1/11
@LangChainAI
We asked, you answered — our State of AI Agents Report is here!
We surveyed 1300+ industry professionals, from developers to business leaders, on how they're using AI agents today — and the results are in.
What are the top use cases for agents? The biggest challenges when building agents? And who's finding success after deploying their agents to production?
Read the full report LangChain State of AI Agents Report
Here's 5 key insights in the thread below
https://video.twimg.com/ext_tw_video/1857116336973094912/pu/vid/avc1/1218x720/UNMhyAcjOZ95AEuw.mp4
2/11
@LangChainAI
1⃣ Agent adoption is a coin toss, but nearly everyone has plans for it.
About 50% of respondents have agents in production, with mid-sized companies leading the charge. That number is poised to grow, with 78% planning to implement AI agents soon.
3/11
@LangChainAI
2⃣ Research and summarization is the leading agent use case among respondents (at 58%), followed by personal assistance / productivity (54%) and customer service (46%).
AI agents are taking over time-consuming tasks—whether it’s more repetitive tasks for productivity, or handling complex information retrieval and data analysis.
4/11
@LangChainAI
3⃣ Tracing (observability) and human oversight are crucial to keeping agents in check.
Many companies, especially enterprises, favor read-only permissions for their agents and add in extra controls -- including offline evaluation to catch issues before shipping to production.
5/11
@LangChainAI
4⃣ Performance quality is THE major hurdle to deploying agents in production.
Reliability matters — and for many companies, the unpredictability of agent outputs and poor response quality are primary concerns.
6/11
@LangChainAI
5⃣ Agent success stories: The spotlight's on Cursor, Perplexity, and Replit
Companies like @cursor_ai, @perplexity_ai, and @Replit are fan favorites, redefining productivity with AI agents — from code generation to advanced query search.
7/11
@LangChainAI
Curious about the full picture? Check out the full State of AI Agents Report here: LangChain State of AI Agents Report
8/11
@DavidFSWD
what about a discussion about defining "agents"? You just asked a bunch of people if they use "Agents", but there is no qualification for what that means. (first question)
because Agent is a buzzword that doesn't mean anything
9/11
@LangChainAI
Great question! We have a blog discussing the definition of an agent and what it means to be agentic:
What is an AI agent?
10/11
@AIAgentNews
Awesome! Definitely getting featured in this week’s issue
11/11
@nisyron
It's very interesting to not see a discussion about agents for customer support and sales. Is that because there aren't many?
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196
@LangChainAI
We asked, you answered — our State of AI Agents Report is here!
We surveyed 1300+ industry professionals, from developers to business leaders, on how they're using AI agents today — and the results are in.
What are the top use cases for agents? The biggest challenges when building agents? And who's finding success after deploying their agents to production?
Read the full report LangChain State of AI Agents Report
Here's 5 key insights in the thread below
https://video.twimg.com/ext_tw_video/1857116336973094912/pu/vid/avc1/1218x720/UNMhyAcjOZ95AEuw.mp4
2/11
@LangChainAI
1⃣ Agent adoption is a coin toss, but nearly everyone has plans for it.
About 50% of respondents have agents in production, with mid-sized companies leading the charge. That number is poised to grow, with 78% planning to implement AI agents soon.
3/11
@LangChainAI
2⃣ Research and summarization is the leading agent use case among respondents (at 58%), followed by personal assistance / productivity (54%) and customer service (46%).
AI agents are taking over time-consuming tasks—whether it’s more repetitive tasks for productivity, or handling complex information retrieval and data analysis.
4/11
@LangChainAI
3⃣ Tracing (observability) and human oversight are crucial to keeping agents in check.
Many companies, especially enterprises, favor read-only permissions for their agents and add in extra controls -- including offline evaluation to catch issues before shipping to production.
5/11
@LangChainAI
4⃣ Performance quality is THE major hurdle to deploying agents in production.
Reliability matters — and for many companies, the unpredictability of agent outputs and poor response quality are primary concerns.
6/11
@LangChainAI
5⃣ Agent success stories: The spotlight's on Cursor, Perplexity, and Replit
Companies like @cursor_ai, @perplexity_ai, and @Replit are fan favorites, redefining productivity with AI agents — from code generation to advanced query search.
7/11
@LangChainAI
Curious about the full picture? Check out the full State of AI Agents Report here: LangChain State of AI Agents Report
8/11
@DavidFSWD
what about a discussion about defining "agents"? You just asked a bunch of people if they use "Agents", but there is no qualification for what that means. (first question)
because Agent is a buzzword that doesn't mean anything
9/11
@LangChainAI
Great question! We have a blog discussing the definition of an agent and what it means to be agentic:
What is an AI agent?
10/11
@AIAgentNews
Awesome! Definitely getting featured in this week’s issue
11/11
@nisyron
It's very interesting to not see a discussion about agents for customer support and sales. Is that because there aren't many?
To post tweets in this format, more info here: https://www.thecoli.com/threads/tips-and-tricks-for-posting-the-coli-megathread.984734/post-52211196