@LangChain: Model. Harness. Context. The 3 main components of agents. As you build more agents, context increasingly lives AGENTS.m…

X AI KOLs Following Tools

Summary

LangChain announces LangSmith Context Hub, a centralized place for managing agent context including AGENTS.md, skills, policies, and research files.

Model. Harness. Context. The 3 main components of agents. As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files. Context needs its own home. That’s why we built LangSmith Context Hub. https://t.co/OLr85Nh27n
Original Article
View Cached Full Text

Cached at: 05/15/26, 02:57 AM

Model. Harness. Context.

The 3 main components of agents.

As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files.

Context needs its own home. That’s why we built LangSmith Context Hub. https://t.co/OLr85Nh27n

Similar Articles

[N] LangChain Interrupt 2026 announcements [N]

Reddit r/MachineLearning

LangChain announced SmithDB, a distributed database for agent observability, Context Hub for managing agent context with an open memory standard, and Deep Agents v0.6 at Interrupt 2026, alongside enterprise case studies and keynotes by Andrew Ng and Harrison Chase.

@LangChain: Everything you need to know about Managed Deep Agents:

X AI KOLs Timeline

LangChain announces Managed Deep Agents in private beta, a hosted API-first runtime for building, running, and operating deep agents in production, leveraging the open-source Deep Agents harness and integrating with LangSmith for durable execution, streaming, and human-in-the-loop workflows.

Give your agent its own computer (7 minute read)

TLDR AI

LangChain introduces LangSmith Sandboxes, providing each AI agent with its own isolated computer environment for safe code execution, addressing security risks of running untrusted code in containers or locally.