a hot (cold at this point?) take that lead us to build this: every agent in the future will need a sandbox to connect to writing/executing code is not just for coding agents! is useful for all sorts of tasks
@hwchase17
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Managed Deep Agents for Long Horizon Deployment
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Managed deep agents is the easiest way to build and deploy long horizon agents Private preview, dm me if you want access
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Fleet Agents Now Execute Code for General Tasks
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Fleet agents now come with a computer! They can write and execute code, which is helpful for general purpose tasks beyond coding
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Context Hub Launched for AI Agent Context Management
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We launched Context Hub as a way to manage skills, AGENTS.md files, and other context files an agent might need You can easily use it as a virtual filesystem in deepagents See this video for more info!
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Benefits of Lightweight Code Interpreter Environments for AI Development
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code interpreter is a light weight code execution environment lets you do:
– RLMs
– programmatic tool calling
– more! without having to spin up a full sandbox we'll be writing a lot more about the use cases here, but check it out! -
Technical deep dive into the architecture of LangSmith Engine
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great deep dive into how we built LangSmith Engine lots of fun learnings and tips and tricks
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Job opportunity in continual learning research
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Jake will be working with a lot of folks on continual learning – if that’s interesting, reach out to him!
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Integrating LangSmith and OTEL for AI application observability
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right now Engine only works with LangSmith traces but it's super easy to trace to LangSmith, we accept OTEL and integrate with 30+ frameworks! if you want to migrate to LangSmith to try out Engine, we will help as well!
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Decoupling AI Trace Observability from LangChain Ecosystem
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right now its tightly coupled to LangSmith traces, but not to the rest of the LangChain ecosystem eg you can use this on claude code traces, crewai traces, any traces!
