transforms strategic business models and societal values. For companies, creators, and everyday users, │ │ embracing these trends means participating in an AI-powered future that is smarter, more efficient, and more │ │ trustworthy. The promise of AI lies not just in what it can do today, but in how it can empower us all to │ │ innovate and thrive responsibly in the years ahead. │ │ ``` │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Write an engaging blog post about the AI industry, based on the research analysts summary. Draw │ │ inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary │ │ carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the │ │ factual backbone of the blog post. │ │ 2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most │ │ relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude. │ │ 3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for │ │ recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and │ │ whether the writing uses examples, analogies, or plain-language explanations. │ │ 4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the │ │ new post original. Note phrases, pacing, and formatting conventions that improve readability without copying │ │ content. │ │ 5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging │ │ hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three │ │ with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves │ │ the reader with a clear takeaway. │ │ 6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English │ │ explanations, and when technical terms are necessary, define them briefly in context so the post remains │ │ approachable to a general audience. │ │ 7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs │ │ should inform and explain the trends clearly, and the final paragraph should synthesize the implications for │ │ businesses, creators, or everyday users. │ │ 8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained │ │ phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or │ │ dense industry jargon. │ │ 9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it │ │ reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments │ │ drawn from the analyst summary and inspired by the directory’s best examples. │ │ 10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and │ │ maintains a polished blog voice consistent with the examples reviewed from the directory. │ │ Agent: Content Writer │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Crew Completion ────────────────────────────────────────────────╮ │ │ │ Crew Execution Completed │ │ Name: crew │ │ ID: 81b70ca7-00ba-4a47-90c2-3fe4a8622e99 │ │ Final Output: ```markdown │ │ # The AI Industry in 2026: Autonomous Agents, Enterprise Growth, and Responsible Innovation │ │ │ │ Artificial intelligence is no longer just a buzzword or a futuristic idea—it has become a transformative │ │ force reshaping how businesses operate and innovate. In 2026, three powerful trends are driving this change: │ │ the rise of autonomous AI agents that act independently to automate complex workflows, the rapid adoption of │ │ AI across industries as it shifts from experimental to essential infrastructure, and the evolution of │ │ thoughtful regulation and governance to ensure AI is used responsibly. Together, these trends paint a future │ │ where AI is both a strategic partner for enterprises and a trusted technology for society. │ │ │ │ At the forefront is agentic AI, a new breed of intelligent systems designed to make decisions, learn from │ │ experience, and complete multi-step tasks without constant human input. Unlike traditional AI that reacts to │ │ direct commands, these autonomous agents proactively manage workflows across departments like marketing, │ │ sales, and operations, freeing professionals from routine cognitive work. This shift is more than just saving │ │ time or cutting costs—it represents a fundamental rethinking of automation as a source of competitive │ │ advantage. Companies deploying these AI agents are poised to innovate and respond to market changes faster, │ │ setting new standards for agility and productivity. │ │ │ │ Simultaneously, AI adoption is booming in enterprises worldwide, with major companies integrating AI deeply │ │ into their operations rather than using it in isolated pilots. This broader deployment includes sophisticated │ │ production models, industry-specific AI tools, and advanced data systems such as vector databases that boost │ │ decision-making speed and accuracy. This maturity in AI use is reflected in soaring market valuations and │ │ measurable productivity improvements reported by workers. AI is fast becoming the backbone of business │ │ innovation and digital transformation, helping organizations optimize costs, accelerate product development, │ │ and stay ahead of competitors in a rapidly changing landscape. │ │ │ │ Lastly, as AI’s impact grows, so too does the need for robust regulation and ethical governance. Across the │ │ globe, governments and industry groups are crafting frameworks that balance encouraging innovation with │ │ minimizing risks like bias, privacy breaches, and misuse. New laws categorize AI applications based on their │ │ risk, creating tailored rules that protect users while allowing beneficial technologies to flourish. │ │ Responsible AI governance is no longer just a compliance issue—it’s a competitive differentiator that builds │ │ public trust and attracts investment. As businesses advance AI adoption aligned with ethical standards, they │ │ lay the groundwork for sustainable growth and long-term societal benefits. │ │ │ │ Overall, the AI industry in 2026 is entering a dynamic phase where autonomous capabilities, widespread │ │ enterprise integration, and careful regulation converge. This combination not only advances technology but │ │ also transforms strategic business models and societal values. For companies, creators, and everyday users, │ │ embracing these trends means participating in an AI-powered future that is smarter, more efficient, and more │ │ trustworthy. The promise of AI lies not just in what it can do today, but in how it can empower us all to │ │ innovate and thrive responsibly in the years ahead. │ │ ``` │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
CrewOutput(raw='```markdown\n# The AI Industry in 2026: Autonomous Agents, Enterprise Growth, and Responsible Innovation\n\nArtificial intelligence is no longer just a buzzword or a futuristic idea—it has become a transformative force reshaping how businesses operate and innovate. In 2026, three powerful trends are driving this change: the rise of autonomous AI agents that act independently to automate complex workflows, the rapid adoption of AI across industries as it shifts from experimental to essential infrastructure, and the evolution of thoughtful regulation and governance to ensure AI is used responsibly. Together, these trends paint a future where AI is both a strategic partner for enterprises and a trusted technology for society.\n\nAt the forefront is agentic AI, a new breed of intelligent systems designed to make decisions, learn from experience, and complete multi-step tasks without constant human input. Unlike traditional AI that reacts to direct commands, these autonomous agents proactively manage workflows across departments like marketing, sales, and operations, freeing professionals from routine cognitive work. This shift is more than just saving time or cutting costs—it represents a fundamental rethinking of automation as a source of competitive advantage. Companies deploying these AI agents are poised to innovate and respond to market changes faster, setting new standards for agility and productivity.\n\nSimultaneously, AI adoption is booming in enterprises worldwide, with major companies integrating AI deeply into their operations rather than using it in isolated pilots. This broader deployment includes sophisticated production models, industry-specific AI tools, and advanced data systems such as vector databases that boost decision-making speed and accuracy. This maturity in AI use is reflected in soaring market valuations and measurable productivity improvements reported by workers. AI is fast becoming the backbone of business innovation and digital transformation, helping organizations optimize costs, accelerate product development, and stay ahead of competitors in a rapidly changing landscape.\n\nLastly, as AI’s impact grows, so too does the need for robust regulation and ethical governance. Across the globe, governments and industry groups are crafting frameworks that balance encouraging innovation with minimizing risks like bias, privacy breaches, and misuse. New laws categorize AI applications based on their risk, creating tailored rules that protect users while allowing beneficial technologies to flourish. Responsible AI governance is no longer just a compliance issue—it’s a competitive differentiator that builds public trust and attracts investment. As businesses advance AI adoption aligned with ethical standards, they lay the groundwork for sustainable growth and long-term societal benefits.\n\nOverall, the AI industry in 2026 is entering a dynamic phase where autonomous capabilities, widespread enterprise integration, and careful regulation converge. This combination not only advances technology but also transforms strategic business models and societal values. For companies, creators, and everyday users, embracing these trends means participating in an AI-powered future that is smarter, more efficient, and more trustworthy. The promise of AI lies not just in what it can do today, but in how it can empower us all to innovate and thrive responsibly in the years ahead.\n```', pydantic=None, json_dict=None, tasks_output=[TaskOutput(description='Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective internally as: identify the top 3 most current and materially important trends in the AI industry, not just general news. Prioritize developments that are both recent and industry-shaping.\n2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest.\n3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is balanced and not overly dependent on one type of development.\n4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across multiple sources, since trends supported by several independent reports are more likely to be truly significant.\n5. For each candidate trend, capture the following: what is happening, why it is trending now, which companies or sectors are involved, and what the broader implication is for the AI industry.\n6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined significance rather than simply recency.\n7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short explanation of why it matters, and a unique perspective on its significance. The unique perspective should connect the trend to a broader business or societal implication, such as competitive advantage, cost structure changes, trust and compliance, or shifts in product design.\n8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and keep terminology current. Remove redundant or weakly supported claims.\n9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and grounded in evidence.', name='Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective internally as: identify the top 3 most current and materially important trends in the AI industry, not just general news. Prioritize developments that are both recent and industry-shaping.\n2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest.\n3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is balanced and not overly dependent on one type of development.\n4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across multiple sources, since trends supported by several independent reports are more likely to be truly significant.\n5. For each candidate trend, capture the following: what is happening, why it is trending now, which companies or sectors are involved, and what the broader implication is for the AI industry.\n6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined significance rather than simply recency.\n7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short explanation of why it matters, and a unique perspective on its significance. The unique perspective should connect the trend to a broader business or societal implication, such as competitive advantage, cost structure changes, trust and compliance, or shifts in product design.\n8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and keep terminology current. Remove redundant or weakly supported claims.\n9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and grounded in evidence.', expected_output='A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.', summary='Research the latest trends in the AI industry and provide...', raw="Based on a comprehensive review of recent and high-quality sources from industry reports, news, expert analyses, and market forecasts about the AI industry trends in 2026, the top 3 most materially important and current trends shaping the AI landscape are:\n\n---\n\n1. Agentic AI and Autonomous AI Agents Redefining Enterprise Automation \nDescription: Agentic AI systems, capable of autonomous decision-making, multi-step reasoning, and independent task execution, are becoming pivotal in enterprise automation and operational transformation. \nWhy it Matters: Unlike traditional AI models that respond to direct prompts, agentic AI acts proactively with goal-oriented behavior, taking over complex workflows and freeing human workers from routine cognitive tasks. This leap enables a new class of productivity tools and automated services that scale enterprise capabilities significantly. \nUnique Perspective: The rise of agentic AI signals a foundational shift in how businesses view automation—not just as a cost-saving measure but as a strategic lever for competitive advantage. By deploying AI agents that collaborate seamlessly with humans across departments like marketing, sales, HR, and operations, companies can reengineer workflows for agility and innovation, potentially outpacing competitors locked in older automation paradigms.\n\n---\n\n2. Rapid Enterprise Adoption and Market Expansion of AI Across Industries \nDescription: AI adoption in enterprises is accelerating rapidly, with significant growth in AI-powered production models, vector databases, and tailored industry applications boosting operational efficiency and innovation at scale. \nWhy it Matters: Recent data indicate that a substantial portion of Fortune 500 and Global 2000 companies are live, paying customers of leading AI startups, driving the enterprise AI market from tens of billions in 2024 toward projected valuations exceeding $150-200 billion by 2030. Productivity gains and measurable business value reported by workers underscore AI's transitioning role from exploratory technology to essential business infrastructure. \nUnique Perspective: This trend reflects a maturing AI market where technology adoption correlates directly with strategic importance. Enterprises that embed AI deeply into their processes—not just experimental or siloed use—are likely to reshape cost structures and innovation cycles. This embeds AI as a core driver of digital transformation, amplifying organizational intelligence and responsiveness to market changes.\n\n---\n\n3. Evolution of AI Regulation, Governance, and Responsible AI Practices \nDescription: Global regulatory efforts, governance frameworks, and industry collaborations are evolving rapidly to address risks associated with AI deployment, including ethical use, transparency, data privacy, and risk-based oversight tailored to AI’s complexity and impact. \nWhy it Matters: As AI technologies proliferate, regulatory bodies worldwide are crafting nuanced approaches rather than blanket bans. The emergence of risk-category-based AI Acts (e.g., in the EU) and calls for co-governance models that balance innovation and safety highlight the critical need for frameworks ensuring AI’s trustworthy and equitable use. Governance is increasingly central to AI’s sustainable integration in business and society. \nUnique Perspective: The AI regulatory landscape transformation is not merely about compliance costs but an enabler of long-term AI adoption and public trust. Companies leading in responsible AI governance could gain reputational benefits and reduce operational risks, while jurisdictions pioneering balanced AI regulations might attract greater AI investments and innovation. This trend underscores the interplay between technological advancement and societal values shaping AI’s future trajectory.\n\n---\n\nIn summary, 2026 stands out as a landmark year where the convergence of autonomous AI capabilities, widespread enterprise integration, and emerging regulatory clarity collectively reshape the AI industry. This triad drives not only technological sophistication but also profound strategic implications for competitiveness, operational model innovation, and trust-building in AI adoption. These trends are supported by multiple independent reports and market analyses, reflecting their broad impact and scalability potential across sectors.", pydantic=None, json_dict=None, agent='Market Research Analyst', output_format=<OutputFormat.RAW: 'raw'>, messages=[{'role': 'system', 'content': 'You are Market Research Analyst. An expert analyst with a keen eye for market trends.\nYour personal goal is: Provide up-to-date market analysis of the AI industry'}, {'role': 'user', 'content': '\nCurrent Task: Research the latest trends in the AI industry and provide a summary.1. Clarify the research objective internally as: identify the top 3 most current and materially important trends in the AI industry, not just general news. Prioritize developments that are both recent and industry-shaping.\n2. Use the Serper internet search tool to gather broad, high-quality recent sources. Start with a search query focused on current AI industry trends, such as: latest AI industry trends 2026 news, AI industry developments latest, generative AI enterprise adoption latest, AI regulation and model releases latest.\n3. Refine the search with multiple targeted queries to cover distinct sub-areas: model innovation, enterprise adoption, regulation/governance, infrastructure/chips, and AI agents/automation. This ensures the summary is balanced and not overly dependent on one type of development.\n4. Prefer recent news results and reputable sources over opinion pieces. Look for repeated themes across multiple sources, since trends supported by several independent reports are more likely to be truly significant.\n5. For each candidate trend, capture the following: what is happening, why it is trending now, which companies or sectors are involved, and what the broader implication is for the AI industry.\n6. Evaluate the importance of each trend using a practical lens: market adoption, strategic impact, technological novelty, regulatory consequences, and future scalability. Select the top 3 based on combined significance rather than simply recency.\n7. Build a concise synthesis for each selected trend that includes: a one-sentence description, a short explanation of why it matters, and a unique perspective on its significance. The unique perspective should connect the trend to a broader business or societal implication, such as competitive advantage, cost structure changes, trust and compliance, or shifts in product design.\n8. Cross-check the final summary against the original sources to ensure accuracy, avoid overstatement, and keep terminology current. Remove redundant or weakly supported claims.\n9. Structure the final output as a clear summary of the top 3 trending developments in the AI industry, with each trend separated and easy to scan. Ensure the tone reflects market analysis: insightful, current, and grounded in evidence.\n\nThis is the expected criteria for your final answer: A summary of the top 3 trending developments in the AI industry with a unique perspective on their significance.\nyou MUST return the actual complete content as the final answer, not a summary.'}, {'role': 'assistant', 'content': '', 'tool_calls': [{'id': 'call_3cB0A3ll2vC8X0em2q0Xi2Zu', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "latest AI industry trends 2026 news"}'}}, {'id': 'call_yuUOCMrxVEy8qBrlbxpT5Y14', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "model innovation in AI 2026"}'}}, {'id': 'call_eWXm2S7lTq7qZ0cR7yXQUDvh', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "enterprise adoption of AI latest"}'}}, {'id': 'call_AtvrRTRiGqAoDcLbVPlqkvia', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "AI regulation and governance latest"}'}}, {'id': 'call_hbOu8snzCGyk08RUiBHWqdzQ', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "AI infrastructure and chips development 2026"}'}}, {'id': 'call_EVAKLG0ZWYAgHkJ02LNJ8kNn', 'type': 'function', 'function': {'name': 'search_the_internet_with_serper', 'arguments': '{"search_query": "AI agents and automation advancements 2026"}'}}]}, {'role': 'tool', 'content': '{\'searchParameters\': {\'q\': \'latest AI industry trends 2026 news\', \'type\': \'search\', \'num\': 10, \'engine\': \'google\'}, \'organic\': [{\'title\': "What\'s next in AI: 7 trends to watch in 2026", \'link\': \'https://news.microsoft.com/source/features/ai/whats-next-in-ai-7-trends-to-watch-in-2026/\', \'snippet\': \'Seven AI trends to watch in 2026 will make AI a true partner — boosting teamwork, security, research momentum and infrastructure efficiency.\', \'position\': 1}, {\'title\': \'AI Trends 2026\', \'link\': \'https://www.infotech.com/research/ss/ai-trends-2026\', \'snippet\': \'Five AI trends will shape IT in 2026 · 1. 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Next, Claude Code is ...\', \'position\': 2}, {\'title\': \'Top AI Trends Shaping Business and Innovation in 2026\', \'link\': \'https://london.theaisummit.com/ai-trends-in-2026/\', \'snippet\': \'AI trends of 2026, from agentic systems to scaling enterprise AI. Agentic AI systems are making autonomous decisions across your operations. Multimodal models ...\', \'position\': 3}, {\'title\': \'The New AI Business Model Making Millions in 2026\', \'link\': \'https://medium.com/write-a-catalyst/the-new-ai-business-model-making-millions-in-2026-94fa3434429e\', \'snippet\': \'At its core, this new model is about creating AI-powered stores — digital shops or revenue engines that sell automated products, services, or ...\', \'position\': 4}, {\'title\': \'AI Transformation 2026: 26 Predictions Redefining CX, EX ...\', \'link\': \'https://www.linkedin.com/pulse/ai-transformation-2026-26-predictions-redefining-cx-ex-saltz-gulko-twspf\', \'snippet\': \'By 2026, expect a surge of “citizen innovators” – front-line staff, marketers, operations managers – using easy AI tools to solve problems and ...\', \'position\': 5}, {\'title\': \'AI Trends for 2026: From Experimentation to Scalable ...\', \'link\': \'https://www.youtube.com/watch?v=vK0HL9kF8JI\', \'snippet\': \'5 key AI trends shaping 2026: Agentic AI and autonomous agents The future of work: human–AI–robot collaboration Governance, security, and trust ...\', \'position\': 6}, {\'title\': \'AI-based Business Model Innovation 2026\', \'link\': \'https://www.innoman.fi/en/blog/ai-based-business-model-innovation-2026/\', \'snippet\': \'The business model has three main entities: value proposition, value capture and value creation. A value proposition is a promise to the ...\', \'position\': 7}, {\'title\': \'10 AI Trends for 2026 Businesses Must Watch\', \'link\': \'https://thoughtminds.ai/blog/10-ai-trends-for-2026-what-businesses-must-watch-for-this-year\', \'snippet\': \'the newest AI innovations include autonomous agents, multimodal intelligence, edge computing, and even industry-specific models.\', \'position\': 8}, {\'title\': \'Action items for AI decision makers in 2026\', \'link\': \'https://mitsloan.mit.edu/ideas-made-to-matter/action-items-ai-decision-makers-2026\', \'snippet\': "1. Agentic AI isn\'t ready for prime time — yet · 2. The AI bubble will deflate, with economic ramifications · 3. Generative AI should become an ...", \'position\': 9}], \'peopleAlsoAsk\': [{\'question\': \'What are the new AI models coming in 2026?\', \'snippet\': \'New AI model releases planned in April 2026\\n\\nThe next major expected releases are Claude Mythos (Anthropic, timing uncertain), Grok 5 (xAI, Q2 2026), and GPT-5.5 (OpenAI, likely mid-2026). Prediction markets suggest Claude Mythos is the most likely April release.Apr 1, 2026\', \'title\': \'New AI Model Releases News | April, 2026 (STARTUP EDITION)\', \'link\': \'https://blog.mean.ceo/new-ai-model-releases-news-april-2026/#:~:text=New%20AI%20model%20releases%20planned%20in%20April%202026,-The%20most%20current&text=The%20next%20major%20expected%20releases,the%20most%20likely%20April%20release.\'}, {\'question\': \'What is the AI innovation in 2026?\', \'snippet\': \'One of the defining trends of 2026, Agentic AI are systems capable of reasoning, planning, and executing tasks independently. 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A debate rages about whether current laws are too strict; efforts to halt or weaken\\xa0...\', \'position\': 9}], \'relatedSearches\': [{\'query\': \'Artificial Intelligence laws and regulations\'}, {\'query\': \'Ai regulation and governance latest 2022\'}, {\'query\': \'AI regulations around the world\'}, {\'query\': \'Ai regulation debate\'}, {\'query\': \'Regulating under uncertainty governance options for generative ai\'}, {\'query\': \'Ai regulation in the us trump\'}], \'credits\': 1}', 'tool_call_id': 'call_AtvrRTRiGqAoDcLbVPlqkvia', 'name': 'search_the_internet_with_serper'}, {'role': 'tool', 'content': '{\'searchParameters\': {\'q\': \'AI infrastructure and chips development 2026\', \'type\': \'search\', \'num\': 10, \'engine\': \'google\'}, \'organic\': [{\'title\': \'Key Trends Shaping the Semiconductor Industry in 2026\', \'link\': \'https://www.edge-ai-vision.com/2026/04/key-trends-shaping-the-semiconductor-industry-in-2026/\', \'snippet\': "Physical AI will grow faster than data AI in 2026—here\'s the evidence. The next wave of AI chip demand will come from AI embedded in physical ...", \'position\': 1}, {\'title\': \'[Expert POV] The real battleground in the AI semiconductor ...\', \'link\': \'https://news.skhynix.com/2026-expert-column-series-ep3/\', \'snippet\': \'Beginning in 2026, however, AI is expected to expand more deeply into the physical world, diversifying into AI transformation (AX) models3 and ...\', \'position\': 2}, {\'title\': \'The AI Inference Pivot: Why 2026 Could Be The Most ...\', \'link\': \'https://www.youtube.com/watch?v=1xTCgdX7A_8\', \'snippet\': \'Robert Maire of Semiconductor Advisors discusses the key themes and trends that will drive the chip sector in 2026.\', \'position\': 3}, {\'title\': \'AI in Semiconductor Industry: What Will Drive 2026 Growth\', \'link\': \'https://www.crispidea.com/ai-in-semiconductor-industry-2026/\', \'snippet\': \'In 2026, AI chips account for roughly 50% of revenue but less than 0.2% of total unit volume. This is because high-end AI accelerators (like ...\', \'position\': 4}, {\'title\': \'After a Year of Blistering Growth, AI Chip Makers Get ...\', \'link\': \'https://www.wsj.com/tech/ai/after-a-year-of-blistering-growth-ai-chip-makers-get-ready-for-bigger-2026-d9f62dbd\', \'snippet\': \'Semiconductor companies achieved over $400 billion in combined sales in 2025, driven by AI growth, with 2026 projected to be even larger.\', \'position\': 5}, {\'title\': \'AI to Reshape the Global Technology Landscape in 2026 ...\', \'link\': \'https://www.prnewswire.com/news-releases/ai-to-reshape-the-global-technology-landscape-in-2026-says-trendforce-302626789.html\', \'snippet\': "PRNewswire/ -- TrendForce has identified 10 key technology trends that will define the tech industry\'s evolution in 2026.", \'position\': 6}, {\'title\': \'AI Infrastructure in 2026: Challenges, Reality & Enterprise ...\', \'link\': \'https://www.youtube.com/watch?v=qHbgWP8ynSM\', \'snippet\': \'Rob Hirschfeld, CEO … 2026 holds for companies building AI factories, trying to exit VMware, and navigating the hype around agentic AI.\', \'position\': 7}, {\'title\': \'Top 10 AI Infrastructure Stocks to Buy in 2026\', \'link\': \'https://bingx.com/en/learn/article/top-ai-infrastructure-stocks-to-buy-chip-manufacturing-and-design-leaders\', \'snippet\': \'Leading hyperscalers and technology conglomerates are projected to spend nearly $700 billion in 2026 alone on AI data centers, high-speed ...\', \'position\': 8}], \'peopleAlsoAsk\': [{\'question\': \'What are the latest AI developments 2026?\', \'snippet\': \'\', \'title\': \'\', \'link\': \'\'}, {\'question\': \'What makes AI infrastructure production ready in 2026?\', \'snippet\': \'In 2026, production-ready AI infrastructure is not defined by just compute scale alone. It is defined by repeatable deployment, governed lifecycle, measurable quality, resilient operations, and predictable economics.Feb 11, 2026\', \'title\': \'What Makes AI Infrastructure Truly Production-Ready in 2026 - Gruve\', \'link\': \'https://gruve.ai/blog/what-makes-ai-infrastructure-production-ready-in-2026/#:~:text=In%202026%2C%20production%2Dready%20AI,resilient%20operations%2C%20and%20predictable%20economics.\'}, {\'question\': \'Which companies are building AI chips?\', \'snippet\': \'The Top Six AI Chip Manufacturers in the World in 2025\\n___Taiwan Semiconductor Manufacturing Company (TSMC) Headquarters: Hsinchu, Taiwan. ...\\n___Samsung Foundry (Samsung Electronics) ...\\n___GlobalFoundries. ...\\n___Semiconductor Manufacturing International Corporation (SMIC) ...\\n___United Microelectronics Corporation (UMC) ...\\n___Intel Foundry Services (IFS)\', \'title\': \'The List of the Top Six AI Chip Manufacturers in 2025 - CubeFabs\', \'link\': \'https://cubefabs.com/resources/the-top-ai-chip-manufacturers-in-2025\'}, {\'question\': \'What is the 30% rule in AI?\', \'snippet\': \'\', \'title\': \'\', \'link\': \'\'}], \'relatedSearches\': [{\'query\': \'Manus ai sold to meta\'}, {\'query\': \'Facebook buys AI company\'}, {\'query\': \'Manus ai stock price\'}, {\'query\': \'Wsj Meta Manus\'}, {\'query\': "Five things to know about nvidia\'s $20 billion licensing deal"}, {\'query\': \'Nvidia deals\'}, {\'query\': \'Meta manus acquisition price\'}, {\'query\': \'Meta buys AI startup\'}], \'credits\': 1}', 'tool_call_id': 'call_hbOu8snzCGyk08RUiBHWqdzQ', 'name': 'search_the_internet_with_serper'}, {'role': 'tool', 'content': '{\'searchParameters\': {\'q\': \'AI agents and automation advancements 2026\', \'type\': \'search\', \'num\': 10, \'engine\': \'google\'}, \'organic\': [{\'title\': \'AI Trends 2026: Quantum, Agentic AI & Smarter Automation\', \'link\': \'https://www.youtube.com/watch?v=zt0JA5rxdfM\', \'snippet\': \'define AI in 2026? 🚀 Martin Keen & Aaron Baughman explore groundbreaking trends like Agentic AI, cloud computing, automation, and quantum ...\', \'position\': 1}, {\'title\': \'Future of AI Agents: Top Trends in 2026\', \'link\': \'https://www.blueprism.com/resources/blog/future-ai-agents-trends/\', \'snippet\': "In 2026, agentic automation will redraw the enterprise map. The question is no longer capability, it\'s control. The future won\'t belong to those ...", \'position\': 2}, {\'title\': \'AI agent trends 2026 report\', \'link\': \'https://cloud.google.com/resources/content/ai-agent-trends-2026\', \'snippet\': \'Our new report reveals the 5 top trends in agentic AI that can help transform businesses, for 2026 and beyond. agents improve customer service, code quality, ...\', \'position\': 3}, {\'title\': \'AI agents for automation in 2026, sorted by use case. Not a ...\', \'link\': \'https://www.reddit.com/r/AI_Agents/comments/1szfsq4/ai_agents_for_automation_in_2026_sorted_by_use/\', \'snippet\': \'AI agents for automation in 2026, sorted. If your automation needs are tightly centered on commerce workflows order sync, inventory updates, ...\', \'position\': 4}, {\'title\': \'The 2026 Guide to AI Agents\', \'link\': \'https://www.ibm.com/think/ai-agents\', \'snippet\': \'In this comprehensive guide, you will find a collection of AI agent-related content such as educational explainers, hands-on tutorials, podcast episodes and ...\', \'position\': 5}, {\'title\': \'AI Agents Market Size, Share And Trends Report, 2026-2033\', \'link\': \'https://www.grandviewresearch.com/industry-analysis/ai-agents-market-report\', \'snippet\': \'The AI agents market size was valued at $7.6 billion in 2025, projected to grow from $10.9 billion in 2026 to $182.9 billion by 2033, at a CAGR of 49.6%\', \'position\': 6}, {\'title\': \'2026: The Real Year of AI Agents & AI Automation\', \'link\': \'https://smartstudios.io/blog/2026-the-real-year-of-ai-agents-ai-automation/\', \'snippet\': \'In 2026, AI-powered platforms are becoming part of everyday operations across marketing, sales, HR, operations, and more. Some systems help move data between ...\', \'position\': 7}, {\'title\': \'Top 13 Agentic AI Trends to Watch in 2026\', \'link\': \'https://www.firecrawl.dev/blog/agentic-ai-trends\', \'snippet\': \'AI agents are making it dramatically more accessible and capable. The browser automation market is expected to grow 45% year-over-year, driven ...\', \'position\': 8}], \'relatedSearches\': [{\'query\': \'Ai agents and automation advancements 2026 pdf\'}, {\'query\': \'AI agent trends 2026 pdf\'}, {\'query\': \'Google AI agent trends 2026\'}, {\'query\': \'Ai agents trends 2026\'}, {\'query\': \'AI agents 2026\'}, {\'query\': \'2026 State of AI agents report\'}, {\'query\': \'Future of AI in 2026\'}, {\'query\': \'AI 2026 predictions\'}], \'credits\': 1}', 'tool_call_id': 'call_EVAKLG0ZWYAgHkJ02LNJ8kNn', 'name': 'search_the_internet_with_serper'}, {'role': 'assistant', 'content': "Based on a comprehensive review of recent and high-quality sources from industry reports, news, expert analyses, and market forecasts about the AI industry trends in 2026, the top 3 most materially important and current trends shaping the AI landscape are:\n\n---\n\n1. Agentic AI and Autonomous AI Agents Redefining Enterprise Automation \nDescription: Agentic AI systems, capable of autonomous decision-making, multi-step reasoning, and independent task execution, are becoming pivotal in enterprise automation and operational transformation. \nWhy it Matters: Unlike traditional AI models that respond to direct prompts, agentic AI acts proactively with goal-oriented behavior, taking over complex workflows and freeing human workers from routine cognitive tasks. This leap enables a new class of productivity tools and automated services that scale enterprise capabilities significantly. \nUnique Perspective: The rise of agentic AI signals a foundational shift in how businesses view automation—not just as a cost-saving measure but as a strategic lever for competitive advantage. By deploying AI agents that collaborate seamlessly with humans across departments like marketing, sales, HR, and operations, companies can reengineer workflows for agility and innovation, potentially outpacing competitors locked in older automation paradigms.\n\n---\n\n2. Rapid Enterprise Adoption and Market Expansion of AI Across Industries \nDescription: AI adoption in enterprises is accelerating rapidly, with significant growth in AI-powered production models, vector databases, and tailored industry applications boosting operational efficiency and innovation at scale. \nWhy it Matters: Recent data indicate that a substantial portion of Fortune 500 and Global 2000 companies are live, paying customers of leading AI startups, driving the enterprise AI market from tens of billions in 2024 toward projected valuations exceeding $150-200 billion by 2030. Productivity gains and measurable business value reported by workers underscore AI's transitioning role from exploratory technology to essential business infrastructure. \nUnique Perspective: This trend reflects a maturing AI market where technology adoption correlates directly with strategic importance. Enterprises that embed AI deeply into their processes—not just experimental or siloed use—are likely to reshape cost structures and innovation cycles. This embeds AI as a core driver of digital transformation, amplifying organizational intelligence and responsiveness to market changes.\n\n---\n\n3. Evolution of AI Regulation, Governance, and Responsible AI Practices \nDescription: Global regulatory efforts, governance frameworks, and industry collaborations are evolving rapidly to address risks associated with AI deployment, including ethical use, transparency, data privacy, and risk-based oversight tailored to AI’s complexity and impact. \nWhy it Matters: As AI technologies proliferate, regulatory bodies worldwide are crafting nuanced approaches rather than blanket bans. The emergence of risk-category-based AI Acts (e.g., in the EU) and calls for co-governance models that balance innovation and safety highlight the critical need for frameworks ensuring AI’s trustworthy and equitable use. Governance is increasingly central to AI’s sustainable integration in business and society. \nUnique Perspective: The AI regulatory landscape transformation is not merely about compliance costs but an enabler of long-term AI adoption and public trust. Companies leading in responsible AI governance could gain reputational benefits and reduce operational risks, while jurisdictions pioneering balanced AI regulations might attract greater AI investments and innovation. This trend underscores the interplay between technological advancement and societal values shaping AI’s future trajectory.\n\n---\n\nIn summary, 2026 stands out as a landmark year where the convergence of autonomous AI capabilities, widespread enterprise integration, and emerging regulatory clarity collectively reshape the AI industry. This triad drives not only technological sophistication but also profound strategic implications for competitiveness, operational model innovation, and trust-building in AI adoption. These trends are supported by multiple independent reports and market analyses, reflecting their broad impact and scalability potential across sectors."}]), TaskOutput(description='Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the factual backbone of the blog post.\n2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude.\n3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and whether the writing uses examples, analogies, or plain-language explanations.\n4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the new post original. Note phrases, pacing, and formatting conventions that improve readability without copying content.\n5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves the reader with a clear takeaway.\n6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English explanations, and when technical terms are necessary, define them briefly in context so the post remains approachable to a general audience.\n7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs should inform and explain the trends clearly, and the final paragraph should synthesize the implications for businesses, creators, or everyday users.\n8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or dense industry jargon.\n9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments drawn from the analyst summary and inspired by the directory’s best examples.\n10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and maintains a polished blog voice consistent with the examples reviewed from the directory.', name='Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the factual backbone of the blog post.\n2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude.\n3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and whether the writing uses examples, analogies, or plain-language explanations.\n4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the new post original. Note phrases, pacing, and formatting conventions that improve readability without copying content.\n5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves the reader with a clear takeaway.\n6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English explanations, and when technical terms are necessary, define them briefly in context so the post remains approachable to a general audience.\n7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs should inform and explain the trends clearly, and the final paragraph should synthesize the implications for businesses, creators, or everyday users.\n8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or dense industry jargon.\n9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments drawn from the analyst summary and inspired by the directory’s best examples.\n10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and maintains a polished blog voice consistent with the examples reviewed from the directory.', expected_output='A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.', summary='Write an engaging blog post about the AI industry, based...', raw='```markdown\n# The AI Industry in 2026: Autonomous Agents, Enterprise Growth, and Responsible Innovation\n\nArtificial intelligence is no longer just a buzzword or a futuristic idea—it has become a transformative force reshaping how businesses operate and innovate. In 2026, three powerful trends are driving this change: the rise of autonomous AI agents that act independently to automate complex workflows, the rapid adoption of AI across industries as it shifts from experimental to essential infrastructure, and the evolution of thoughtful regulation and governance to ensure AI is used responsibly. Together, these trends paint a future where AI is both a strategic partner for enterprises and a trusted technology for society.\n\nAt the forefront is agentic AI, a new breed of intelligent systems designed to make decisions, learn from experience, and complete multi-step tasks without constant human input. Unlike traditional AI that reacts to direct commands, these autonomous agents proactively manage workflows across departments like marketing, sales, and operations, freeing professionals from routine cognitive work. This shift is more than just saving time or cutting costs—it represents a fundamental rethinking of automation as a source of competitive advantage. Companies deploying these AI agents are poised to innovate and respond to market changes faster, setting new standards for agility and productivity.\n\nSimultaneously, AI adoption is booming in enterprises worldwide, with major companies integrating AI deeply into their operations rather than using it in isolated pilots. This broader deployment includes sophisticated production models, industry-specific AI tools, and advanced data systems such as vector databases that boost decision-making speed and accuracy. This maturity in AI use is reflected in soaring market valuations and measurable productivity improvements reported by workers. AI is fast becoming the backbone of business innovation and digital transformation, helping organizations optimize costs, accelerate product development, and stay ahead of competitors in a rapidly changing landscape.\n\nLastly, as AI’s impact grows, so too does the need for robust regulation and ethical governance. Across the globe, governments and industry groups are crafting frameworks that balance encouraging innovation with minimizing risks like bias, privacy breaches, and misuse. New laws categorize AI applications based on their risk, creating tailored rules that protect users while allowing beneficial technologies to flourish. Responsible AI governance is no longer just a compliance issue—it’s a competitive differentiator that builds public trust and attracts investment. As businesses advance AI adoption aligned with ethical standards, they lay the groundwork for sustainable growth and long-term societal benefits.\n\nOverall, the AI industry in 2026 is entering a dynamic phase where autonomous capabilities, widespread enterprise integration, and careful regulation converge. This combination not only advances technology but also transforms strategic business models and societal values. For companies, creators, and everyday users, embracing these trends means participating in an AI-powered future that is smarter, more efficient, and more trustworthy. The promise of AI lies not just in what it can do today, but in how it can empower us all to innovate and thrive responsibly in the years ahead.\n```', pydantic=None, json_dict=None, agent='Content Writer', output_format=<OutputFormat.RAW: 'raw'>, messages=[{'role': 'system', 'content': 'You are Content Writer. A skilled writer with a passion for technology.\nYour personal goal is: Craft engaging blog posts about the AI industry'}, {'role': 'user', 'content': "\nCurrent Task: Write an engaging blog post about the AI industry, based on the research analysts summary. Draw inspiration from the latest blog posts in the directory.1. First, review the research analyst’s summary carefully and extract the three key AI trends along with the unique perspective for each. Treat this as the factual backbone of the blog post.\n2. Use the DirectoryReadTool to list the available files in ./blog-posts. Identify the most recent or most relevant blog posts, focusing on style, structure, tone, and how they open, transition, and conclude.\n3. Use the FileReadTool to read several of the strongest example posts in full. Look specifically for recurring patterns such as paragraph length, headline style, introduction hooks, accessibility level, and whether the writing uses examples, analogies, or plain-language explanations.\n4. Compare the blog examples to determine the house style the writer should emulate, while still keeping the new post original. Note phrases, pacing, and formatting conventions that improve readability without copying content.\n5. Design a 4-paragraph markdown blog outline before drafting. A strong structure is: paragraph 1 = engaging hook and broad context, paragraph 2 = trend one and its significance, paragraph 3 = trend two and trend three with smooth transitions, paragraph 4 = forward-looking conclusion that ties the trends together and leaves the reader with a clear takeaway.\n6. Translate the analyst summary into accessible language. Replace technical jargon with plain-English explanations, and when technical terms are necessary, define them briefly in context so the post remains approachable to a general audience.\n7. Ensure each paragraph has a distinct purpose: the first should capture attention, the middle paragraphs should inform and explain the trends clearly, and the final paragraph should synthesize the implications for businesses, creators, or everyday users.\n8. Keep the tone engaging, informative, and easy to follow. Use concise sentences, vivid but restrained phrasing, and natural transitions between ideas. Avoid overly academic wording, excessive abbreviations, or dense industry jargon.\n9. Format the final blog post in markdown, making sure the output is exactly 4 paragraphs. Confirm that it reads as a cohesive article rather than a list, while still reflecting the latest AI industry developments drawn from the analyst summary and inspired by the directory’s best examples.\n10. Before finalizing, check that the post is aligned with the research summary, remains accessible, and maintains a polished blog voice consistent with the examples reviewed from the directory.\n\nThis is the expected criteria for your final answer: A 4-paragraph blog post formatted in markdown with engaging, informative, and accessible content, avoiding complex jargon.\nyou MUST return the actual complete content as the final answer, not a summary.\n\nThis is the context you're working with:\nBased on a comprehensive review of recent and high-quality sources from industry reports, news, expert analyses, and market forecasts about the AI industry trends in 2026, the top 3 most materially important and current trends shaping the AI landscape are:\n\n---\n\n1. Agentic AI and Autonomous AI Agents Redefining Enterprise Automation \nDescription: Agentic AI systems, capable of autonomous decision-making, multi-step reasoning, and independent task execution, are becoming pivotal in enterprise automation and operational transformation. \nWhy it Matters: Unlike traditional AI models that respond to direct prompts, agentic AI acts proactively with goal-oriented behavior, taking over complex workflows and freeing human workers from routine cognitive tasks. This leap enables a new class of productivity tools and automated services that scale enterprise capabilities significantly. \nUnique Perspective: The rise of agentic AI signals a foundational shift in how businesses view automation—not just as a cost-saving measure but as a strategic lever for competitive advantage. By deploying AI agents that collaborate seamlessly with humans across departments like marketing, sales, HR, and operations, companies can reengineer workflows for agility and innovation, potentially outpacing competitors locked in older automation paradigms.\n\n---\n\n2. Rapid Enterprise Adoption and Market Expansion of AI Across Industries \nDescription: AI adoption in enterprises is accelerating rapidly, with significant growth in AI-powered production models, vector databases, and tailored industry applications boosting operational efficiency and innovation at scale. \nWhy it Matters: Recent data indicate that a substantial portion of Fortune 500 and Global 2000 companies are live, paying customers of leading AI startups, driving the enterprise AI market from tens of billions in 2024 toward projected valuations exceeding $150-200 billion by 2030. Productivity gains and measurable business value reported by workers underscore AI's transitioning role from exploratory technology to essential business infrastructure. \nUnique Perspective: This trend reflects a maturing AI market where technology adoption correlates directly with strategic importance. Enterprises that embed AI deeply into their processes—not just experimental or siloed use—are likely to reshape cost structures and innovation cycles. This embeds AI as a core driver of digital transformation, amplifying organizational intelligence and responsiveness to market changes.\n\n---\n\n3. Evolution of AI Regulation, Governance, and Responsible AI Practices \nDescription: Global regulatory efforts, governance frameworks, and industry collaborations are evolving rapidly to address risks associated with AI deployment, including ethical use, transparency, data privacy, and risk-based oversight tailored to AI’s complexity and impact. \nWhy it Matters: As AI technologies proliferate, regulatory bodies worldwide are crafting nuanced approaches rather than blanket bans. The emergence of risk-category-based AI Acts (e.g., in the EU) and calls for co-governance models that balance innovation and safety highlight the critical need for frameworks ensuring AI’s trustworthy and equitable use. Governance is increasingly central to AI’s sustainable integration in business and society. \nUnique Perspective: The AI regulatory landscape transformation is not merely about compliance costs but an enabler of long-term AI adoption and public trust. Companies leading in responsible AI governance could gain reputational benefits and reduce operational risks, while jurisdictions pioneering balanced AI regulations might attract greater AI investments and innovation. This trend underscores the interplay between technological advancement and societal values shaping AI’s future trajectory.\n\n---\n\nIn summary, 2026 stands out as a landmark year where the convergence of autonomous AI capabilities, widespread enterprise integration, and emerging regulatory clarity collectively reshape the AI industry. This triad drives not only technological sophistication but also profound strategic implications for competitiveness, operational model innovation, and trust-building in AI adoption. These trends are supported by multiple independent reports and market analyses, reflecting their broad impact and scalability potential across sectors."}, {'role': 'assistant', 'content': '', 'tool_calls': [{'id': 'call_d7FwBx2H1upcBEibkCt16wGj', 'type': 'function', 'function': {'name': 'list_files_in_directory', 'arguments': '{}'}}, {'id': 'call_HhE7xxQ8W29cc2zbsBx3WYBc', 'type': 'function', 'function': {'name': 'read_a_files_content', 'arguments': '{"file_path": "./blog-posts/ai-industry-2025-insights.md", "start_line": 1, "line_count": 20}'}}, {'id': 'call_JesIhqxGwrvFn0eiSIq3KuDb', 'type': 'function', 'function': {'name': 'read_a_files_content', 'arguments': '{"file_path": "./blog-posts/future-of-ai-enterprise.md", "start_line": 1, "line_count": 20}'}}]}, {'role': 'tool', 'content': 'File paths: \n-/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md', 'tool_call_id': 'call_d7FwBx2H1upcBEibkCt16wGj', 'name': 'list_files_in_directory'}, {'role': 'tool', 'content': 'Error: File not found at path: blog-posts/ai-industry-2025-insights.md', 'tool_call_id': 'call_HhE7xxQ8W29cc2zbsBx3WYBc', 'name': 'read_a_files_content'}, {'role': 'tool', 'content': 'Error: File not found at path: blog-posts/future-of-ai-enterprise.md', 'tool_call_id': 'call_JesIhqxGwrvFn0eiSIq3KuDb', 'name': 'read_a_files_content'}, {'role': 'assistant', 'content': '', 'tool_calls': [{'id': 'call_JqvVh6XJqr6udsoqDg0K4tDJ', 'type': 'function', 'function': {'name': 'list_files_in_directory', 'arguments': '{}'}}]}, {'role': 'tool', 'content': 'File paths: \n-/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md', 'tool_call_id': 'call_JqvVh6XJqr6udsoqDg0K4tDJ', 'name': 'list_files_in_directory'}, {'role': 'assistant', 'content': '', 'tool_calls': [{'id': 'call_syLMYk4emnTTcAt6RayLNFlg', 'type': 'function', 'function': {'name': 'read_a_files_content', 'arguments': '{"file_path":"/content/drive/MyDrive/Books_Writings/NLPBook/blog-posts/new_post.md","start_line":1,"line_count":50}'}}]}, {'role': 'tool', 'content': '# AI Industry Trends in 2024: A Transformative Shift in Technology and Business\n\nThe AI landscape in 2024 is undergoing a profound transformation, marked by rapid growth and new paradigms in intelligence and autonomy. At the forefront is agentic AI—autonomous systems capable of independently executing complex tasks across digital and physical realms. This technology is swiftly evolving from a supplementary assistant into a central driver of operational efficiency and innovation. Enterprises across commerce, manufacturing, and governance are adopting these AI agents to streamline workflows and make smarter decisions, signaling a shift in how work gets done. This transition holds huge implications for productivity and competitiveness, as companies that harness trustworthy and capable agentic AI stand to redefine market leadership in the coming decade.\n\nFoundational AI models remain the bedrock of this revolution, serving as versatile platforms powering an array of applications. In 2024, there is a growing emphasis on transparency, open competition, and ethical deployment of these vast models. The rise of powerful open-source alternatives alongside proprietary systems spurs a dynamic ecosystem that fosters innovation while challenging traditional market power structures. This environment encourages more accessible and diverse AI tools, though it also calls for vigilant oversight to manage risks like bias and safety. The evolving interplay between openness and control in foundation models is shaping not only technological progress but also the regulatory and policy framework guiding AI’s future.\n\nSupporting these advancements is the rapidly expanding AI infrastructure ecosystem, encompassing specialized chips, cloud platforms, and data centers optimized for AI workloads. This backbone is critical to scaling AI applications from research prototypes to real-world impact. Infrastructure investments are skyrocketing, reflecting the capital-intensive nature of AI development and deployment. Leading tech players are racing to secure control over hardware supply chains and develop more efficient, powerful computing resources. These trends underscore the strategic importance of AI infrastructure in driving cost-effective innovation, determining where AI capabilities flourish geographically, and influencing global technology leadership amid complex geopolitical dynamics.\n\nTogether, these trends paint a picture of a maturing AI industry that integrates cutting-edge autonomy, foundational model evolution, and robust infrastructure growth. For businesses, creators, and policymakers, understanding and engaging with this intertwined landscape is essential to unlocking AI’s full potential. The rapid commercialization of agentic AI, coupled with a push for transparency and open competition in foundation models, all powered by a deepening infrastructure base, sets the stage for an AI-powered future that is more dynamic, inclusive, and impactful than ever before. The journey ahead promises not just technological breakthroughs but also a reimagining of how innovation shapes society and markets worldwide.', 'tool_call_id': 'call_syLMYk4emnTTcAt6RayLNFlg', 'name': 'read_a_files_content'}, {'role': 'assistant', 'content': '```markdown\n# The AI Industry in 2026: Autonomous Agents, Enterprise Growth, and Responsible Innovation\n\nArtificial intelligence is no longer just a buzzword or a futuristic idea—it has become a transformative force reshaping how businesses operate and innovate. In 2026, three powerful trends are driving this change: the rise of autonomous AI agents that act independently to automate complex workflows, the rapid adoption of AI across industries as it shifts from experimental to essential infrastructure, and the evolution of thoughtful regulation and governance to ensure AI is used responsibly. Together, these trends paint a future where AI is both a strategic partner for enterprises and a trusted technology for society.\n\nAt the forefront is agentic AI, a new breed of intelligent systems designed to make decisions, learn from experience, and complete multi-step tasks without constant human input. Unlike traditional AI that reacts to direct commands, these autonomous agents proactively manage workflows across departments like marketing, sales, and operations, freeing professionals from routine cognitive work. This shift is more than just saving time or cutting costs—it represents a fundamental rethinking of automation as a source of competitive advantage. Companies deploying these AI agents are poised to innovate and respond to market changes faster, setting new standards for agility and productivity.\n\nSimultaneously, AI adoption is booming in enterprises worldwide, with major companies integrating AI deeply into their operations rather than using it in isolated pilots. This broader deployment includes sophisticated production models, industry-specific AI tools, and advanced data systems such as vector databases that boost decision-making speed and accuracy. This maturity in AI use is reflected in soaring market valuations and measurable productivity improvements reported by workers. AI is fast becoming the backbone of business innovation and digital transformation, helping organizations optimize costs, accelerate product development, and stay ahead of competitors in a rapidly changing landscape.\n\nLastly, as AI’s impact grows, so too does the need for robust regulation and ethical governance. Across the globe, governments and industry groups are crafting frameworks that balance encouraging innovation with minimizing risks like bias, privacy breaches, and misuse. New laws categorize AI applications based on their risk, creating tailored rules that protect users while allowing beneficial technologies to flourish. Responsible AI governance is no longer just a compliance issue—it’s a competitive differentiator that builds public trust and attracts investment. As businesses advance AI adoption aligned with ethical standards, they lay the groundwork for sustainable growth and long-term societal benefits.\n\nOverall, the AI industry in 2026 is entering a dynamic phase where autonomous capabilities, widespread enterprise integration, and careful regulation converge. This combination not only advances technology but also transforms strategic business models and societal values. For companies, creators, and everyday users, embracing these trends means participating in an AI-powered future that is smarter, more efficient, and more trustworthy. The promise of AI lies not just in what it can do today, but in how it can empower us all to innovate and thrive responsibly in the years ahead.\n```'}])], token_usage=UsageMetrics(total_tokens=16443, prompt_tokens=14800, cached_prompt_tokens=4736, completion_tokens=1643, reasoning_tokens=0, cache_creation_tokens=0, successful_requests=6))
40.3. Application: Financial Analyst#
Here we create an agent that prepares the forward-looking outlook for Nvidia, using a sample article from Seeking Alpha.
40.4. Collect the Tools needed#
All the tools are listed here: https://docs.crewai.com/tools/browserbaseloadtool
Here we use two tools:
A tool for scraping websites from a given URL:
ScrapeWebsiteTool,A tool to create a searchable vector store:
TXTSearchTool
from crewai_tools import ScrapeWebsiteTool, TXTSearchTool, WebsiteSearchTool
import requests
# Instantiate tools
docs_tool = DirectoryReadTool(directory='./blog-posts')
file_tool = FileReadTool()
search_tool = SerperDevTool()
# web_rag_tool = WebsiteSearchTool()
# Initialize the tool, potentially passing the session
url = 'https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-fourth-quarter-and-fiscal-2025#:~:text=NVIDIA%20will%20pay%20its%20next,record%20on%20March%2012%2C%202025.&text=NVIDIA%27s%20outlook%20for%20the%20first,%2C%20plus%20or%20minus%202%25.'
tool_scrape = ScrapeWebsiteTool(url)
# Extract the text
text = tool_scrape.run()
text
╭────────────────────────── Tracing Preference Saved ──────────────────────────╮
│ │
│ Info: Tracing has been disabled. │
│ │
│ Your preference has been saved. Future Crew/Flow executions will not │
│ collect traces. │
│ │
│ To enable tracing later, do any one of these: │
│ • Set tracing=True in your Crew/Flow code │
│ • Set CREWAI_TRACING_ENABLED=true in your project's .env file │
│ • Run: crewai traces enable │
│ │
╰──────────────────────────────────────────────────────────────────────────────╯
'The following text is scraped website content:\nNVIDIA Announces Financial Results for Fourth Quarter and Fiscal 2025 | NVIDIA Newsroom\nArtificial Intelligence Computing Leadership from NVIDIA\nPLATFORMS\nAutonomous Machines\nCloud & Data Center\nDeep Learning & Ai\nDesign & Pro Visualization\nHealthcare\nHigh Performance Computing\nSelf-Driving Cars\nGaming & Entertainment\nother links\nDevelopers\nIndustries\nShop\nDrivers\nSupport\nAbout NVIDIA\nView All Products\nGPU TECHNOLOGY CONFERENCE\nNVIDIA Blog\nCommunity\nCareers\nTECHNOLOGIES\nNewsroom\nNVIDIA in Brief\nExec Bios\nNVIDIA Blog\nPodcast\nMedia Assets\nIn the News\nPress Contacts\nOnline Press Kits\nNVIDIA in Brief\nExec Bios\nNVIDIA Blog\nPodcast\nMedia Assets\nIn the News\nPress Contacts\nOnline Press Kits\nPress Release\nShare\nTweet\nTwitter\nShare\nLinkedIn\nShare\nFacebook\nEmail\nic_arrow-back-to-top\nNVIDIA Announces Financial Results for Fourth Quarter and Fiscal 2025\nRecord quarterly revenue of $39.3 billion, up 12% from Q3 and up 78% from a year ago\nRecord quarterly Data Center revenue of $35.6 billion, up 16% from Q3 and up 93% from a year ago\nRecord full-year revenue of $130.5 billion, up 114%\nFebruary 26, 2025\nNVIDIA (NASDAQ: NVDA) today reported revenue for the fourth quarter ended January 26, 2025, of $39.3 billion, up 12% from the previous quarter and up 78% from a year ago.\nFor the quarter, GAAP earnings per diluted share was $0.89, up 14% from the previous quarter and up 82% from a year ago. Non-GAAP earnings per diluted share was $0.89, up 10% from the previous quarter and up 71% from a year ago.\nFor fiscal 2025, revenue was $130.5 billion, up 114% from a year ago. GAAP earnings per diluted share was $2.94, up 147% from a year ago. Non-GAAP earnings per diluted share was $2.99, up 130% from a year ago.\n“Demand for Blackwell is amazing as reasoning AI adds another scaling law — increasing compute for training makes models smarter and increasing compute for long thinking makes the answer smarter,” said Jensen Huang, founder and CEO of NVIDIA.\n“We’ve successfully ramped up the massive-scale production of Blackwell AI supercomputers, achieving billions of dollars in sales in its first quarter. AI is advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries.”\nNVIDIA will pay its next quarterly cash dividend of $0.01 per share on April 2, 2025, to all shareholders of record on March 12, 2025.\nQ4 Fiscal 2025 Summary\nGAAP\n($ in millions, except earnings\nper share)\nQ4 FY25\nQ3 FY25\nQ4 FY24\nQ/Q\nY/Y\nRevenue\n$39,331\n$35,082\n$22,103\nUp 12%\nUp 78%\nGross margin\n73.0%\n74.6%\n76.0%\nDown 1.6 pts\nDown 3.0 pts\nOperating expenses\n$4,689\n$4,287\n$3,176\nUp 9%\nUp 48%\nOperating income\n$24,034\n$21,869\n$13,615\nUp 10%\nUp 77%\nNet income\n$22,091\n$19,309\n$12,285\nUp 14%\nUp 80%\nDiluted earnings per share*\n$0.89\n$0.78\n$0.49\nUp 14%\nUp 82%\nNon-GAAP\n($ in millions, except earnings\nper share)\nQ4 FY25\nQ3 FY25\nQ4 FY24\nQ/Q\nY/Y\nRevenue\n$39,331\n$35,082\n$22,103\nUp 12%\nUp 78%\nGross margin\n73.5%\n75.0%\n76.7%\nDown 1.5 pts\nDown 3.2 pts\nOperating expenses\n$3,378\n$3,046\n$2,210\nUp 11%\nUp 53%\nOperating income\n$25,516\n$23,276\n$14,749\nUp 10%\nUp 73%\nNet income\n$22,066\n$20,010\n$12,839\nUp 10%\nUp 72%\nDiluted earnings per share*\n$0.89\n$0.81\n$0.52\nUp 10%\nUp 71%\nFiscal 2025 Summary\nGAAP\n($ in millions, except earnings\nper share)\nFY25\nFY24\nY/Y\nRevenue\n$130,497\n$60,922\nUp 114%\nGross margin\n75.0%\n72.7%\nUp 2.3 pts\nOperating expenses\n$16,405\n$11,329\nUp 45%\nOperating income\n$81,453\n$32,972\nUp 147%\nNet income\n$72,880\n$29,760\nUp 145%\nDiluted earnings per share*\n$2.94\n$1.19\nUp 147%\nNon-GAAP\n($ in millions, except earnings\nper share)\nFY25\nFY24\nY/Y\nRevenue\n$130,497\n$60,922\nUp 114%\nGross margin\n75.5%\n73.8%\nUp 1.7 pts\nOperating expenses\n$11,716\n$7,825\nUp 50%\nOperating income\n$86,789\n$37,134\nUp 134%\nNet income\n$74,265\n$32,312\nUp 130%\nDiluted earnings per share*\n$2.99\n$1.30\nUp 130%\n*All per share amounts presented herein have been retroactively adjusted to reflect the ten-for-one stock split, which was effective June 7, 2024.\nOutlook \r\nNVIDIA’s outlook for the first quarter of fiscal 2026 is as follows:\nRevenue is expected to be $43.0 billion, plus or minus 2%.\nGAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis points.\nGAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, respectively.\nGAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, excluding gains and losses from non-marketable and publicly-held equity securities.\nGAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items.\nHighlights\nNVIDIA achieved progress since its previous earnings announcement in these areas:\nData Center\nFourth-quarter revenue was a record $35.6 billion, up 16% from the previous quarter and up 93% from a year ago. Full-year revenue rose 142% to a record $115.2 billion.\nAnnounced that NVIDIA will serve as a key technology partner for the $500 billion Stargate Project.\nRevealed that cloud service providers AWS, CoreWeave, Google Cloud Platform (GCP), Microsoft Azure and Oracle Cloud Infrastructure (OCI) are bringing NVIDIA® GB200 systems to cloud regions around the world to meet surging customer demand for AI.\nPartnered with AWS to make the NVIDIA DGX™ Cloud AI computing platform and NVIDIA NIM™ microservices available through AWS Marketplace.\nRevealed that Cisco will integrate NVIDIA Spectrum-X™ into its networking portfolio to help enterprises build AI infrastructure.\nRevealed that more than 75% of the systems on the TOP500 list of the world’s most powerful supercomputers are powered by NVIDIA technologies.\nAnnounced a collaboration with Verizon to integrate NVIDIA AI Enterprise, NIM and accelerated computing with Verizon’s private 5G network to power a range of edge enterprise AI applications and services.\nUnveiled partnerships with industry leaders including IQVIA, Illumina, Mayo Clinic and Arc Institute to advance genomics, drug discovery and healthcare.\nLaunched NVIDIA AI Blueprints and Llama Nemotron model families for building AI agents and released NVIDIA NIM microservices to safeguard applications for agentic AI.\nAnnounced the opening of NVIDIA’s first R&D center in Vietnam .\nRevealed that Siemens Healthineers has adopted MONAI Deploy for medical imaging AI.\nGaming and AI PC\nFourth-quarter Gaming revenue was $2.5 billion, down 22% from the previous quarter and down 11% from a year ago.\xa0Full-year revenue rose 9% to $11.4 billion.\nAnnounced new GeForce RTX™ 50 Series graphics cards and laptops powered by the NVIDIA Blackwell architecture, delivering breakthroughs in AI-driven rendering to gamers, creators and developers.\nLaunched GeForce RTX 5090 and 5080 graphics cards, delivering up to a 2x performance improvement over the prior generation.\nIntroduced NVIDIA DLSS 4 with Multi Frame Generation and image quality enhancements, with 75 games and apps supporting it at launch, and unveiled NVIDIA Reflex 2 technology, which can reduce PC latency by up to 75%.\nUnveiled NVIDIA NIM microservices, AI Blueprints and the Llama Nemotron family of open models for RTX AI PCs to help developers and enthusiasts build AI agents and creative workflows.\nProfessional Visualization\nFourth-quarter revenue was $511 million, up 5% from the previous quarter and up 10% from a year ago. Full-year revenue rose 21% to $1.9 billion.\nUnveiled NVIDIA Project DIGITS , a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace™ Blackwell platform.\nAnnounced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications, including robotics, autonomous vehicles and vision AI.\nIntroduced NVIDIA Media2 , an AI-powered initiative transforming content creation, streaming and live media experiences, built on NIM and AI Blueprints.\nAutomotive and Robotics\nFourth-quarter Automotive revenue was $570 million, up 27% from the previous quarter and up 103% from a year ago. Full-year revenue rose 55% to $1.7 billion.\nAnnounced that Toyota, the world’s largest automaker, will build its next-generation vehicles on NVIDIA DRIVE AGX Orin™ running the safety-certified NVIDIA DriveOS operating system.\nPartnered with Hyundai Motor Group to create safer, smarter vehicles, supercharge manufacturing and deploy cutting-edge robotics with NVIDIA AI and NVIDIA Omniverse .\nAnnounced that the NVIDIA DriveOS safe autonomous driving operating system received ASIL-D functional safety certification and launched the NVIDIA DRIVE™ AI Systems Inspection Lab .\nLaunched NVIDIA Cosmos™ , a platform comprising state-of-the-art generative world foundation models, to accelerate physical AI development, with adoption by leading robotics and automotive companies 1X, Agile Robots, Waabi, Uber and others.\nUnveiled the NVIDIA Jetson Orin Nano™ Super , which delivers up to a 1.7x gain in generative AI performance.\nCFO Commentary \r\nCommentary on the quarter by Colette Kress, NVIDIA’s executive vice president and chief financial officer, is available at https://investor.nvidia.com .\nConference Call and Webcast Information \r\nNVIDIA will conduct a conference call with analysts and investors to discuss its fourth quarter and fiscal 2025 financial results and current financial prospects today at 2 p.m. Pacific time (5 p.m. Eastern time). A live webcast (listen-only mode) of the conference call will be accessible at NVIDIA’s investor relations website, https://investor.nvidia.com . The webcast will be recorded and available for replay until NVIDIA’s conference call to discuss its financial results for its first quarter of fiscal 2026.\nNon-GAAP Measures \r\nTo supplement NVIDIA’s condensed consolidated financial statements presented in accordance with GAAP, the company uses non-GAAP measures of certain components of financial performance. These non-GAAP measures include non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses, non-GAAP operating income, non-GAAP other income (expense), net, non-GAAP net income, non-GAAP net income, or earnings, per diluted share, and free cash flow. For NVIDIA’s investors to be better able to compare its current results with those of previous periods, the company has shown a reconciliation of GAAP to non-GAAP financial measures. These reconciliations adjust the related GAAP financial measures to exclude stock-based compensation expense, acquisition-related and other costs, other, gains from non-marketable and publicly-held equity securities, net, interest expense related to amortization of debt discount, and the associated tax impact of these items where applicable. Free cash flow is calculated as GAAP net cash provided by operating activities less both purchases related to property and equipment and intangible assets and principal payments on property and equipment and intangible assets. NVIDIA believes the presentation of its non-GAAP financial measures enhances the user’s overall understanding of the company’s historical financial performance. The presentation of the company’s non-GAAP financial measures is not meant to be considered in isolation or as a substitute for the company’s financial results prepared in accordance with GAAP, and the company’s non-GAAP measures may be different from non-GAAP measures used by other companies.\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED STATEMENTS OF INCOME\n(In millions, except per share data)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2025\n2024\nRevenue\n$\n39,331\n$\n22,103\n$\n130,497\n$\n60,922\nCost of revenue\n10,608\n5,312\n32,639\n16,621\nGross profit\n28,723\n16,791\n97,858\n44,301\nOperating expenses\nResearch and development\n3,714\n2,465\n12,914\n8,675\nSales, general and administrative\n975\n711\n3,491\n2,654\nTotal operating expenses\n4,689\n3,176\n16,405\n11,329\nOperating income\n24,034\n13,615\n81,453\n32,972\nInterest income\n511\n294\n1,786\n866\nInterest expense\n(61\n)\n(63\n)\n(247\n)\n(257\n)\nOther, net\n733\n260\n1,034\n237\nOther income (expense), net\n1,183\n491\n2,573\n846\nIncome before income tax\n25,217\n14,106\n84,026\n33,818\nIncome tax expense\n3,126\n1,821\n11,146\n4,058\nNet income\n$\n22,091\n$\n12,285\n$\n72,880\n$\n29,760\nNet income per share:\nBasic\n$\n0.90\n$\n0.51\n$\n2.97\n$\n1.21\nDiluted\n$\n0.89\n$\n0.49\n$\n2.94\n$\n1.19\nWeighted average shares used in per share computation:\nBasic\n24,489\n24,660\n24,555\n24,690\nDiluted\n24,706\n24,900\n24,804\n24,940\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED BALANCE SHEETS\n(In millions)\n(Unaudited)\nJanuary 26,\nJanuary 28,\n2025\n2024\nASSETS\nCurrent assets:\nCash, cash equivalents and marketable securities\n$\n43,210\n$\n25,984\nAccounts receivable, net\n23,065\n9,999\nInventories\n10,080\n5,282\nPrepaid expenses and other current assets\n3,771\n3,080\nTotal current assets\n80,126\n44,345\nProperty and equipment, net\n6,283\n3,914\nOperating lease assets\n1,793\n1,346\nGoodwill\n5,188\n4,430\nIntangible assets, net\n807\n1,112\nDeferred income tax assets\n10,979\n6,081\nOther assets\n6,425\n4,500\nTotal assets\n$\n111,601\n$\n65,728\nLIABILITIES AND SHAREHOLDERS’ EQUITY\nCurrent liabilities:\nAccounts payable\n$\n6,310\n$\n2,699\nAccrued and other current liabilities\n11,737\n6,682\nShort-term debt\n-\n1,250\nTotal current liabilities\n18,047\n10,631\nLong-term debt\n8,463\n8,459\nLong-term operating lease liabilities\n1,519\n1,119\nOther long-term liabilities\n4,245\n2,541\nTotal liabilities\n32,274\n22,750\nShareholders’ equity\n79,327\n42,978\nTotal liabilities and shareholders’ equity\n$\n111,601\n$\n65,728\nNVIDIA CORPORATION\nCONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS\n(In millions)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2025\n2024\nCash flows from operating activities:\nNet income\n$\n22,091\n$\n12,285\n$\n72,880\n$\n29,760\nAdjustments to reconcile net income to net cash\nprovided by operating activities:\nStock-based compensation expense\n1,321\n993\n4,737\n3,549\nDepreciation and amortization\n543\n387\n1,864\n1,508\nDeferred income taxes\n(598\n)\n(78\n)\n(4,477\n)\n(2,489\n)\nGains on non-marketable equity securities and publicly-held equity securities, net\n(727\n)\n(260\n)\n(1,030\n)\n(238\n)\nOther\n(138\n)\n(109\n)\n(502\n)\n(278\n)\nChanges in operating assets and liabilities, net of acquisitions:\nAccounts receivable\n(5,370\n)\n(1,690\n)\n(13,063\n)\n(6,172\n)\nInventories\n(2,424\n)\n(503\n)\n(4,781\n)\n(98\n)\nPrepaid expenses and other assets\n331\n(1,184\n)\n(395\n)\n(1,522\n)\nAccounts payable\n867\n281\n3,357\n1,531\nAccrued and other current liabilities\n360\n1,072\n4,278\n2,025\nOther long-term liabilities\n372\n305\n1,221\n514\nNet cash provided by operating activities\n16,628\n11,499\n64,089\n28,090\nCash flows from investing activities:\nProceeds from maturities of marketable securities\n1,710\n1,731\n11,195\n9,732\nProceeds from sales of marketable securities\n177\n50\n495\n50\nProceeds from sales of non-marketable equity securities\n-\n-\n171\n1\nPurchases of marketable securities\n(7,010\n)\n(7,524\n)\n(26,575\n)\n(18,211\n)\nPurchase related to property and equipment and intangible assets\n(1,077\n)\n(253\n)\n(3,236\n)\n(1,069\n)\nPurchases of non-marketable equity securities\n(478\n)\n(113\n)\n(1,486\n)\n(862\n)\nAcquisitions, net of cash acquired\n(542\n)\n-\n(1,007\n)\n(83\n)\nOther\n22\n-\n22\n(124\n)\nNet cash used in investing activities\n(7,198\n)\n(6,109\n)\n(20,421\n)\n(10,566\n)\nCash flows from financing activities:\nProceeds related to employee stock plans\n-\n-\n490\n403\nPayments related to repurchases of common stock\n(7,810\n)\n(2,660\n)\n(33,706\n)\n(9,533\n)\nPayments related to tax on restricted stock units\n(1,861\n)\n(841\n)\n(6,930\n)\n(2,783\n)\nRepayment of debt\n-\n-\n(1,250\n)\n(1,250\n)\nDividends paid\n(245\n)\n(99\n)\n(834\n)\n(395\n)\nPrincipal payments on property and equipment and intangible assets\n(32\n)\n(29\n)\n(129\n)\n(74\n)\nOther\n-\n-\n-\n(1\n)\nNet cash used in financing activities\n(9,948\n)\n(3,629\n)\n(42,359\n)\n(13,633\n)\nChange in cash, cash equivalents, and restricted cash\n(518\n)\n1,761\n1,309\n3,891\nCash, cash equivalents, and restricted cash at beginning of period\n9,107\n5,519\n7,280\n3,389\nCash, cash equivalents, and restricted cash at end of period\n$\n8,589\n$\n7,280\n$\n8,589\n$\n7,280\nSupplemental disclosures of cash flow information:\nCash paid for income taxes, net\n$\n4,129\n$\n1,874\n$\n15,118\n$\n6,549\nCash paid for interest\n$\n22\n$\n26\n$\n246\n$\n252\nNVIDIA CORPORATION\nRECONCILIATION OF GAAP TO NON-GAAP FINANCIAL MEASURES\n(In millions, except per share data)\n(Unaudited)\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nGAAP cost of revenue\n$\n10,608\n$\n8,926\n$\n5,312\n$\n32,639\n$\n16,621\nGAAP gross profit\n$\n28,723\n$\n26,156\n$\n16,791\n$\n97,858\n$\n44,301\nGAAP gross margin\n73.0\n%\n74.6\n%\n76.0\n%\n75.0\n%\n72.7\n%\nAcquisition-related and other costs (A)\n118\n116\n119\n472\n477\nStock-based compensation expense (B)\n53\n50\n45\n178\n141\nOther (C)\n-\n-\n4\n(3\n)\n40\nNon-GAAP cost of revenue\n$\n10,437\n$\n8,759\n$\n5,144\n$\n31,992\n$\n15,963\nNon-GAAP gross profit\n$\n28,894\n$\n26,322\n$\n16,959\n$\n98,505\n$\n44,959\nNon-GAAP gross margin\n73.5\n%\n75.0\n%\n76.7\n%\n75.5\n%\n73.8\n%\nGAAP operating expenses\n$\n4,689\n$\n4,287\n$\n3,176\n$\n16,405\n$\n11,329\nStock-based compensation expense (B)\n(1,268\n)\n(1,202\n)\n(948\n)\n(4,559\n)\n(3,408\n)\nAcquisition-related and other costs (A)\n(43\n)\n(39\n)\n(18\n)\n(130\n)\n(106\n)\nOther (C)\n-\n-\n-\n-\n10\nNon-GAAP operating expenses\n$\n3,378\n$\n3,046\n$\n2,210\n$\n11,716\n$\n7,825\nGAAP operating income\n$\n24,034\n$\n21,869\n$\n13,615\n$\n81,453\n$\n32,972\nTotal impact of non-GAAP adjustments to operating income\n1,482\n1,407\n1,134\n5,336\n4,162\nNon-GAAP operating income\n$\n25,516\n$\n23,276\n$\n14,749\n$\n86,789\n$\n37,134\nGAAP other income (expense), net\n$\n1,183\n$\n447\n$\n491\n$\n2,573\n$\n846\nGains from non-marketable equity securities and publicly-held equity securities, net\n(727\n)\n(37\n)\n(260\n)\n(1,030\n)\n(238\n)\nInterest expense related to amortization of debt discount\n1\n1\n1\n4\n4\nNon-GAAP other income (expense), net\n$\n457\n$\n411\n$\n232\n$\n1,547\n$\n612\nGAAP net income\n$\n22,091\n$\n19,309\n$\n12,285\n$\n72,880\n$\n29,760\nTotal pre-tax impact of non-GAAP adjustments\n756\n1,371\n875\n4,310\n3,928\nIncome tax impact of non-GAAP adjustments (D)\n(781\n)\n(670\n)\n(321\n)\n(2,925\n)\n(1,376\n)\nNon-GAAP net income\n$\n22,066\n$\n20,010\n$\n12,839\n$\n74,265\n$\n32,312\nDiluted net income per share (E)\nGAAP\n$\n0.89\n$\n0.78\n$\n0.49\n$\n2.94\n$\n1.19\nNon-GAAP\n$\n0.89\n$\n0.81\n$\n0.52\n$\n2.99\n$\n1.30\nWeighted average shares used in diluted net income per share computation (E)\n24,706\n24,774\n24,900\n24,804\n24,936\nGAAP net cash provided by operating activities\n$\n16,628\n$\n17,629\n$\n11,499\n$\n64,089\n$\n28,090\nPurchases related to property and equipment and intangible assets\n(1,077\n)\n(813\n)\n(253\n)\n(3,236\n)\n(1,069\n)\nPrincipal payments on property and equipment and intangible assets\n(32\n)\n(29\n)\n(29\n)\n(129\n)\n(74\n)\nFree cash flow\n$\n15,519\n$\n16,787\n$\n11,217\n$\n60,724\n$\n26,947\n(A) Acquisition-related and other costs are comprised of amortization of intangible assets, transaction costs, and certain compensation charges and are included in the following line items:\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nCost of revenue\n$\n118\n$\n116\n$\n119\n$\n472\n$\n477\nResearch and development\n$\n27\n$\n23\n$\n12\n$\n79\n$\n49\nSales, general and administrative\n$\n16\n$\n16\n$\n6\n$\n51\n$\n57\n(B) Stock-based compensation consists of the following:\nThree Months Ended\nTwelve Months Ended\nJanuary 26,\nOctober 27,\nJanuary 28,\nJanuary 26,\nJanuary 28,\n2025\n2024\n2024\n2025\n2024\nCost of revenue\n$\n53\n$\n50\n$\n45\n$\n178\n$\n141\nResearch and development\n$\n955\n$\n910\n$\n706\n$\n3,423\n$\n2,532\nSales, general and administrative\n$\n313\n$\n292\n$\n242\n$\n1,136\n$\n876\n(C) Other consists of IP-related costs and assets held for sale related adjustments\n(D) Income tax impact of non-GAAP adjustments, including the recognition of excess tax benefits or deficiencies related to stock-based compensation under GAAP accounting standard (ASU 2016-09).\n(E) Reflects a ten-for-one stock split on June 7, 2024\nNVIDIA CORPORATION\nRECONCILIATION OF GAAP TO NON-GAAP OUTLOOK\nQ1 FY2026 Outlook\n($ in millions)\nGAAP gross margin\n70.6\n%\nImpact of stock-based compensation expense, acquisition-related costs, and other costs\n0.4\n%\nNon-GAAP gross margin\n71.0\n%\nGAAP operating expenses\n$\n5,150\nStock-based compensation expense, acquisition-related costs, and other costs\n(1,550\n)\nNon-GAAP operating expenses\n$\n3,600\nAbout NVIDIA\nNVIDIA \xa0(NASDAQ: NVDA) is the world leader in accelerated computing.\nCertain statements in this press release including, but not limited to, statements as to: AI advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments and related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n© 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, GeForce RTX, NVIDIA Cosmos, NVIDIA Spectrum-X, NVIDIA DGX, NVIDIA DRIVE, NVIDIA DRIVE AGX Orin, NVIDIA Grace, NVIDIA Jetson Orin Nano, NVIDIA NIM and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\nMedia Contacts\nStewart Stecker\nInvestor Relations\nsstecker@nvidia.com\nMylene Mangalindan\nCorporate Communications\nNVIDIA Corporation\npress@nvidia.com\nDownloads\nDownload Press Release\nDownload Attachments\nMore Images\naabe86db-ce89-4434-b83c-495082979801\nDownload / File Link\nMore News\nJapan Government, Industrial Leaders and NVIDIA Launch the World’s First National AI Infrastructure\nJuly 16, 2026\nJapan’s Robotics and Manufacturing Leaders Build on NVIDIA Cosmos to Advance Physical AI Frontier\nJuly 15, 2026\nJapan’s Enterprises and Startups Build Industry-Specialized AI With NVIDIA Nemotron Open Models\nJuly 15, 2026\nNVIDIA Announces BioNeMo Agent Toolkit — Tools for Agents to Accelerate Scientific Discovery\nJune 23, 2026\nNVIDIA Announces Halos for Robotics, the Industry’s First Full-Stack Safety System for Physical AI\nJune 22, 2026\nAbout NVIDIA\nNVIDIA \xa0(NASDAQ: NVDA) is the world leader in accelerated computing.\nCertain statements in this press release including, but not limited to, statements as to: AI advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, including with its collaborators and partners; expectations with respect to technology developments and related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; expectations with respect to AI and related industries; and other statements that are not historical facts are risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic and political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n© 2025 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, GeForce RTX, NVIDIA Cosmos, NVIDIA Spectrum-X, NVIDIA DGX, NVIDIA DRIVE, NVIDIA DRIVE AGX Orin, NVIDIA Grace, NVIDIA Jetson Orin Nano, NVIDIA NIM and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\nMedia Contacts\nGlobal contacts for media inquiries.\nAll Contacts\nStay Informed\nNewsroom updates delivered to your inbox.\nSubscribe\nCorporate Information\nAbout NVIDIA\nCorporate Overview\nTechnologies\nNVIDIA Research\nInvestors\nSocial Responsibility\nNVIDIA Foundation\nGet Involved\nForums\nCareers\nDeveloper Home\nJoin the Developer Program\nNVIDIA Partner Network\nNVIDIA Inception\nResources for Venture Capitalists\nVenture Capital (NVentures)\nTechnical Training\nTraining for IT Professionals\nProfessional Services for Data Science\nNews & Events\nNewsroom\nNVIDIA Blog\nNVIDIA Technical Blog\nWebinars\nStay Informed\nEvents Calendar\nNVIDIA GTC\nNVIDIA On-Demand\nSign Up for NVIDIA News\nSubscribe\nFollow NVIDIA\nFacebook\nLinkedIn\nInstagram\nYouTube\nNVIDIA\nUSA - United States\nPrivacy Policy\nYour Privacy Choices\nManage Cookie Settings\nTerms of Service\nAccessibility\nCorporate Policies\nProduct Security\nContact\nCopyright © 2026 NVIDIA Corporation\n'
# Write content to a file
if not os.path.exists('crewai'):
os.mkdir('crewai')
with open('crewai/nvidia.txt', 'w') as f:
f.write(text)
f.close()
The TXTSearchTool creates a vector index and enables search.
# os.environ['OPENAI_API_KEY'] = 'API-KEY'
# Initialize the tool with a specific text file, so the agent can search within the given text file's content
tool_search = TXTSearchTool(txt='crewai/nvidia.txt')
40.5. Application: Build a Financial Analyst Agent#
As shown below, you need to specify
The
AgentsandTasks.The
Crewis then the collections of Agents, Tasks, and Tools (tools were defined earlier)
By default, CrewAI uses the gpt-4o model unless specified to use another model. CrewAI uses LiteLLM, which is installed already with it, https://www.litellm.ai. LiteLLM is an interface that may be used to address a large number of LLM providers and their models.
from crewai import Agent, Task, Crew
question = 'What is the forward-looking outlook for Nvidia?'
context = tool_search.run(question)
fin_analyst = Agent(
role='Financial Analyst',
goal=f'Based on the context provided, answer the Question - {question} Context - {context}',
backstory='You are a financial analyst and an expert on forecasting the future trajectory of a firm',
verbose=True,
allow_delegation=False,
tools=[tool_search, search_tool]
)
task_answer = Task(
description="Analyze the question, understand the context, and generate the correct response",
tools=[tool_search],
agent=fin_analyst,
expected_output='Provide a relevant answer to the question'
)
crew = Crew(
agents=[fin_analyst],
tasks=[task_answer],
verbose=True,
planning=True, # Enable planning feature
)
40.6. Run the Crew for the financial analyst#
Execute the entire agentic workflow. What we have is a single agent and one task with a single tool. So it is pretty straightforward.
# If debugging is needed, uncomment the lines below.
# import litellm
# litellm._turn_on_debug()
import asyncio
output = await crew.kickoff_async()
╭─────────────────────────────────────────── 🚀 Crew Execution Started ───────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: dd02df7b-1f68-4a3e-8cb3-0020f85c3a4a │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[2026-07-16 18:29:39][INFO]: Planning the crew execution
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Based on these tasks summary: │ │ Task Number 1 - Analyze the question, understand the context, and generate the correct │ │ response │ │ "task_description": Analyze the question, understand the context, and generate the correct │ │ response │ │ "task_expected_output": Provide a relevant answer to the question │ │ "agent": Financial Analyst │ │ "agent_goal": Based on the context provided, answer the Question - What is the │ │ forward-looking outlook for Nvidia? Context - Relevant Content: │ │ │ │ (1,550 │ │ │ │ ) │ │ │ │ Non-GAAP operating expenses │ │ │ │ $ │ │ │ │ 3,600 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations │ │ │ │ │ │ 73.8% │ │ │ │ Up 1.7 pts │ │ │ │ Operating expenses │ │ │ │ $11,716 │ │ │ │ $7,825 │ │ │ │ Up 50% │ │ │ │ Operating income │ │ │ │ $86,789 │ │ │ │ $37,134 │ │ │ │ Up 134% │ │ │ │ Net income │ │ │ │ $74,265 │ │ │ │ $32,312 │ │ │ │ Up 130% │ │ │ │ Diluted earnings per share* │ │ │ │ $2.99 │ │ │ │ $1.30 │ │ │ │ Up 130% │ │ │ │ *All per share amounts presented herein have been retroactively adjusted to reflect the ten-for-one stock │ │ split, which was effective June 7, 2024. │ │ │ │ Outlook │ │ │ │ NVIDIA’s outlook for the first quarter of fiscal 2026 is as follows: │ │ │ │ Revenue is expected to be $43.0 billion, plus or minus 2%. │ │ │ │ GAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis │ │ points. │ │ │ │ GAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, │ │ respectively. │ │ │ │ GAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, │ │ excluding gains and losses from non-marketable and publicly-held equity securities. │ │ │ │ GAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ Highlights │ │ │ │ NVIDIA achieved progress since its previous earnings announcement in these areas: │ │ │ │ Data Center │ │ │ │ Fourth-quarter revenue was a record $35.6 billion, up 16% from the previous quarter and up 93% from a year │ │ ago. Full-year revenue rose 142% to a record $115.2 billion. │ │ │ │ Announced that NVIDIA will serve as a key technology partner for the $500 billion Stargate Project. │ │ │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations. . │ │ Important factors that could cause actual results to differ materially include: global economic and political │ │ conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; │ │ the impact of technological development and competition; development of new products and technologies or │ │ enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or │ │ NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or │ │ demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or │ │ technologies when integrated into systems; and changes in applicable laws and regulations, as well as other │ │ factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange │ │ Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on │ │ Form 10-Q │ │ . Important factors that could cause actual results to differ materially include: global economic and │ │ political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s │ │ products; the impact of technological development and competition; development of new products and │ │ technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s │ │ products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer │ │ preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of │ │ NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and │ │ regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with │ │ the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K │ │ and quarterly reports on Form 10-Q. . Copies of reports filed with the SEC are posted on the company’s │ │ website and are available from NVIDIA without charge. . These forward-looking statements are not guarantees │ │ of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims │ │ any obligation to update these forward-looking statements to reflect future events or circumstances. │ │ │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations. . │ │ Important factors that could cause actual results to differ materially include: global economic and political │ │ conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; │ │ the impact of technological development and competition; development of new products and technologies or │ │ enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or │ │ NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or │ │ demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or │ │ technologies when integrated into systems; and changes in applicable laws and regulations, as well as other │ │ factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange │ │ Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on │ │ Form 10-Q │ │ . Important factors that could cause actual results to differ materially include: global economic and │ │ political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s │ │ products; the impact of technological development and competition; development of new products and │ │ technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s │ │ products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer │ │ preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of │ │ NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and │ │ regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with │ │ the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K │ │ and quarterly reports on Form 10-Q. . Copies of reports filed with the SEC are posted on the company’s │ │ website and are available from NVIDIA without charge. . These forward-looking statements are not guarantees │ │ of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims │ │ any obligation to update these forward-looking statements to reflect future events or circumstances. │ │ │ │ │ │ June 22, 2026 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations │ │ "task_tools": [TXTSearchTool(name="Search a txt's content", description='Tool Name: │ │ search_a_txts_content\nTool Arguments: {\n "description": "Input for TXTSearchTool.",\n "properties": {\n │ │ "search_query": {\n "description": "Mandatory search query you want to use to search the txt\'s │ │ content",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "FixedTXTSearchToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to semantic search a query the crewai/nvidia.txt txt\'s │ │ content.', env_vars=[], args_schema=<class │ │ 'crewai_tools.tools.txt_search_tool.txt_search_tool.FixedTXTSearchToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, summarize=False, │ │ similarity_threshold=0.6, limit=5, collection_name='rag_tool_collection', │ │ adapter=CrewAIRagAdapter(collection_name='rag_tool_collection', summarize=False, similarity_threshold=0.6, │ │ limit=5, config=ChromaDBConfig(provider='chromadb', │ │ embedding_function=<chromadb.utils.embedding_functions.openai_embedding_function.OpenAIEmbeddingFunction │ │ object at 0x7cd2601d0410>, limit=5, score_threshold=0.6, batch_size=100, tenant='default_tenant', │ │ database='default_database', settings=Settings(environment='', │ │ chroma_api_impl='chromadb.api.rust.RustBindingsAPI', chroma_server_nofile=None, │ │ chroma_server_thread_pool_size=40, tenant_id='default', topic_namespace='default', chroma_server_host=None, │ │ chroma_server_headers=None, chroma_server_http_port=None, chroma_server_ssl_enabled=False, │ │ chroma_server_ssl_verify=None, chroma_server_api_default_path=<APIVersion.V2: '/api/v2'>, │ │ chroma_server_cors_allow_origins=[], is_persistent=True, persist_directory='/root/.local/share/NLPBook', │ │ chroma_memory_limit_bytes=0, chroma_segment_cache_policy=None, allow_reset=True, │ │ chroma_auth_token_transport_header=None, chroma_client_auth_provider=None, │ │ chroma_client_auth_credentials=None, chroma_server_auth_ignore_paths={'APIVersion.V2': ['GET'], │ │ 'APIVersion.V2/heartbeat': ['GET'], 'APIVersion.V2/version': ['GET'], 'APIVersion.V1': ['GET'], │ │ 'APIVersion.V1/heartbeat': ['GET'], 'APIVersion.V1/version': ['GET']}, │ │ chroma_overwrite_singleton_tenant_database_access_from_auth=False, chroma_server_authn_provider=None, │ │ chroma_server_authn_credentials=None, chroma_server_authn_credentials_file=None, │ │ chroma_server_authz_provider=None, chroma_server_authz_config=None, chroma_server_authz_config_file=None, │ │ chroma_product_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', │ │ chroma_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', anonymized_telemetry=False, │ │ chroma_otel_collection_endpoint='', chroma_otel_service_name='chromadb', chroma_otel_collection_headers={}, │ │ chroma_otel_granularity=None, migrations='apply', migrations_hash_algorithm='md5', │ │ chroma_segment_directory_impl='chromadb.segment.impl.distributed.segment_directory.RendezvousHashSegmentDirec │ │ tory', chroma_segment_directory_routing_mode=<RoutingMode.ID: 'id'>, │ │ chroma_memberlist_provider_impl='chromadb.segment.impl.distributed.segment_directory.CustomResourceMemberlist │ │ Provider', worker_memberlist_name='query-service-memberlist', chroma_server_grpc_port=None, │ │ chroma_sysdb_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_producer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_consumer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_segment_manager_impl='chromadb.segment.impl.manager.local.LocalSegmentManager', │ │ chroma_executor_impl='chromadb.execution.executor.local.LocalExecutor', chroma_query_replication_factor=2, │ │ chroma_quota_provider_impl=None, chroma_rate_limiting_provider_impl=None, │ │ chroma_quota_enforcer_impl='chromadb.quota.simple_quota_enforcer.SimpleQuotaEnforcer', │ │ chroma_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleRateLimitEnforcer', │ │ chroma_async_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleAsyncRateLimitEnforcer', │ │ chroma_logservice_request_timeout_seconds=3, chroma_sysdb_request_timeout_seconds=3, │ │ chroma_query_request_timeout_seconds=60, chroma_db_impl=None, │ │ chroma_collection_assignment_policy_impl='chromadb.ingest.impl.simple_policy.SimpleAssignmentPolicy', │ │ chroma_coordinator_host='localhost', chroma_logservice_host='localhost', chroma_logservice_port=50052))), │ │ config={}, txt='crewai/nvidia.txt', │ │ tool_type='crewai_tools.tools.txt_search_tool.txt_search_tool.TXTSearchTool')] │ │ "agent_tools": [name="Search a txt's content" description='Tool Name: │ │ search_a_txts_content\nTool Arguments: {\n "description": "Input for TXTSearchTool.",\n "properties": {\n │ │ "search_query": {\n "description": "Mandatory search query you want to use to search the txt\'s │ │ content",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "FixedTXTSearchToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to semantic search a query the crewai/nvidia.txt txt\'s │ │ content.' env_vars=[] args_schema=<class │ │ 'crewai_tools.tools.txt_search_tool.txt_search_tool.FixedTXTSearchToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 summarize=False similarity_threshold=0.6 │ │ limit=5 collection_name='rag_tool_collection' adapter=CrewAIRagAdapter(collection_name='rag_tool_collection', │ │ summarize=False, similarity_threshold=0.6, limit=5, config=ChromaDBConfig(provider='chromadb', │ │ embedding_function=<chromadb.utils.embedding_functions.openai_embedding_function.OpenAIEmbeddingFunction │ │ object at 0x7cd2601d0410>, limit=5, score_threshold=0.6, batch_size=100, tenant='default_tenant', │ │ database='default_database', settings=Settings(environment='', │ │ chroma_api_impl='chromadb.api.rust.RustBindingsAPI', chroma_server_nofile=None, │ │ chroma_server_thread_pool_size=40, tenant_id='default', topic_namespace='default', chroma_server_host=None, │ │ chroma_server_headers=None, chroma_server_http_port=None, chroma_server_ssl_enabled=False, │ │ chroma_server_ssl_verify=None, chroma_server_api_default_path=<APIVersion.V2: '/api/v2'>, │ │ chroma_server_cors_allow_origins=[], is_persistent=True, persist_directory='/root/.local/share/NLPBook', │ │ chroma_memory_limit_bytes=0, chroma_segment_cache_policy=None, allow_reset=True, │ │ chroma_auth_token_transport_header=None, chroma_client_auth_provider=None, │ │ chroma_client_auth_credentials=None, chroma_server_auth_ignore_paths={'APIVersion.V2': ['GET'], │ │ 'APIVersion.V2/heartbeat': ['GET'], 'APIVersion.V2/version': ['GET'], 'APIVersion.V1': ['GET'], │ │ 'APIVersion.V1/heartbeat': ['GET'], 'APIVersion.V1/version': ['GET']}, │ │ chroma_overwrite_singleton_tenant_database_access_from_auth=False, chroma_server_authn_provider=None, │ │ chroma_server_authn_credentials=None, chroma_server_authn_credentials_file=None, │ │ chroma_server_authz_provider=None, chroma_server_authz_config=None, chroma_server_authz_config_file=None, │ │ chroma_product_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', │ │ chroma_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', anonymized_telemetry=False, │ │ chroma_otel_collection_endpoint='', chroma_otel_service_name='chromadb', chroma_otel_collection_headers={}, │ │ chroma_otel_granularity=None, migrations='apply', migrations_hash_algorithm='md5', │ │ chroma_segment_directory_impl='chromadb.segment.impl.distributed.segment_directory.RendezvousHashSegmentDirec │ │ tory', chroma_segment_directory_routing_mode=<RoutingMode.ID: 'id'>, │ │ chroma_memberlist_provider_impl='chromadb.segment.impl.distributed.segment_directory.CustomResourceMemberlist │ │ Provider', worker_memberlist_name='query-service-memberlist', chroma_server_grpc_port=None, │ │ chroma_sysdb_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_producer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_consumer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_segment_manager_impl='chromadb.segment.impl.manager.local.LocalSegmentManager', │ │ chroma_executor_impl='chromadb.execution.executor.local.LocalExecutor', chroma_query_replication_factor=2, │ │ chroma_quota_provider_impl=None, chroma_rate_limiting_provider_impl=None, │ │ chroma_quota_enforcer_impl='chromadb.quota.simple_quota_enforcer.SimpleQuotaEnforcer', │ │ chroma_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleRateLimitEnforcer', │ │ chroma_async_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleAsyncRateLimitEnforcer', │ │ chroma_logservice_request_timeout_seconds=3, chroma_sysdb_request_timeout_seconds=3, │ │ chroma_query_request_timeout_seconds=60, chroma_db_impl=None, │ │ chroma_collection_assignment_policy_impl='chromadb.ingest.impl.simple_policy.SimpleAssignmentPolicy', │ │ chroma_coordinator_host='localhost', chroma_logservice_host='localhost', chroma_logservice_port=50052))) │ │ config={} txt='crewai/nvidia.txt' │ │ tool_type='crewai_tools.tools.txt_search_tool.txt_search_tool.TXTSearchTool', name='Search the internet with │ │ Serper' description='Tool Name: search_the_internet_with_serper\nTool Arguments: {\n "description": "Input │ │ for SerperDevTool.",\n "properties": {\n "search_query": {\n "description": "Mandatory search query │ │ you want to use to search the internet",\n "title": "Search Query",\n "type": "string"\n }\n │ │ },\n "required": [\n "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n │ │ "additionalProperties": false\n}\nTool Description: A tool that can be used to search the internet with a │ │ search_query. Supports different search types: \'search\' (default), \'news\'' │ │ env_vars=[EnvVar(name='SERPER_API_KEY', description='API key for Serper', required=True, default=None)] │ │ args_schema=<class 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'> │ │ result_schema=None description_updated=False cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0> result_as_answer=False max_usage_count=None current_usage_count=0 │ │ base_url='https://google.serper.dev' n_results=10 save_file=False search_type='search' country='' location='' │ │ locale='' tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool'] │ │ Create the most descriptive plan based on the tasks descriptions, tools available, and agents' goals for │ │ them to execute their goals with perfection. │ │ ID: fbb8ebf1-7644-44af-8bde-1620bb017450 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Analyze the question, understand the context, and generate the correct response1. Carefully read the │ │ user’s question and isolate the exact ask: determine the forward-looking outlook for Nvidia. │ │ 2. Review the provided context with special attention to the sections labeled Outlook, Highlights, and the │ │ forward-looking statements/disclaimer language. │ │ 3. Use the txt search tool to locate the most relevant passages in crewai/nvidia.txt by searching for │ │ high-signal terms such as "Outlook", "fiscal 2026", "Blackwell", "Data Center", "revenue is expected", and │ │ "forward-looking statements". │ │ 4. If necessary, use the internet search tool only to validate whether there is any additional public context │ │ around Nvidia’s outlook, but prioritize the provided document since the task is to answer based on the │ │ supplied content. │ │ 5. Extract the core forward-looking guidance exactly as stated in the source, including revenue expectations, │ │ margin expectations, operating expense expectations, other income/expense expectations, and tax rate │ │ expectations. │ │ 6. Identify broader qualitative outlook cues from the Highlights section, including record Data Center │ │ revenue growth, the role in the Stargate Project, and references to Blackwell, AI growth, agentic AI, and │ │ physical AI. │ │ 7. Note that the press release explicitly frames these as forward-looking statements and includes risk │ │ factors; keep this context intact and do not overstate certainty. │ │ 8. Construct the answer so it directly addresses the question with a concise but complete outlook summary, │ │ using the source’s numbers and language where appropriate. │ │ 9. Ensure the response distinguishes between near-term quantified guidance and longer-term thematic optimism, │ │ while acknowledging the risks and uncertainties stated by Nvidia. │ │ 10. Deliver a clear final response that answers what Nvidia’s outlook is, grounded strictly in the provided │ │ text and phrased as a relevant answer to the question. │ │ ID: 909d0170-a2ac-4253-89bd-4037b10ac585 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Based on these tasks summary: │ │ Task Number 1 - Analyze the question, understand the context, and generate the correct │ │ response │ │ "task_description": Analyze the question, understand the context, and generate the correct │ │ response │ │ "task_expected_output": Provide a relevant answer to the question │ │ "agent": Financial Analyst │ │ "agent_goal": Based on the context provided, answer the Question - What is the │ │ forward-looking outlook for Nvidia? Context - Relevant Content: │ │ │ │ (1,550 │ │ │ │ ) │ │ │ │ Non-GAAP operating expenses │ │ │ │ $ │ │ │ │ 3,600 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations │ │ │ │ │ │ 73.8% │ │ │ │ Up 1.7 pts │ │ │ │ Operating expenses │ │ │ │ $11,716 │ │ │ │ $7,825 │ │ │ │ Up 50% │ │ │ │ Operating income │ │ │ │ $86,789 │ │ │ │ $37,134 │ │ │ │ Up 134% │ │ │ │ Net income │ │ │ │ $74,265 │ │ │ │ $32,312 │ │ │ │ Up 130% │ │ │ │ Diluted earnings per share* │ │ │ │ $2.99 │ │ │ │ $1.30 │ │ │ │ Up 130% │ │ │ │ *All per share amounts presented herein have been retroactively adjusted to reflect the ten-for-one stock │ │ split, which was effective June 7, 2024. │ │ │ │ Outlook │ │ │ │ NVIDIA’s outlook for the first quarter of fiscal 2026 is as follows: │ │ │ │ Revenue is expected to be $43.0 billion, plus or minus 2%. │ │ │ │ GAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis │ │ points. │ │ │ │ GAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, │ │ respectively. │ │ │ │ GAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, │ │ excluding gains and losses from non-marketable and publicly-held equity securities. │ │ │ │ GAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ Highlights │ │ │ │ NVIDIA achieved progress since its previous earnings announcement in these areas: │ │ │ │ Data Center │ │ │ │ Fourth-quarter revenue was a record $35.6 billion, up 16% from the previous quarter and up 93% from a year │ │ ago. Full-year revenue rose 142% to a record $115.2 billion. │ │ │ │ Announced that NVIDIA will serve as a key technology partner for the $500 billion Stargate Project. │ │ │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations. . │ │ Important factors that could cause actual results to differ materially include: global economic and political │ │ conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; │ │ the impact of technological development and competition; development of new products and technologies or │ │ enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or │ │ NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or │ │ demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or │ │ technologies when integrated into systems; and changes in applicable laws and regulations, as well as other │ │ factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange │ │ Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on │ │ Form 10-Q │ │ . Important factors that could cause actual results to differ materially include: global economic and │ │ political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s │ │ products; the impact of technological development and competition; development of new products and │ │ technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s │ │ products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer │ │ preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of │ │ NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and │ │ regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with │ │ the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K │ │ and quarterly reports on Form 10-Q. . Copies of reports filed with the SEC are posted on the company’s │ │ website and are available from NVIDIA without charge. . These forward-looking statements are not guarantees │ │ of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims │ │ any obligation to update these forward-looking statements to reflect future events or circumstances. │ │ │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations. . │ │ Important factors that could cause actual results to differ materially include: global economic and political │ │ conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s products; │ │ the impact of technological development and competition; development of new products and technologies or │ │ enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s products or │ │ NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer preferences or │ │ demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA’s products or │ │ technologies when integrated into systems; and changes in applicable laws and regulations, as well as other │ │ factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange │ │ Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on │ │ Form 10-Q │ │ . Important factors that could cause actual results to differ materially include: global economic and │ │ political conditions; NVIDIA’s reliance on third parties to manufacture, assemble, package and test NVIDIA’s │ │ products; the impact of technological development and competition; development of new products and │ │ technologies or enhancements to NVIDIA’s existing product and technologies; market acceptance of NVIDIA’s │ │ products or NVIDIA’s partners’ products; design, manufacturing or software defects; changes in consumer │ │ preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of │ │ NVIDIA’s products or technologies when integrated into systems; and changes in applicable laws and │ │ regulations, as well as other factors detailed from time to time in the most recent reports NVIDIA files with │ │ the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K │ │ and quarterly reports on Form 10-Q. . Copies of reports filed with the SEC are posted on the company’s │ │ website and are available from NVIDIA without charge. . These forward-looking statements are not guarantees │ │ of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims │ │ any obligation to update these forward-looking statements to reflect future events or circumstances. │ │ │ │ │ │ June 22, 2026 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations │ │ "task_tools": [TXTSearchTool(name="Search a txt's content", description='Tool Name: │ │ search_a_txts_content\nTool Arguments: {\n "description": "Input for TXTSearchTool.",\n "properties": {\n │ │ "search_query": {\n "description": "Mandatory search query you want to use to search the txt\'s │ │ content",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "FixedTXTSearchToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to semantic search a query the crewai/nvidia.txt txt\'s │ │ content.', env_vars=[], args_schema=<class │ │ 'crewai_tools.tools.txt_search_tool.txt_search_tool.FixedTXTSearchToolSchema'>, result_schema=None, │ │ description_updated=False, cache_function=<function _default_cache_function at 0x7cd271046fc0>, │ │ result_as_answer=False, max_usage_count=None, current_usage_count=0, summarize=False, │ │ similarity_threshold=0.6, limit=5, collection_name='rag_tool_collection', │ │ adapter=CrewAIRagAdapter(collection_name='rag_tool_collection', summarize=False, similarity_threshold=0.6, │ │ limit=5, config=ChromaDBConfig(provider='chromadb', │ │ embedding_function=<chromadb.utils.embedding_functions.openai_embedding_function.OpenAIEmbeddingFunction │ │ object at 0x7cd2601d0410>, limit=5, score_threshold=0.6, batch_size=100, tenant='default_tenant', │ │ database='default_database', settings=Settings(environment='', │ │ chroma_api_impl='chromadb.api.rust.RustBindingsAPI', chroma_server_nofile=None, │ │ chroma_server_thread_pool_size=40, tenant_id='default', topic_namespace='default', chroma_server_host=None, │ │ chroma_server_headers=None, chroma_server_http_port=None, chroma_server_ssl_enabled=False, │ │ chroma_server_ssl_verify=None, chroma_server_api_default_path=<APIVersion.V2: '/api/v2'>, │ │ chroma_server_cors_allow_origins=[], is_persistent=True, persist_directory='/root/.local/share/NLPBook', │ │ chroma_memory_limit_bytes=0, chroma_segment_cache_policy=None, allow_reset=True, │ │ chroma_auth_token_transport_header=None, chroma_client_auth_provider=None, │ │ chroma_client_auth_credentials=None, chroma_server_auth_ignore_paths={'APIVersion.V2': ['GET'], │ │ 'APIVersion.V2/heartbeat': ['GET'], 'APIVersion.V2/version': ['GET'], 'APIVersion.V1': ['GET'], │ │ 'APIVersion.V1/heartbeat': ['GET'], 'APIVersion.V1/version': ['GET']}, │ │ chroma_overwrite_singleton_tenant_database_access_from_auth=False, chroma_server_authn_provider=None, │ │ chroma_server_authn_credentials=None, chroma_server_authn_credentials_file=None, │ │ chroma_server_authz_provider=None, chroma_server_authz_config=None, chroma_server_authz_config_file=None, │ │ chroma_product_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', │ │ chroma_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', anonymized_telemetry=False, │ │ chroma_otel_collection_endpoint='', chroma_otel_service_name='chromadb', chroma_otel_collection_headers={}, │ │ chroma_otel_granularity=None, migrations='apply', migrations_hash_algorithm='md5', │ │ chroma_segment_directory_impl='chromadb.segment.impl.distributed.segment_directory.RendezvousHashSegmentDirec │ │ tory', chroma_segment_directory_routing_mode=<RoutingMode.ID: 'id'>, │ │ chroma_memberlist_provider_impl='chromadb.segment.impl.distributed.segment_directory.CustomResourceMemberlist │ │ Provider', worker_memberlist_name='query-service-memberlist', chroma_server_grpc_port=None, │ │ chroma_sysdb_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_producer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_consumer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_segment_manager_impl='chromadb.segment.impl.manager.local.LocalSegmentManager', │ │ chroma_executor_impl='chromadb.execution.executor.local.LocalExecutor', chroma_query_replication_factor=2, │ │ chroma_quota_provider_impl=None, chroma_rate_limiting_provider_impl=None, │ │ chroma_quota_enforcer_impl='chromadb.quota.simple_quota_enforcer.SimpleQuotaEnforcer', │ │ chroma_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleRateLimitEnforcer', │ │ chroma_async_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleAsyncRateLimitEnforcer', │ │ chroma_logservice_request_timeout_seconds=3, chroma_sysdb_request_timeout_seconds=3, │ │ chroma_query_request_timeout_seconds=60, chroma_db_impl=None, │ │ chroma_collection_assignment_policy_impl='chromadb.ingest.impl.simple_policy.SimpleAssignmentPolicy', │ │ chroma_coordinator_host='localhost', chroma_logservice_host='localhost', chroma_logservice_port=50052))), │ │ config={}, txt='crewai/nvidia.txt', │ │ tool_type='crewai_tools.tools.txt_search_tool.txt_search_tool.TXTSearchTool')] │ │ "agent_tools": [name="Search a txt's content" description='Tool Name: │ │ search_a_txts_content\nTool Arguments: {\n "description": "Input for TXTSearchTool.",\n "properties": {\n │ │ "search_query": {\n "description": "Mandatory search query you want to use to search the txt\'s │ │ content",\n "title": "Search Query",\n "type": "string"\n }\n },\n "required": [\n │ │ "search_query"\n ],\n "title": "FixedTXTSearchToolSchema",\n "type": "object",\n "additionalProperties": │ │ false\n}\nTool Description: A tool that can be used to semantic search a query the crewai/nvidia.txt txt\'s │ │ content.' env_vars=[] args_schema=<class │ │ 'crewai_tools.tools.txt_search_tool.txt_search_tool.FixedTXTSearchToolSchema'> result_schema=None │ │ description_updated=False cache_function=<function _default_cache_function at 0x7cd271046fc0> │ │ result_as_answer=False max_usage_count=None current_usage_count=0 summarize=False similarity_threshold=0.6 │ │ limit=5 collection_name='rag_tool_collection' adapter=CrewAIRagAdapter(collection_name='rag_tool_collection', │ │ summarize=False, similarity_threshold=0.6, limit=5, config=ChromaDBConfig(provider='chromadb', │ │ embedding_function=<chromadb.utils.embedding_functions.openai_embedding_function.OpenAIEmbeddingFunction │ │ object at 0x7cd2601d0410>, limit=5, score_threshold=0.6, batch_size=100, tenant='default_tenant', │ │ database='default_database', settings=Settings(environment='', │ │ chroma_api_impl='chromadb.api.rust.RustBindingsAPI', chroma_server_nofile=None, │ │ chroma_server_thread_pool_size=40, tenant_id='default', topic_namespace='default', chroma_server_host=None, │ │ chroma_server_headers=None, chroma_server_http_port=None, chroma_server_ssl_enabled=False, │ │ chroma_server_ssl_verify=None, chroma_server_api_default_path=<APIVersion.V2: '/api/v2'>, │ │ chroma_server_cors_allow_origins=[], is_persistent=True, persist_directory='/root/.local/share/NLPBook', │ │ chroma_memory_limit_bytes=0, chroma_segment_cache_policy=None, allow_reset=True, │ │ chroma_auth_token_transport_header=None, chroma_client_auth_provider=None, │ │ chroma_client_auth_credentials=None, chroma_server_auth_ignore_paths={'APIVersion.V2': ['GET'], │ │ 'APIVersion.V2/heartbeat': ['GET'], 'APIVersion.V2/version': ['GET'], 'APIVersion.V1': ['GET'], │ │ 'APIVersion.V1/heartbeat': ['GET'], 'APIVersion.V1/version': ['GET']}, │ │ chroma_overwrite_singleton_tenant_database_access_from_auth=False, chroma_server_authn_provider=None, │ │ chroma_server_authn_credentials=None, chroma_server_authn_credentials_file=None, │ │ chroma_server_authz_provider=None, chroma_server_authz_config=None, chroma_server_authz_config_file=None, │ │ chroma_product_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', │ │ chroma_telemetry_impl='chromadb.telemetry.product.posthog.Posthog', anonymized_telemetry=False, │ │ chroma_otel_collection_endpoint='', chroma_otel_service_name='chromadb', chroma_otel_collection_headers={}, │ │ chroma_otel_granularity=None, migrations='apply', migrations_hash_algorithm='md5', │ │ chroma_segment_directory_impl='chromadb.segment.impl.distributed.segment_directory.RendezvousHashSegmentDirec │ │ tory', chroma_segment_directory_routing_mode=<RoutingMode.ID: 'id'>, │ │ chroma_memberlist_provider_impl='chromadb.segment.impl.distributed.segment_directory.CustomResourceMemberlist │ │ Provider', worker_memberlist_name='query-service-memberlist', chroma_server_grpc_port=None, │ │ chroma_sysdb_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_producer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_consumer_impl='chromadb.db.impl.sqlite.SqliteDB', │ │ chroma_segment_manager_impl='chromadb.segment.impl.manager.local.LocalSegmentManager', │ │ chroma_executor_impl='chromadb.execution.executor.local.LocalExecutor', chroma_query_replication_factor=2, │ │ chroma_quota_provider_impl=None, chroma_rate_limiting_provider_impl=None, │ │ chroma_quota_enforcer_impl='chromadb.quota.simple_quota_enforcer.SimpleQuotaEnforcer', │ │ chroma_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleRateLimitEnforcer', │ │ chroma_async_rate_limit_enforcer_impl='chromadb.rate_limit.simple_rate_limit.SimpleAsyncRateLimitEnforcer', │ │ chroma_logservice_request_timeout_seconds=3, chroma_sysdb_request_timeout_seconds=3, │ │ chroma_query_request_timeout_seconds=60, chroma_db_impl=None, │ │ chroma_collection_assignment_policy_impl='chromadb.ingest.impl.simple_policy.SimpleAssignmentPolicy', │ │ chroma_coordinator_host='localhost', chroma_logservice_host='localhost', chroma_logservice_port=50052))) │ │ config={} txt='crewai/nvidia.txt' │ │ tool_type='crewai_tools.tools.txt_search_tool.txt_search_tool.TXTSearchTool', name='Search the internet with │ │ Serper' description='Tool Name: search_the_internet_with_serper\nTool Arguments: {\n "description": "Input │ │ for SerperDevTool.",\n "properties": {\n "search_query": {\n "description": "Mandatory search query │ │ you want to use to search the internet",\n "title": "Search Query",\n "type": "string"\n }\n │ │ },\n "required": [\n "search_query"\n ],\n "title": "SerperDevToolSchema",\n "type": "object",\n │ │ "additionalProperties": false\n}\nTool Description: A tool that can be used to search the internet with a │ │ search_query. Supports different search types: \'search\' (default), \'news\'' │ │ env_vars=[EnvVar(name='SERPER_API_KEY', description='API key for Serper', required=True, default=None)] │ │ args_schema=<class 'crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevToolSchema'> │ │ result_schema=None description_updated=False cache_function=<function _default_cache_function at │ │ 0x7cd271046fc0> result_as_answer=False max_usage_count=None current_usage_count=0 │ │ base_url='https://google.serper.dev' n_results=10 save_file=False search_type='search' country='' location='' │ │ locale='' tool_type='crewai_tools.tools.serper_dev_tool.serper_dev_tool.SerperDevTool'] │ │ Create the most descriptive plan based on the tasks descriptions, tools available, and agents' goals for │ │ them to execute their goals with perfection. │ │ Agent: Task Execution Planner │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: Financial Analyst │ │ │ │ Task: Analyze the question, understand the context, and generate the correct response1. Carefully read the │ │ user’s question and isolate the exact ask: determine the forward-looking outlook for Nvidia. │ │ 2. Review the provided context with special attention to the sections labeled Outlook, Highlights, and the │ │ forward-looking statements/disclaimer language. │ │ 3. Use the txt search tool to locate the most relevant passages in crewai/nvidia.txt by searching for │ │ high-signal terms such as "Outlook", "fiscal 2026", "Blackwell", "Data Center", "revenue is expected", and │ │ "forward-looking statements". │ │ 4. If necessary, use the internet search tool only to validate whether there is any additional public context │ │ around Nvidia’s outlook, but prioritize the provided document since the task is to answer based on the │ │ supplied content. │ │ 5. Extract the core forward-looking guidance exactly as stated in the source, including revenue expectations, │ │ margin expectations, operating expense expectations, other income/expense expectations, and tax rate │ │ expectations. │ │ 6. Identify broader qualitative outlook cues from the Highlights section, including record Data Center │ │ revenue growth, the role in the Stargate Project, and references to Blackwell, AI growth, agentic AI, and │ │ physical AI. │ │ 7. Note that the press release explicitly frames these as forward-looking statements and includes risk │ │ factors; keep this context intact and do not overstate certainty. │ │ 8. Construct the answer so it directly addresses the question with a concise but complete outlook summary, │ │ using the source’s numbers and language where appropriate. │ │ 9. Ensure the response distinguishes between near-term quantified guidance and longer-term thematic optimism, │ │ while acknowledging the risks and uncertainties stated by Nvidia. │ │ 10. Deliver a clear final response that answers what Nvidia’s outlook is, grounded strictly in the provided │ │ text and phrased as a relevant answer to the question. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#1) ─────────────────────────────────────────╮ │ │ │ Tool: search_a_txts_content │ │ Args: {'search_query': 'Outlook'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool search_a_txts_content executed with result: Relevant Content:
$
313
$
292
$
242
$
1,136
$
876
(C) Other consists of IP-related costs and assets held for sale related adjustments
(D) Income tax impact of non-GAAP adjustments, includi...
╭─────────────────────────────────────── ✅ Tool Execution Completed (#1) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_a_txts_content │ │ Output: Relevant Content: │ │ │ │ $ │ │ │ │ 313 │ │ │ │ $ │ │ │ │ 292 │ │ │ │ $ │ │ │ │ 242 │ │ │ │ $ │ │ │ │ 1,136 │ │ │ │ $ │ │ │ │ 876 │ │ │ │ (C) Other consists of IP-related costs and assets held for sale related adjustments │ │ │ │ (D) Income tax impact of non-GAAP adjustments, including the recognition of excess tax benefits or │ │ deficiencies related to stock-based compensation under GAAP accounting standard (ASU 2016-09). │ │ │ │ (E) Reflects a ten-for-one stock split on June 7, 2024 │ │ │ │ NVIDIA CORPORATION │ │ │ │ RECONCILIATION OF GAAP TO NON-GAAP OUTLOOK │ │ │ │ Q1 FY2026 Outlook │ │ │ │ ($ in millions) │ │ │ │ GAAP gross margin │ │ │ │ 70.6 │ │ │ │ % │ │ │ │ Impact of stock-based compensation expense, acquisition-related costs, and other costs │ │ │ │ 0.4 │ │ │ │ % │ │ │ │ Non-GAAP gross margin │ │ │ │ 71.0 │ │ │ │ % │ │ │ │ GAAP operating expenses │ │ │ │ $ │ │ │ │ 5,150 │ │ │ │ Stock-based compensation expense, acquisition-related costs, and other costs │ │ │ │ (1,550 │ │ │ │ ) │ │ │ │ Non-GAAP operating expenses │ │ │ │ $ │ │ │ │ 3,600 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────── 🔧 Tool Execution Started (#2) ─────────────────────────────────────────╮ │ │ │ Tool: search_a_txts_content │ │ Args: {'search_query': 'fiscal 2026'} │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Tool search_a_txts_content executed with result: Relevant Content:
per share)
Q4 FY25
Q3 FY25
Q4 FY24
Q/Q
Y/Y
Revenue
$39,331
$35,082
$22,103
Up 12%
Up 78%
Gross margin
73.0%
74.6%
76.0%
Down 1.6 pts
Down 3.0 pts
Operating expense...
╭─────────────────────────────────────── ✅ Tool Execution Completed (#2) ────────────────────────────────────────╮ │ │ │ Tool Completed │ │ Tool: search_a_txts_content │ │ Output: Relevant Content: │ │ │ │ per share) │ │ │ │ Q4 FY25 │ │ │ │ Q3 FY25 │ │ │ │ Q4 FY24 │ │ │ │ Q/Q │ │ │ │ Y/Y │ │ │ │ Revenue │ │ │ │ $39,331 │ │ │ │ $35,082 │ │ │ │ $22,103 │ │ │ │ Up 12% │ │ │ │ Up 78% │ │ │ │ Gross margin │ │ │ │ 73.0% │ │ │ │ 74.6% │ │ │ │ 76.0% │ │ │ │ Down 1.6 pts │ │ │ │ Down 3.0 pts │ │ │ │ Operating expenses │ │ │ │ $4,689 │ │ │ │ $4,287 │ │ │ │ $3,176 │ │ │ │ Up 9% │ │ │ │ Up 48% │ │ │ │ Operating income │ │ │ │ $24,034 │ │ │ │ $21,869 │ │ │ │ $13,615 │ │ │ │ Up 10% │ │ │ │ Up 77% │ │ │ │ Net income │ │ │ │ $22,091 │ │ │ │ $19,309 │ │ │ │ $12,285 │ │ │ │ Up 14% │ │ │ │ Up 80% │ │ │ │ Diluted earnings per share* │ │ │ │ $0.89 │ │ │ │ $0.78 │ │ │ │ $0.49 │ │ │ │ Up 14% │ │ │ │ Up 82% │ │ │ │ Non-GAAP │ │ │ │ ($ in millions, except earnings │ │ │ │ per share) │ │ │ │ Q4 FY25 │ │ │ │ Q3 FY25 │ │ │ │ Q4 FY24 │ │ │ │ Q/Q │ │ │ │ Y/Y │ │ │ │ Revenue │ │ │ │ $39,331 │ │ │ │ $35,082 │ │ │ │ $22,103 │ │ │ │ Up 12% │ │ │ │ Up 78% │ │ │ │ Gross margin │ │ │ │ 73.5% │ │ │ │ 75.0% │ │ │ │ 76.7% │ │ │ │ Down 1.5 pts │ │ │ │ Down 3.2 pts │ │ │ │ Operating expenses │ │ │ │ $3,378 │ │ │ │ $3,046 │ │ │ │ $2,210 │ │ │ │ Up 11% │ │ │ │ Up 53% │ │ │ │ Operating income │ │ │ │ $25,516 │ │ │ │ $23,276 │ │ │ │ $14,749 │ │ │ │ Up 10% │ │ │ │ Up 73% │ │ │ │ Net income │ │ │ │ $22,066 │ │ │ │ $20,010 │ │ │ │ $12,839 │ │ │ │ Up 10% │ │ │ │ Up 72% │ │ │ │ Diluted earnings per share* │ │ │ │ $0.89 │ │ │ │ $0.81 │ │ │ │ $0.52 │ │ │ │ Up 10% │ │ │ │ Up 71% │ │ │ │ Fiscal 2025 Summary │ │ │ │ GAAP │ │ │ │ ($ in millions, except earnings │ │ │ │ per share) │ │ │ │ FY25 │ │ │ │ FY24 │ │ │ │ Y/Y │ │ │ │ Revenue │ │ │ │ $130,497 │ │ │ │ $60,922 │ │ │ │ Up 114% │ │ │ │ Gross margin │ │ │ │ 75.0% │ │ │ │ 72.7% │ │ │ │ Up 2.3 pts │ │ │ │ Operating expenses │ │ │ │ $16,405 │ │ │ │ $11,329 │ │ │ │ Up 45% │ │ │ │ Operating income │ │ │ │ $81,453 │ │ │ │ $32,972 │ │ │ │ Up 147% │ │ │ │ Net income │ │ │ │ $72,880 │ │ │ │ $29,760 │ │ │ │ Up 145% │ │ │ │ Diluted earnings per share* │ │ │ │ $2.94 │ │ │ │ $1.19 │ │ │ │ Up 147% │ │ │ │ Non-GAAP │ │ │ │ ($ in millions, except earnings │ │ │ │ per share) │ │ │ │ FY25 │ │ │ │ FY24 │ │ │ │ Y/Y │ │ │ │ Revenue │ │ │ │ $130,497 │ │ │ │ $60,922 │ │ │ │ Up 114% │ │ │ │ Gross margin │ │ │ │ 75.5% │ │ │ │ 73.8% │ │ │ │ Up 1.7 pts │ │ │ │ Operating expenses │ │ │ │ $11,716 │ │ │ │ $7,825 │ │ │ │ Up 50% │ │ │ │ Operating income │ │ │ │ $86,789 │ │ │ │ $37,134 │ │ │ │ Up 134% │ │ │ │ Net income │ │ │ │ $74,265 │ │ │ │ $32,312 │ │ │ │ Up 130% │ │ │ │ │ │ June 22, 2026 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ Certain statements in this press release including, but not limited to, statements as to: AI advancing at │ │ light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest │ │ industries; expectations with respect to growth, performance and benefits of NVIDIA’s products, services and │ │ technologies, including Blackwell, and related trends and drivers; expectations with respect to supply and │ │ demand for NVIDIA’s products, services and technologies, including Blackwell, and related matters including │ │ inventory, production and distribution; expectations with respect to NVIDIA’s third party arrangements, │ │ including with its collaborators and partners; expectations with respect to technology developments and │ │ related trends and drivers; future NVIDIA cash dividends or other returns to stockholders; NVIDIA’s financial │ │ and business outlook for the first quarter of fiscal 2026 and beyond; projected market growth and trends; │ │ expectations with respect to AI and related industries; and other statements that are not historical facts │ │ are risks and uncertainties that could cause results to be materially different than expectations │ │ │ │ │ │ $ │ │ │ │ 313 │ │ │ │ $ │ │ │ │ 292 │ │ │ │ $ │ │ │ │ 242 │ │ │ │ $ │ │ │ │ 1,136 │ │ │ │ $ │ │ │ │ 876 │ │ │ │ (C) Other consists of IP-related costs and assets held for sale related adjustments │ │ │ │ (D) Income tax impact of non-GAAP adjustments, including the recognition of excess tax benefits or │ │ deficiencies related to stock-based compensation under GAAP accounting standard (ASU 2016-09). │ │ │ │ (E) Reflects a ten-for-one stock split on June 7, 2024 │ │ │ │ NVIDIA CORPORATION │ │ │ │ RECONCILIATION OF GAAP TO NON-GAAP OUTLOOK │ │ │ │ Q1 FY2026 Outlook │ │ │ │ ($ in millions) │ │ │ │ GAAP gross margin │ │ │ │ 70.6 │ │ │ │ % │ │ │ │ Impact of stock-based compensation expense, acquisition-related costs, and other costs │ │ │ │ 0.4 │ │ │ │ % │ │ │ │ Non-GAAP gross margin │ │ │ │ 71.0 │ │ │ │ % │ │ │ │ GAAP operating expenses │ │ │ │ $ │ │ │ │ 5,150 │ │ │ │ Stock-based compensation expense, acquisition-related costs, and other costs │ │ │ │ (1,550 │ │ │ │ ) │ │ │ │ Non-GAAP operating expenses │ │ │ │ $ │ │ │ │ 3,600 │ │ │ │ About NVIDIA │ │ │ │ NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing. │ │ │ │ │ │ 73.8% │ │ │ │ Up 1.7 pts │ │ │ │ Operating expenses │ │ │ │ $11,716 │ │ │ │ $7,825 │ │ │ │ Up 50% │ │ │ │ Operating income │ │ │ │ $86,789 │ │ │ │ $37,134 │ │ │ │ Up 134% │ │ │ │ Net income │ │ │ │ $74,265 │ │ │ │ $32,312 │ │ │ │ Up 130% │ │ │ │ Diluted earnings per share* │ │ │ │ $2.99 │ │ │ │ $1.30 │ │ │ │ Up 130% │ │ │ │ *All per share amounts presented herein have been retroactively adjusted to reflect the ten-for-one stock │ │ split, which was effective June 7, 2024. │ │ │ │ Outlook │ │ │ │ NVIDIA’s outlook for the first quarter of fiscal 2026 is as follows: │ │ │ │ Revenue is expected to be $43.0 billion, plus or minus 2%. │ │ │ │ GAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis │ │ points. │ │ │ │ GAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, │ │ respectively. │ │ │ │ GAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, │ │ excluding gains and losses from non-marketable and publicly-held equity securities. │ │ │ │ GAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ Highlights │ │ │ │ NVIDIA achieved progress since its previous earnings announcement in these areas: │ │ │ │ Data Center │ │ │ │ Fourth-quarter revenue was a record $35.6 billion, up 16% from the previous quarter and up 93% from a year │ │ ago. Full-year revenue rose 142% to a record $115.2 billion. │ │ │ │ Announced that NVIDIA will serve as a key technology partner for the $500 billion Stargate Project. │ │ │ │ │ │ 24,706 │ │ │ │ 24,774 │ │ │ │ 24,900 │ │ │ │ 24,804 │ │ │ │ 24,936 │ │ │ │ GAAP net cash provided by operating activities │ │ │ │ $ │ │ │ │ 16,628 │ │ │ │ $ │ │ │ │ 17,629 │ │ │ │ $ │ │ │ │ 11,499 │ │ │ │ $ │ │ │ │ 64,089 │ │ │ │ $ │ │ │ │ 28,090 │ │ │ │ Purchases related to property and equipment and intangible assets │ │ │ │ (1,077 │ │ │ │ ) │ │ │ │ (813 │ │ │ │ ) │ │ │ │ (253 │ │ │ │ ) │ │ │ │ (3,236 │ │ │ │ ) │ │ │ │ (1,069 │ │ │ │ ) │ │ │ │ Principal payments on property and equipment and intangible assets │ │ │ │ (32 │ │ │ │ ) │ │ │ │ (29 │ │ │ │ ) │ │ │ │ (29 │ │ │ │ ) │ │ │ │ (129 │ │ │ │ ) │ │ │ │ (74 │ │ │ │ ) │ │ │ │ Free cash flow │ │ │ │ $ │ │ │ │ 15,519 │ │ │ │ $ │ │ │ │ 16,787 │ │ │ │ $ │ │ │ │ 11,217 │ │ │ │ $ │ │ │ │ 60,724 │ │ │ │ $ │ │ │ │ 26,947 │ │ │ │ (A) Acquisition-related and other costs are comprised of amortization of intangible assets, transaction │ │ costs, and certain compensation charges and are included in the following line items: │ │ │ │ Three Months Ended │ │ │ │ Twelve Months Ended │ │ │ │ January 26, │ │ │ │ October 27, │ │ │ │ January 28, │ │ │ │ January 26, │ │ │ │ January 28, │ │ │ │ 2025 │ │ │ │ 2024 │ │ │ │ 2024 │ │ │ │ 2025 │ │ │ │ 2024 │ │ │ │ Cost of revenue │ │ │ │ $ │ │ │ │ 118 │ │ │ │ $ │ │ │ │ 116 │ │ │ │ $ │ │ │ │ 119 │ │ │ │ $ │ │ │ │ 472 │ │ │ │ $ │ │ │ │ 477 │ │ │ │ Research and development │ │ │ │ $ │ │ │ │ 27 │ │ │ │ $ │ │ │ │ 23 │ │ │ │ $ │ │ │ │ 12 │ │ │ │ $ │ │ │ │ 79 │ │ │ │ $ │ │ │ │ 49 │ │ │ │ Sales, general and administrative │ │ │ │ $ │ │ │ │ 16 │ │ │ │ $ │ │ │ │ 16 │ │ │ │ $ │ │ │ │ 6 │ │ │ │ $ │ │ │ │ 51 │ │ │ │ $ │ │ │ │ 57 │ │ │ │ (B) Stock-based compensation consists of the following: │ │ │ │ Three Months Ended │ │ │ │ Twelve Months Ended │ │ │ │ January 26, │ │ │ │ October 27, │ │ │ │ January 28, │ │ │ │ January 26, │ │ │ │ January 28, │ │ │ │ 2025 │ │ │ │ 2024 │ │ │ │ 2024 │ │ │ │ 2025 │ │ │ │ 2024 │ │ │ │ Cost of revenue │ │ │ │ $ │ │ │ │ 53 │ │ │ │ $ │ │ │ │ 50 │ │ │ │ $ │ │ │ │ 45 │ │ │ │ $ │ │ │ │ 178 │ │ │ │ $ │ │ │ │ 141 │ │ │ │ Research and development │ │ │ │ $ │ │ │ │ 955 │ │ │ │ $ │ │ │ │ 910 │ │ │ │ $ │ │ │ │ 706 │ │ │ │ $ │ │ │ │ 3,423 │ │ │ │ $ │ │ │ │ 2,532 │ │ │ │ Sales, general and administrative │ │ │ │ $ │ │ │ │ 313 │ │ │ │ $ │ │ │ │ 292 │ │ │ │ $ │ │ │ │ 242 │ │ │ │ $ │ │ │ │ 1,136 │ │ │ │ $ │ │ │ │ 876 │ │ │ │ (C) Other consists of IP-related costs and assets held for sale related adjustments │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[Finalize] todos_count=0, todos_with_results=0
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: Financial Analyst │ │ │ │ Final Answer: │ │ The forward-looking outlook for Nvidia for the first quarter of fiscal 2026 is as follows: │ │ │ │ - Revenue is expected to be $43.0 billion, plus or minus 2%. │ │ - GAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis │ │ points. │ │ - GAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, │ │ respectively. │ │ - GAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, │ │ excluding gains and losses from non-marketable and publicly-held equity securities. │ │ - GAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ Highlights indicating broader qualitative outlook include: │ │ │ │ - Data Center segment achieved fourth-quarter revenue of a record $35.6 billion, up 16% from the prior │ │ quarter and up 93% year-over-year. Full-year revenue rose 142% to a record $115.2 billion. │ │ - Nvidia announced it will serve as a key technology partner for the $500 billion Stargate Project. │ │ - The company highlights AI advancing at light speed, with agentic AI and physical AI setting the stage for │ │ the next wave of revolution across major industries. │ │ - Expectations for growth, performance, and benefits of Nvidia’s products, technologies including Blackwell, │ │ supply and demand dynamics, and market trends reflect positive future momentum. │ │ │ │ Nvidia explicitly states these forward-looking statements are subject to risks and uncertainties that could │ │ cause actual results to differ materially. Important risk factors include global economic and political │ │ conditions, reliance on third parties for manufacturing, technological competition and developments, market │ │ acceptance, product performance issues, changes in consumer preferences, regulatory changes, and other │ │ factors disclosed in Nvidia’s SEC filings. │ │ │ │ Therefore, Nvidia’s outlook for Q1 FY 2026 and beyond demonstrates strong revenue growth expectations, stable │ │ to slightly lower gross margins compared to previous periods, controlled operating expenses, and a positive │ │ other income outlook, supported by significant progress in its Data Center segment, AI advancements, new │ │ partnerships like the Stargate Project, and innovations like Blackwell. However, these expectations are made │ │ with caution given the various stated risks. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Analyze the question, understand the context, and generate the correct response1. Carefully read the │ │ user’s question and isolate the exact ask: determine the forward-looking outlook for Nvidia. │ │ 2. Review the provided context with special attention to the sections labeled Outlook, Highlights, and the │ │ forward-looking statements/disclaimer language. │ │ 3. Use the txt search tool to locate the most relevant passages in crewai/nvidia.txt by searching for │ │ high-signal terms such as "Outlook", "fiscal 2026", "Blackwell", "Data Center", "revenue is expected", and │ │ "forward-looking statements". │ │ 4. If necessary, use the internet search tool only to validate whether there is any additional public context │ │ around Nvidia’s outlook, but prioritize the provided document since the task is to answer based on the │ │ supplied content. │ │ 5. Extract the core forward-looking guidance exactly as stated in the source, including revenue expectations, │ │ margin expectations, operating expense expectations, other income/expense expectations, and tax rate │ │ expectations. │ │ 6. Identify broader qualitative outlook cues from the Highlights section, including record Data Center │ │ revenue growth, the role in the Stargate Project, and references to Blackwell, AI growth, agentic AI, and │ │ physical AI. │ │ 7. Note that the press release explicitly frames these as forward-looking statements and includes risk │ │ factors; keep this context intact and do not overstate certainty. │ │ 8. Construct the answer so it directly addresses the question with a concise but complete outlook summary, │ │ using the source’s numbers and language where appropriate. │ │ 9. Ensure the response distinguishes between near-term quantified guidance and longer-term thematic optimism, │ │ while acknowledging the risks and uncertainties stated by Nvidia. │ │ 10. Deliver a clear final response that answers what Nvidia’s outlook is, grounded strictly in the provided │ │ text and phrased as a relevant answer to the question. │ │ Agent: Financial Analyst │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── Crew Completion ────────────────────────────────────────────────╮ │ │ │ Crew Execution Completed │ │ Name: crew │ │ ID: dd02df7b-1f68-4a3e-8cb3-0020f85c3a4a │ │ Final Output: The forward-looking outlook for Nvidia for the first quarter of fiscal 2026 is as follows: │ │ │ │ - Revenue is expected to be $43.0 billion, plus or minus 2%. │ │ - GAAP and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively, plus or minus 50 basis │ │ points. │ │ - GAAP and non-GAAP operating expenses are expected to be approximately $5.2 billion and $3.6 billion, │ │ respectively. │ │ - GAAP and non-GAAP other income and expense are expected to be an income of approximately $400 million, │ │ excluding gains and losses from non-marketable and publicly-held equity securities. │ │ - GAAP and non-GAAP tax rates are expected to be 17.0%, plus or minus 1%, excluding any discrete items. │ │ │ │ Highlights indicating broader qualitative outlook include: │ │ │ │ - Data Center segment achieved fourth-quarter revenue of a record $35.6 billion, up 16% from the prior │ │ quarter and up 93% year-over-year. Full-year revenue rose 142% to a record $115.2 billion. │ │ - Nvidia announced it will serve as a key technology partner for the $500 billion Stargate Project. │ │ - The company highlights AI advancing at light speed, with agentic AI and physical AI setting the stage for │ │ the next wave of revolution across major industries. │ │ - Expectations for growth, performance, and benefits of Nvidia’s products, technologies including Blackwell, │ │ supply and demand dynamics, and market trends reflect positive future momentum. │ │ │ │ Nvidia explicitly states these forward-looking statements are subject to risks and uncertainties that could │ │ cause actual results to differ materially. Important risk factors include global economic and political │ │ conditions, reliance on third parties for manufacturing, technological competition and developments, market │ │ acceptance, product performance issues, changes in consumer preferences, regulatory changes, and other │ │ factors disclosed in Nvidia’s SEC filings. │ │ │ │ Therefore, Nvidia’s outlook for Q1 FY 2026 and beyond demonstrates strong revenue growth expectations, stable │ │ to slightly lower gross margins compared to previous periods, controlled operating expenses, and a positive │ │ other income outlook, supported by significant progress in its Data Center segment, AI advancements, new │ │ partnerships like the Stargate Project, and innovations like Blackwell. However, these expectations are made │ │ with caution given the various stated risks. │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
p80(output.raw)
The forward-looking outlook for Nvidia for the first quarter of fiscal 2026 is
as follows: - Revenue is expected to be $43.0 billion, plus or minus 2%. - GAAP
and non-GAAP gross margins are expected to be 70.6% and 71.0%, respectively,
plus or minus 50 basis points. - GAAP and non-GAAP operating expenses are
expected to be approximately $5.2 billion and $3.6 billion, respectively. - GAAP
and non-GAAP other income and expense are expected to be an income of
approximately $400 million, excluding gains and losses from non-marketable and
publicly-held equity securities. - GAAP and non-GAAP tax rates are expected to
be 17.0%, plus or minus 1%, excluding any discrete items. Highlights indicating
broader qualitative outlook include: - Data Center segment achieved fourth-
quarter revenue of a record $35.6 billion, up 16% from the prior quarter and up
93% year-over-year. Full-year revenue rose 142% to a record $115.2 billion. -
Nvidia announced it will serve as a key technology partner for the $500 billion
Stargate Project. - The company highlights AI advancing at light speed, with
agentic AI and physical AI setting the stage for the next wave of revolution
across major industries. - Expectations for growth, performance, and benefits of
Nvidia’s products, technologies including Blackwell, supply and demand dynamics,
and market trends reflect positive future momentum. Nvidia explicitly states
these forward-looking statements are subject to risks and uncertainties that
could cause actual results to differ materially. Important risk factors include
global economic and political conditions, reliance on third parties for
manufacturing, technological competition and developments, market acceptance,
product performance issues, changes in consumer preferences, regulatory changes,
and other factors disclosed in Nvidia’s SEC filings. Therefore, Nvidia’s
outlook for Q1 FY 2026 and beyond demonstrates strong revenue growth
expectations, stable to slightly lower gross margins compared to previous
periods, controlled operating expenses, and a positive other income outlook,
supported by significant progress in its Data Center segment, AI advancements,
new partnerships like the Stargate Project, and innovations like Blackwell.
However, these expectations are made with caution given the various stated
risks.
40.7. Application: Conversation between a therapist and a patient#
%run keys.ipynb
!pip install colorama --quiet
from crewai import Agent, Task, Crew
# Initialize colorama for cross-platform color support
from colorama import Fore, Style, init
init()
# Define a custom callback function
def blue_final_answer(output):
"""Callback to print the final answer in dark blue."""
print(Fore.BLUE + "Final Answer: " + output.raw + Style.RESET_ALL)
# Define Agents and Tasks, finally Crew
patient = Agent(
role = 'A patient in therapy',
goal = f'Talk to a therapist about your problem, and answer questions asked by the therapist, and stop when you are satisfied with the answers',
backstory = 'You are a patient who suffers from stress because of poor work life balance',
verbose = True,
allow_delegation = False,
tools = []
)
therapist = Agent(
role = 'A therapist who meets patients',
goal = f'Listen to a patient and ask questions to a patient about their problem, receive an answer, and keep the conversation going, and stop when you are satisfied with the answers',
backstory = 'You are a therapist who see patients for therapy',
verbose = True,
allow_delegation = False,
tools = []
)
task_patient = Task(
description = "Engage in a fruitful conversation with the therapist to alleviate your stress",
tools = [],
agent = patient,
expected_output = 'A successful therapy session with about 20 exchanges in the conversation between patient and therapist',
callback=blue_final_answer,
)
task_therapist = Task(
description = "Engage in a fruitful conversation with the patient to alleviate his stress",
tools = [],
agent = therapist,
expected_output = 'A successful therapy session with about 20 exchanges in the conversation between patient and therapist'
)
crew = Crew(
agents = [patient, therapist],
tasks = [task_patient, task_therapist],
verbose = True
)
import asyncio
result = await crew.kickoff_async()
╭─────────────────────────────────────────── 🚀 Crew Execution Started ───────────────────────────────────────────╮ │ │ │ Crew Execution Started │ │ Name: crew │ │ ID: 062c8a4f-472e-4614-a352-f9213b2d4977 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Engage in a fruitful conversation with the therapist to alleviate your stress │ │ ID: d005c0f4-c7a8-4e86-8247-f131edc1a721 │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: A patient in therapy │ │ │ │ Task: Engage in a fruitful conversation with the therapist to alleviate your stress │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[Finalize] todos_count=0, todos_with_results=0
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: A patient in therapy │ │ │ │ Final Answer: │ │ Therapist: Good afternoon. I’m glad you’re here today. You mentioned you’re experiencing stress due to poor │ │ work-life balance. Can you tell me a bit more about what’s been going on? │ │ │ │ Patient: Thank you for seeing me. Lately, I feel overwhelmed because work takes up most of my time and │ │ energy. I hardly have time to relax or spend with family and friends. It feels like I’m always working or │ │ worrying about work. │ │ │ │ Therapist: That sounds really tough. When did you first start noticing this imbalance in your life? │ │ │ │ Patient: I think it started a few months ago. My workload increased, and I started taking work home in the │ │ evenings. Weekends used to be free, but now I’m answering emails or finishing projects. It’s like the work │ │ never ends. │ │ │ │ Therapist: I see. How is this affecting other areas of your life, like your relationships, hobbies, or │ │ overall well-being? │ │ │ │ Patient: My relationships are definitely suffering. I’m often too tired to socialize or even call my friends │ │ and family. Hobbies have been neglected. I used to enjoy reading and going for walks, but now I feel too │ │ stressed or drained. Also, I’ve been feeling anxious and have trouble sleeping. │ │ │ │ Therapist: That must be really hard to cope with. When you think about why you’ve taken on so much work, what │ │ comes to mind? │ │ │ │ Patient: I guess I’m afraid of falling behind or disappointing my boss. There’s pressure to perform well, and │ │ I feel like if I don’t put in extra hours, I won’t be seen as a good employee. │ │ │ │ Therapist: It sounds like you’re carrying a lot of pressure and responsibility. Do you set any boundaries │ │ when it comes to work, like specific end times or breaks, or is it more flexible? │ │ │ │ Patient: Honestly, I don’t set firm boundaries. My work hours are flexible, which sounds good, but in │ │ practice, it means I’m working whenever I can. Sometimes I check emails late at night or during meals. │ │ │ │ Therapist: That flexibility can be a double-edged sword. Have you tried setting any limits on your work time │ │ or creating a routine to help separate work from personal time? │ │ │ │ Patient: I’ve thought about it but haven’t really put anything concrete in place. It’s hard because the │ │ workload can be unpredictable, and I worry that if I say no or stop early, things will pile up. │ │ │ │ Therapist: That fear is understandable. Let’s explore what small changes might feel manageable to you. For │ │ example, could you consider designating one hour after work as “no work” time just to rest or pursue │ │ something enjoyable? │ │ │ │ Patient: That might be doable. Maybe I could try to stop working by 7 pm and use that time to go for a walk │ │ or read. │ │ │ │ Therapist: That sounds like a positive step. How do you think you could communicate this boundary at work or │ │ to yourself so it feels more real? │ │ │ │ Patient: I could let my colleagues know that after 7 pm I won’t respond to emails unless it’s an emergency. I │ │ also need to remind myself that taking breaks won’t make me less productive in the long run. │ │ │ │ Therapist: It’s important to give yourself permission to rest. How do you feel about the idea of practicing │ │ mindfulness or relaxation techniques to manage stress more effectively? │ │ │ │ Patient: I’ve heard about mindfulness but haven’t tried it. I’m willing to give it a shot if it can help me │ │ stay calmer and more focused. │ │ │ │ Therapist: Great. I can guide you through some simple mindfulness exercises in our sessions. Also, how is │ │ your sleep? You mentioned trouble sleeping—what does your typical night look like? │ │ │ │ Patient: I often lie awake thinking about work or things I need to do. Sometimes I get only 4-5 hours of │ │ sleep. When I’m tired, I’m even less motivated to relax or do self-care. │ │ │ │ Therapist: Sleep difficulties can increase stress and reduce overall functioning. We can look at improving │ │ your sleep hygiene and strategies to calm your mind before bed. Are you open to that? │ │ │ │ Patient: Yes, definitely. I want to feel more rested. │ │ │ │ Therapist: That’s a good goal. When you think about your ideal work-life balance, what would it look like? │ │ │ │ Patient: I’d like to have regular work hours and be able to fully disconnect after work. I want time for │ │ hobbies, socializing, and taking care of myself. Feeling less anxious and more in control would be amazing. │ │ │ │ Therapist: Those are realistic and healthy goals. Let’s work on creating a gradual plan to move towards that │ │ balance. What do you think might get in the way, and how can we address those challenges? │ │ │ │ Patient: The main challenge is my own expectations and fear of falling behind. Also, workplace culture │ │ sometimes rewards overworking. I guess I need support in changing my mindset and communicating boundaries. │ │ │ │ Therapist: That’s very insightful. We can work on building your assertiveness and coping skills to handle │ │ these pressures. Would it feel useful to explore any past experiences or beliefs contributing to these fears? │ │ │ │ Patient: Yes, I think I’ve always felt that I have to prove myself, especially at work. I’m afraid that if I │ │ don’t keep up, I might lose what I’ve earned. │ │ │ │ Therapist: Understanding these core beliefs can help us reshape them. For now, let’s focus on practical steps │ │ you can take this week to create space for yourself. Can you identify one or two small changes to start with? │ │ │ │ Patient: I’ll try setting a 7 pm cutoff for work and dedicate 30 minutes to a relaxing activity before bed. │ │ Also, I’ll write down my worries before going to sleep to clear my mind. │ │ │ │ Therapist: Excellent. We’ll check in on how these changes go next time. Remember, progress can be gradual. │ │ How do you feel after discussing all this today? │ │ │ │ Patient: I feel hopeful. It’s good to have a plan and realize I’m not alone in this. Talking about it helps. │ │ │ │ Therapist: I’m glad to hear that. You’re doing important work for your wellbeing. We’ll continue working │ │ together to support you. Is there anything else you want to address before we wrap up today? │ │ │ │ Patient: No, this covers it. Thank you. │ │ │ │ Therapist: You’re very welcome. Take care, and I look forward to seeing you at our next session. │ │ │ │ Patient: Thanks. See you then. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Final Answer: Therapist: Good afternoon. I’m glad you’re here today. You mentioned you’re experiencing stress due to poor work-life balance. Can you tell me a bit more about what’s been going on?
Patient: Thank you for seeing me. Lately, I feel overwhelmed because work takes up most of my time and energy. I hardly have time to relax or spend with family and friends. It feels like I’m always working or worrying about work.
Therapist: That sounds really tough. When did you first start noticing this imbalance in your life?
Patient: I think it started a few months ago. My workload increased, and I started taking work home in the evenings. Weekends used to be free, but now I’m answering emails or finishing projects. It’s like the work never ends.
Therapist: I see. How is this affecting other areas of your life, like your relationships, hobbies, or overall well-being?
Patient: My relationships are definitely suffering. I’m often too tired to socialize or even call my friends and family. Hobbies have been neglected. I used to enjoy reading and going for walks, but now I feel too stressed or drained. Also, I’ve been feeling anxious and have trouble sleeping.
Therapist: That must be really hard to cope with. When you think about why you’ve taken on so much work, what comes to mind?
Patient: I guess I’m afraid of falling behind or disappointing my boss. There’s pressure to perform well, and I feel like if I don’t put in extra hours, I won’t be seen as a good employee.
Therapist: It sounds like you’re carrying a lot of pressure and responsibility. Do you set any boundaries when it comes to work, like specific end times or breaks, or is it more flexible?
Patient: Honestly, I don’t set firm boundaries. My work hours are flexible, which sounds good, but in practice, it means I’m working whenever I can. Sometimes I check emails late at night or during meals.
Therapist: That flexibility can be a double-edged sword. Have you tried setting any limits on your work time or creating a routine to help separate work from personal time?
Patient: I’ve thought about it but haven’t really put anything concrete in place. It’s hard because the workload can be unpredictable, and I worry that if I say no or stop early, things will pile up.
Therapist: That fear is understandable. Let’s explore what small changes might feel manageable to you. For example, could you consider designating one hour after work as “no work” time just to rest or pursue something enjoyable?
Patient: That might be doable. Maybe I could try to stop working by 7 pm and use that time to go for a walk or read.
Therapist: That sounds like a positive step. How do you think you could communicate this boundary at work or to yourself so it feels more real?
Patient: I could let my colleagues know that after 7 pm I won’t respond to emails unless it’s an emergency. I also need to remind myself that taking breaks won’t make me less productive in the long run.
Therapist: It’s important to give yourself permission to rest. How do you feel about the idea of practicing mindfulness or relaxation techniques to manage stress more effectively?
Patient: I’ve heard about mindfulness but haven’t tried it. I’m willing to give it a shot if it can help me stay calmer and more focused.
Therapist: Great. I can guide you through some simple mindfulness exercises in our sessions. Also, how is your sleep? You mentioned trouble sleeping—what does your typical night look like?
Patient: I often lie awake thinking about work or things I need to do. Sometimes I get only 4-5 hours of sleep. When I’m tired, I’m even less motivated to relax or do self-care.
Therapist: Sleep difficulties can increase stress and reduce overall functioning. We can look at improving your sleep hygiene and strategies to calm your mind before bed. Are you open to that?
Patient: Yes, definitely. I want to feel more rested.
Therapist: That’s a good goal. When you think about your ideal work-life balance, what would it look like?
Patient: I’d like to have regular work hours and be able to fully disconnect after work. I want time for hobbies, socializing, and taking care of myself. Feeling less anxious and more in control would be amazing.
Therapist: Those are realistic and healthy goals. Let’s work on creating a gradual plan to move towards that balance. What do you think might get in the way, and how can we address those challenges?
Patient: The main challenge is my own expectations and fear of falling behind. Also, workplace culture sometimes rewards overworking. I guess I need support in changing my mindset and communicating boundaries.
Therapist: That’s very insightful. We can work on building your assertiveness and coping skills to handle these pressures. Would it feel useful to explore any past experiences or beliefs contributing to these fears?
Patient: Yes, I think I’ve always felt that I have to prove myself, especially at work. I’m afraid that if I don’t keep up, I might lose what I’ve earned.
Therapist: Understanding these core beliefs can help us reshape them. For now, let’s focus on practical steps you can take this week to create space for yourself. Can you identify one or two small changes to start with?
Patient: I’ll try setting a 7 pm cutoff for work and dedicate 30 minutes to a relaxing activity before bed. Also, I’ll write down my worries before going to sleep to clear my mind.
Therapist: Excellent. We’ll check in on how these changes go next time. Remember, progress can be gradual. How do you feel after discussing all this today?
Patient: I feel hopeful. It’s good to have a plan and realize I’m not alone in this. Talking about it helps.
Therapist: I’m glad to hear that. You’re doing important work for your wellbeing. We’ll continue working together to support you. Is there anything else you want to address before we wrap up today?
Patient: No, this covers it. Thank you.
Therapist: You’re very welcome. Take care, and I look forward to seeing you at our next session.
Patient: Thanks. See you then.
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Engage in a fruitful conversation with the therapist to alleviate your stress │ │ Agent: A patient in therapy │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────── 📋 Task Started ────────────────────────────────────────────────╮ │ │ │ Task Started │ │ Name: Engage in a fruitful conversation with the patient to alleviate his stress │ │ ID: e261a44a-f317-4d03-ab8e-bca7f93d7bae │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─────────────────────────────────────────────── 🤖 Agent Started ────────────────────────────────────────────────╮ │ │ │ Agent: A therapist who meets patients │ │ │ │ Task: Engage in a fruitful conversation with the patient to alleviate his stress │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
[Finalize] todos_count=0, todos_with_results=0
╭───────────────────────────────────────────── ✅ Agent Final Answer ─────────────────────────────────────────────╮ │ │ │ Agent: A therapist who meets patients │ │ │ │ Final Answer: │ │ Therapist: Good afternoon. I’m glad you’re here today. You mentioned you’re experiencing stress due to poor │ │ work-life balance. Can you tell me a bit more about what’s been going on? │ │ │ │ Patient: Thank you for seeing me. Lately, I feel overwhelmed because work takes up most of my time and │ │ energy. I hardly have time to relax or spend with family and friends. It feels like I’m always working or │ │ worrying about work. │ │ │ │ Therapist: That sounds really tough. When did you first start noticing this imbalance in your life? │ │ │ │ Patient: I think it started a few months ago. My workload increased, and I started taking work home in the │ │ evenings. Weekends used to be free, but now I’m answering emails or finishing projects. It’s like the work │ │ never ends. │ │ │ │ Therapist: I see. How is this affecting other areas of your life, like your relationships, hobbies, or │ │ overall well-being? │ │ │ │ Patient: My relationships are definitely suffering. I’m often too tired to socialize or even call my friends │ │ and family. Hobbies have been neglected. I used to enjoy reading and going for walks, but now I feel too │ │ stressed or drained. Also, I’ve been feeling anxious and have trouble sleeping. │ │ │ │ Therapist: That must be really hard to cope with. When you think about why you’ve taken on so much work, what │ │ comes to mind? │ │ │ │ Patient: I guess I’m afraid of falling behind or disappointing my boss. There’s pressure to perform well, and │ │ I feel like if I don’t put in extra hours, I won’t be seen as a good employee. │ │ │ │ Therapist: It sounds like you’re carrying a lot of pressure and responsibility. Do you set any boundaries │ │ when it comes to work, like specific end times or breaks, or is it more flexible? │ │ │ │ Patient: Honestly, I don’t set firm boundaries. My work hours are flexible, which sounds good, but in │ │ practice, it means I’m working whenever I can. Sometimes I check emails late at night or during meals. │ │ │ │ Therapist: That flexibility can be a double-edged sword. Have you tried setting any limits on your work time │ │ or creating a routine to help separate work from personal time? │ │ │ │ Patient: I’ve thought about it but haven’t really put anything concrete in place. It’s hard because the │ │ workload can be unpredictable, and I worry that if I say no or stop early, things will pile up. │ │ │ │ Therapist: That fear is understandable. Let’s explore what small changes might feel manageable to you. For │ │ example, could you consider designating one hour after work as “no work” time just to rest or pursue │ │ something enjoyable? │ │ │ │ Patient: That might be doable. Maybe I could try to stop working by 7 pm and use that time to go for a walk │ │ or read. │ │ │ │ Therapist: That sounds like a positive step. How do you think you could communicate this boundary at work or │ │ to yourself so it feels more real? │ │ │ │ Patient: I could let my colleagues know that after 7 pm I won’t respond to emails unless it’s an emergency. I │ │ also need to remind myself that taking breaks won’t make me less productive in the long run. │ │ │ │ Therapist: It’s important to give yourself permission to rest. How do you feel about the idea of practicing │ │ mindfulness or relaxation techniques to manage stress more effectively? │ │ │ │ Patient: I’ve heard about mindfulness but haven’t tried it. I’m willing to give it a shot if it can help me │ │ stay calmer and more focused. │ │ │ │ Therapist: Great. I can guide you through some simple mindfulness exercises in our sessions. Also, how is │ │ your sleep? You mentioned trouble sleeping—what does your typical night look like? │ │ │ │ Patient: I often lie awake thinking about work or things I need to do. Sometimes I get only 4-5 hours of │ │ sleep. When I’m tired, I’m even less motivated to relax or do self-care. │ │ │ │ Therapist: Sleep difficulties can increase stress and reduce overall functioning. We can look at improving │ │ your sleep hygiene and strategies to calm your mind before bed. Are you open to that? │ │ │ │ Patient: Yes, definitely. I want to feel more rested. │ │ │ │ Therapist: That’s a good goal. When you think about your ideal work-life balance, what would it look like? │ │ │ │ Patient: I’d like to have regular work hours and be able to fully disconnect after work. I want time for │ │ hobbies, socializing, and taking care of myself. Feeling less anxious and more in control would be amazing. │ │ │ │ Therapist: Those are realistic and healthy goals. Let’s work on creating a gradual plan to move towards that │ │ balance. What do you think might get in the way, and how can we address those challenges? │ │ │ │ Patient: The main challenge is my own expectations and fear of falling behind. Also, workplace culture │ │ sometimes rewards overworking. I guess I need support in changing my mindset and communicating boundaries. │ │ │ │ Therapist: That’s very insightful. We can work on building your assertiveness and coping skills to handle │ │ these pressures. Would it feel useful to explore any past experiences or beliefs contributing to these fears? │ │ │ │ Patient: Yes, I think I’ve always felt that I have to prove myself, especially at work. I’m afraid that if I │ │ don’t keep up, I might lose what I’ve earned. │ │ │ │ Therapist: Understanding these core beliefs can help us reshape them. For now, let’s focus on practical steps │ │ you can take this week to create space for yourself. Can you identify one or two small changes to start with? │ │ │ │ Patient: I’ll try setting a 7 pm cutoff for work and dedicate 30 minutes to a relaxing activity before bed. │ │ Also, I’ll write down my worries before going to sleep to clear my mind. │ │ │ │ Therapist: Excellent. We’ll check in on how these changes go next time. Remember, progress can be gradual. │ │ How do you feel after discussing all this today? │ │ │ │ Patient: I feel hopeful. It’s good to have a plan and realize I’m not alone in this. Talking about it helps. │ │ │ │ Therapist: I’m glad to hear that. You’re doing important work for your wellbeing. We’ll continue working │ │ together to support you. Is there anything else you want to address before we wrap up today? │ │ │ │ Patient: No, this covers it. Thank you. │ │ │ │ Therapist: You’re very welcome. Take care, and I look forward to seeing you at our next session. │ │ │ │ Patient: Thanks. See you then. │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────────────────── 📋 Task Completion ───────────────────────────────────────────────╮ │ │ │ Task Completed │ │ Name: Engage in a fruitful conversation with the patient to alleviate his stress │ │ Agent: A therapist who meets patients │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
text = result.raw.replace("**", "\n\n")
p80(text)
Therapist: Good afternoon. I’m glad you’re here today. You mentioned you’re
experiencing stress due to poor work-life balance. Can you tell me a bit more
about what’s been going on? Patient: Thank you for seeing me. Lately, I feel
overwhelmed because work takes up most of my time and energy. I hardly have time
to relax or spend with family and friends. It feels like I’m always working or
worrying about work. Therapist: That sounds really tough. When did you first
start noticing this imbalance in your life? Patient: I think it started a few
months ago. My workload increased, and I started taking work home in the
evenings. Weekends used to be free, but now I’m answering emails or finishing
projects. It’s like the work never ends. Therapist: I see. How is this
affecting other areas of your life, like your relationships, hobbies, or overall
well-being? Patient: My relationships are definitely suffering. I’m often too
tired to socialize or even call my friends and family. Hobbies have been
neglected. I used to enjoy reading and going for walks, but now I feel too
stressed or drained. Also, I’ve been feeling anxious and have trouble sleeping.
Therapist: That must be really hard to cope with. When you think about why
you’ve taken on so much work, what comes to mind? Patient: I guess I’m afraid
of falling behind or disappointing my boss. There’s pressure to perform well,
and I feel like if I don’t put in extra hours, I won’t be seen as a good
employee. Therapist: It sounds like you’re carrying a lot of pressure and
responsibility. Do you set any boundaries when it comes to work, like specific
end times or breaks, or is it more flexible? Patient: Honestly, I don’t set
firm boundaries. My work hours are flexible, which sounds good, but in practice,
it means I’m working whenever I can. Sometimes I check emails late at night or
during meals. Therapist: That flexibility can be a double-edged sword. Have you
tried setting any limits on your work time or creating a routine to help
separate work from personal time? Patient: I’ve thought about it but haven’t
really put anything concrete in place. It’s hard because the workload can be
unpredictable, and I worry that if I say no or stop early, things will pile up.
Therapist: That fear is understandable. Let’s explore what small changes might
feel manageable to you. For example, could you consider designating one hour
after work as “no work” time just to rest or pursue something enjoyable?
Patient: That might be doable. Maybe I could try to stop working by 7 pm and use
that time to go for a walk or read. Therapist: That sounds like a positive
step. How do you think you could communicate this boundary at work or to
yourself so it feels more real? Patient: I could let my colleagues know that
after 7 pm I won’t respond to emails unless it’s an emergency. I also need to
remind myself that taking breaks won’t make me less productive in the long run.
Therapist: It’s important to give yourself permission to rest. How do you feel
about the idea of practicing mindfulness or relaxation techniques to manage
stress more effectively? Patient: I’ve heard about mindfulness but haven’t
tried it. I’m willing to give it a shot if it can help me stay calmer and more
focused. Therapist: Great. I can guide you through some simple mindfulness
exercises in our sessions. Also, how is your sleep? You mentioned trouble
sleeping—what does your typical night look like? Patient: I often lie awake
thinking about work or things I need to do. Sometimes I get only 4-5 hours of
sleep. When I’m tired, I’m even less motivated to relax or do self-care.
Therapist: Sleep difficulties can increase stress and reduce overall
functioning. We can look at improving your sleep hygiene and strategies to calm
your mind before bed. Are you open to that? Patient: Yes, definitely. I want to
feel more rested. Therapist: That’s a good goal. When you think about your
ideal work-life balance, what would it look like? Patient: I’d like to have
regular work hours and be able to fully disconnect after work. I want time for
hobbies, socializing, and taking care of myself. Feeling less anxious and more
in control would be amazing. Therapist: Those are realistic and healthy goals.
Let’s work on creating a gradual plan to move towards that balance. What do you
think might get in the way, and how can we address those challenges? Patient:
The main challenge is my own expectations and fear of falling behind. Also,
workplace culture sometimes rewards overworking. I guess I need support in
changing my mindset and communicating boundaries. Therapist: That’s very
insightful. We can work on building your assertiveness and coping skills to
handle these pressures. Would it feel useful to explore any past experiences or
beliefs contributing to these fears? Patient: Yes, I think I’ve always felt
that I have to prove myself, especially at work. I’m afraid that if I don’t keep
up, I might lose what I’ve earned. Therapist: Understanding these core beliefs
can help us reshape them. For now, let’s focus on practical steps you can take
this week to create space for yourself. Can you identify one or two small
changes to start with? Patient: I’ll try setting a 7 pm cutoff for work and
dedicate 30 minutes to a relaxing activity before bed. Also, I’ll write down my
worries before going to sleep to clear my mind. Therapist: Excellent. We’ll
check in on how these changes go next time. Remember, progress can be gradual.
How do you feel after discussing all this today? Patient: I feel hopeful. It’s
good to have a plan and realize I’m not alone in this. Talking about it helps.
Therapist: I’m glad to hear that. You’re doing important work for your
wellbeing. We’ll continue working together to support you. Is there anything
else you want to address before we wrap up today? Patient: No, this covers it.
Thank you. Therapist: You’re very welcome. Take care, and I look forward to
seeing you at our next session. Patient: Thanks. See you then.
╭──────────────────────────────────────────────── Crew Completion ────────────────────────────────────────────────╮ │ │ │ Crew Execution Completed │ │ Name: crew │ │ ID: 062c8a4f-472e-4614-a352-f9213b2d4977 │ │ Final Output: Therapist: Good afternoon. I’m glad you’re here today. You mentioned you’re experiencing stress │ │ due to poor work-life balance. Can you tell me a bit more about what’s been going on? │ │ │ │ Patient: Thank you for seeing me. Lately, I feel overwhelmed because work takes up most of my time and │ │ energy. I hardly have time to relax or spend with family and friends. It feels like I’m always working or │ │ worrying about work. │ │ │ │ Therapist: That sounds really tough. When did you first start noticing this imbalance in your life? │ │ │ │ Patient: I think it started a few months ago. My workload increased, and I started taking work home in the │ │ evenings. Weekends used to be free, but now I’m answering emails or finishing projects. It’s like the work │ │ never ends. │ │ │ │ Therapist: I see. How is this affecting other areas of your life, like your relationships, hobbies, or │ │ overall well-being? │ │ │ │ Patient: My relationships are definitely suffering. I’m often too tired to socialize or even call my friends │ │ and family. Hobbies have been neglected. I used to enjoy reading and going for walks, but now I feel too │ │ stressed or drained. Also, I’ve been feeling anxious and have trouble sleeping. │ │ │ │ Therapist: That must be really hard to cope with. When you think about why you’ve taken on so much work, what │ │ comes to mind? │ │ │ │ Patient: I guess I’m afraid of falling behind or disappointing my boss. There’s pressure to perform well, and │ │ I feel like if I don’t put in extra hours, I won’t be seen as a good employee. │ │ │ │ Therapist: It sounds like you’re carrying a lot of pressure and responsibility. Do you set any boundaries │ │ when it comes to work, like specific end times or breaks, or is it more flexible? │ │ │ │ Patient: Honestly, I don’t set firm boundaries. My work hours are flexible, which sounds good, but in │ │ practice, it means I’m working whenever I can. Sometimes I check emails late at night or during meals. │ │ │ │ Therapist: That flexibility can be a double-edged sword. Have you tried setting any limits on your work time │ │ or creating a routine to help separate work from personal time? │ │ │ │ Patient: I’ve thought about it but haven’t really put anything concrete in place. It’s hard because the │ │ workload can be unpredictable, and I worry that if I say no or stop early, things will pile up. │ │ │ │ Therapist: That fear is understandable. Let’s explore what small changes might feel manageable to you. For │ │ example, could you consider designating one hour after work as “no work” time just to rest or pursue │ │ something enjoyable? │ │ │ │ Patient: That might be doable. Maybe I could try to stop working by 7 pm and use that time to go for a walk │ │ or read. │ │ │ │ Therapist: That sounds like a positive step. How do you think you could communicate this boundary at work or │ │ to yourself so it feels more real? │ │ │ │ Patient: I could let my colleagues know that after 7 pm I won’t respond to emails unless it’s an emergency. I │ │ also need to remind myself that taking breaks won’t make me less productive in the long run. │ │ │ │ Therapist: It’s important to give yourself permission to rest. How do you feel about the idea of practicing │ │ mindfulness or relaxation techniques to manage stress more effectively? │ │ │ │ Patient: I’ve heard about mindfulness but haven’t tried it. I’m willing to give it a shot if it can help me │ │ stay calmer and more focused. │ │ │ │ Therapist: Great. I can guide you through some simple mindfulness exercises in our sessions. Also, how is │ │ your sleep? You mentioned trouble sleeping—what does your typical night look like? │ │ │ │ Patient: I often lie awake thinking about work or things I need to do. Sometimes I get only 4-5 hours of │ │ sleep. When I’m tired, I’m even less motivated to relax or do self-care. │ │ │ │ Therapist: Sleep difficulties can increase stress and reduce overall functioning. We can look at improving │ │ your sleep hygiene and strategies to calm your mind before bed. Are you open to that? │ │ │ │ Patient: Yes, definitely. I want to feel more rested. │ │ │ │ Therapist: That’s a good goal. When you think about your ideal work-life balance, what would it look like? │ │ │ │ Patient: I’d like to have regular work hours and be able to fully disconnect after work. I want time for │ │ hobbies, socializing, and taking care of myself. Feeling less anxious and more in control would be amazing. │ │ │ │ Therapist: Those are realistic and healthy goals. Let’s work on creating a gradual plan to move towards that │ │ balance. What do you think might get in the way, and how can we address those challenges? │ │ │ │ Patient: The main challenge is my own expectations and fear of falling behind. Also, workplace culture │ │ sometimes rewards overworking. I guess I need support in changing my mindset and communicating boundaries. │ │ │ │ Therapist: That’s very insightful. We can work on building your assertiveness and coping skills to handle │ │ these pressures. Would it feel useful to explore any past experiences or beliefs contributing to these fears? │ │ │ │ Patient: Yes, I think I’ve always felt that I have to prove myself, especially at work. I’m afraid that if I │ │ don’t keep up, I might lose what I’ve earned. │ │ │ │ Therapist: Understanding these core beliefs can help us reshape them. For now, let’s focus on practical steps │ │ you can take this week to create space for yourself. Can you identify one or two small changes to start with? │ │ │ │ Patient: I’ll try setting a 7 pm cutoff for work and dedicate 30 minutes to a relaxing activity before bed. │ │ Also, I’ll write down my worries before going to sleep to clear my mind. │ │ │ │ Therapist: Excellent. We’ll check in on how these changes go next time. Remember, progress can be gradual. │ │ How do you feel after discussing all this today? │ │ │ │ Patient: I feel hopeful. It’s good to have a plan and realize I’m not alone in this. Talking about it helps. │ │ │ │ Therapist: I’m glad to hear that. You’re doing important work for your wellbeing. We’ll continue working │ │ together to support you. Is there anything else you want to address before we wrap up today? │ │ │ │ Patient: No, this covers it. Thank you. │ │ │ │ Therapist: You’re very welcome. Take care, and I look forward to seeing you at our next session. │ │ │ │ Patient: Thanks. See you then. │ │ │ │ │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
40.8. Agno#
https://docs.agno.com/introduction
We use and modify some of the examples provided in the documentation to get started.
Side note: In numerology, the name Agno is associated with qualities like intellectual prowess, planning, and spiritual seeking. https://www.sevenreflections.com/name-numerology/agno/
!pip install --upgrade agno
!pip install --upgrade mcp
╭────────────────────────── Tracing Preference Saved ──────────────────────────╮
│ │
│ Info: Tracing has been disabled. │
│ │
│ Your preference has been saved. Future Crew/Flow executions will not │
│ collect traces. │
│ │
│ To enable tracing later, do any one of these: │
│ • Set tracing=True in your Crew/Flow code │
│ • Set CREWAI_TRACING_ENABLED=true in your project's .env file │
│ • Run: crewai traces enable │
│ │
╰──────────────────────────────────────────────────────────────────────────────╯
Collecting agno
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?25hInstalling collected packages: agnoctl, agno
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?25hInstalling collected packages: mcp
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%run keys.ipynb
We now test Agno, and do not give it access to a search tool, so it returns outdated information.
# Test installation
from agno.agent import Agent
from agno.models.openai import OpenAIChat
agent = Agent(
model=OpenAIChat(id="gpt-4.1"),
description="You are an enthusiastic news reporter with a flair for storytelling!",
markdown=True
)
agent.print_response("Tell me about a breaking news story from New York.", stream=True)
Now, let’s add in the search tool recommended by Agno. For a list of tools in Agno, see: https://docs.agno.com/tools/introduction
!pip install lancedb tantivy pypdf duckduckgo-search yfinance ddgs
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from agno.tools.duckduckgo import DuckDuckGoTools
agent = Agent(
model=OpenAIChat(id="gpt-4.1"),
description="You are an enthusiastic news reporter with a flair for storytelling!",
tools=[DuckDuckGoTools()],
# show_tool_calls=True,
markdown=True
)
agent.print_response("Tell me about a breaking news story from New York.", stream=True)
40.9. Multi-agent workflows – An Intelligent Financial Assistant#
Here’s an example from the documentation.
!pip install -U yfinance
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?25hInstalling collected packages: yfinance
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from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from agno.team import Team
web_agent = Agent(
name="Web Agent",
role="Search the web for information",
model=OpenAIChat(id="gpt-4.1"),
tools=[DuckDuckGoTools()],
instructions="Always include sources",
# show_tool_calls=True,
markdown=True,
)
finance_agent = Agent(
name="Finance Agent",
role="Get financial data",
model=OpenAIChat(id="gpt-4.1"),
# tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
tools=[YFinanceTools()],
instructions="Use tables to display data",
# show_tool_calls=True,
markdown=True,
)
agent_team = Team(
# mode="coordinate",
members=[web_agent, finance_agent],
model=OpenAIChat(id="gpt-4.1"),
# success_criteria="A comprehensive financial news report with clear sections and data-driven insights.",
instructions=["Always include sources", "Use tables to display data"],
# show_tool_calls=True,
markdown=True,
)
agent_team.print_response("What's the market outlook and financial performance of AI semiconductor companies?", stream=True)
WARNING Could not run function web_search(query=...): No results found.
ERROR No results found. Traceback (most recent call last): File "/usr/local/lib/python3.12/dist-packages/agno/tools/function.py", line 1087, in execute result = self.function.entrypoint(**entrypoint_args, **self.arguments) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 39, in wrapper_function return wrapper(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 136, in __call__ res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args, kwargs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/agno/tools/websearch.py", line 98, in web_search results = ddgs.text(**search_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 458, in text return self._search_sync("text", query, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 454, in _search_sync raise DDGSException(err or "No results found.") ddgs.exceptions.DDGSException: No results found.
WARNING Could not run function search_news(query=..., max_results=5): No results found.
ERROR No results found. Traceback (most recent call last): File "/usr/local/lib/python3.12/dist-packages/agno/tools/function.py", line 1087, in execute result = self.function.entrypoint(**entrypoint_args, **self.arguments) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 39, in wrapper_function return wrapper(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 136, in __call__ res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args, kwargs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/agno/tools/websearch.py", line 125, in search_news results = ddgs.news(**search_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 466, in news return self._search_sync("news", query, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 454, in _search_sync raise DDGSException(err or "No results found.") ddgs.exceptions.DDGSException: No results found.
WARNING Could not run function web_search(query=...): No results found.
ERROR No results found. Traceback (most recent call last): File "/usr/local/lib/python3.12/dist-packages/agno/tools/function.py", line 1087, in execute result = self.function.entrypoint(**entrypoint_args, **self.arguments) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 39, in wrapper_function return wrapper(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/pydantic/_internal/_validate_call.py", line 136, in __call__ res = self.__pydantic_validator__.validate_python(pydantic_core.ArgsKwargs(args, kwargs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/agno/tools/websearch.py", line 98, in web_search results = ddgs.text(**search_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 458, in text return self._search_sync("text", query, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/dist-packages/ddgs/ddgs.py", line 454, in _search_sync raise DDGSException(err or "No results found.") ddgs.exceptions.DDGSException: No results found.
40.10. Forecasting the market outlook#
res = agent_team.print_response("Summarize the earnings call for Amazon Q1 2026", stream=True)
res
agent_team.print_response("What's the market outlook for the S&P 500 as of the end of 2026", stream=True)
40.11. Using Ollama in Colab for stock outlooks#
The same is also possible with Ollama and many other providers listed here: https://docs.agno.com/models/introduction.
Using this in Jupyter on your laptop is easy but in Colab we need a few more steps as noted here: https://srdas.github.io/NLPBook/NLTK_moreTextHandling_EntityExtraction.html
This is extremely slow in Colab and may not complete.
!pip install colab-xterm
%load_ext colabxterm
Next, you can launch the terminal with the magic command %xterm.
Then, download and install Ollama with the following terminal commands:
curl https://ollama.ai/install.sh | sh
Start the Ollama server:
ollama serve &
(Hit Enter twice to make sure it has given back the terminal.)
Kick off llama3.2:
ollama run llama3.2
%xterm
!pip install ollama
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from agno.tools.yfinance import YFinanceTools
from agno.team import Team
from agno.models.ollama import Ollama
web_agent = Agent(
name="Web Agent",
role="Search the web for information",
model=Ollama(id="llama3.2"),
tools=[DuckDuckGoTools()],
instructions="Always include sources",
show_tool_calls=True,
markdown=True,
)
finance_agent = Agent(
name="Finance Agent",
role="Get financial data",
model=Ollama(id="llama3.2"),
tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
instructions="Use tables to display data",
show_tool_calls=True,
markdown=True,
)
agent_team = Team(
mode="coordinate",
members=[web_agent, finance_agent],
model=Ollama(id="llama3.2"),
success_criteria="A comprehensive financial news report with clear sections and data-driven insights.",
instructions=["Always include sources", "Use tables to display data"],
show_tool_calls=True,
markdown=True,
)
agent_team.print_response("What's the market outlook for NVIDIA in 2025?", stream=True)
40.12. What next?#
Where is this going? How do we think about agents and humans? See an interesting thought piece by Michael Kearns titled “Scientific Frontiers of Agentic AI.”