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We’re launching LangSmith Fleet today!  There are some primitives in Fleet that I think will be very useful in a future where agents do a lot of the world’s work

- Agent Identity: 
as more work is specified by humans but done by agents, we need identity + security models that reflect that.  This means attaching credentials and connections specifically to agents that control what they can read/write and what surface areas they interact with (github, slack, etc)

- Agent Self-Improvement:
There’s more agents that we’ll use over week, month, year time-scales.  Memory and the ability for agents to edit themselves means agents mold to your tasks over use.  Because they’re hooked up to LangSmith, this also lets your team generate evals to ground your changes in metrics over time.

- Integrate with the World:
It’s kinda funny how hard (edge cases!!) it is to connect agents to external tools like Slack and GitHub.  Part of it is auth but part is good context engineering to help agents actually use the connections to do useful work.  Context engineering around external systems is tricky, Fleet does a lot to help with that process!

- Sharing Agents:
Memory + Shared surfaces of access means that agents improve over time with your team but also a useful agent built by one team is immediately helpful to other orgs!  Coding Agents are work engines and helpful to marketing as much as engineering

- Harness Engineering
Agents need to adapt their tooling, prompts, memory to the task at hand.  All of this is adapting the agent harness for the work.  Now agents help you help them.  Fleet is a tool for using agents but also building the harness around agents to make them great at the work you want to do.  A lot of products exist by making this loop tailored to specific tasks

Excited to see people try this, more agents to build and more work to do 🫡

<p>We’re launching LangSmith Fleet today!  There are some primitives in Fleet that I think will be very useful in a future where agents do a lot of the world’s work

- Agent Identity: 
as more work is specified by humans but done by agents, we need identity + security models that reflect that.  This means attaching credentials and connections specifically to agents that control what they can read/write and what surface areas they interact with (github, slack, etc)

- Agent Self-Improvement:
There’s more agents that we’ll use over week, month, year time-scales.  Memory and the ability for agents to edit themselves means agents mold to your tasks over use.  Because they’re hooked up to LangSmith, this also lets your team generate evals to ground your changes in metrics over time.

- Integrate with the World:
It’s kinda funny how hard (edge cases!!) it is to connect agents to external tools like Slack and GitHub.  Part of it is auth but part is good context engineering to help agents actually use the connections to do useful work.  Context engineering around external systems is tricky, Fleet does a lot to help with that process!

- Sharing Agents:
Memory + Shared surfaces of access means that agents improve over time with your team but also a useful agent built by one team is immediately helpful to other orgs!  Coding Agents are work engines and helpful to marketing as much as engineering

- Harness Engineering
Agents need to adapt their tooling, prompts, memory to the task at hand.  All of this is adapting the agent harness for the work.  Now agents help you help them.  Fleet is a tool for using agents but also building the harness around agents to make them great at the work you want to do.  A lot of products exist by making this loop tailored to specific tasks

Excited to see people try this, more agents to build and more work to do 🫡</p>

Harrison Chase

LangSmith Fleet has been launched. Fleet introduces new primitives aimed at supporting future AI-driven workflows, though details in this post are limited to a brief announcement tweet.