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🚀 Announcing LangSmith Skills + CLI 🚀 Agent improvements are increasingly driven by coding agents themselves. We're releasing LangSmith Skills alongside the LangSmith CLI to make coding agents experts at the agent engineering lifecycle. LangSmith Skills enable agents to debug traces, create datasets, and run experiments - and thanks... show more

LangChain

268,259 subscribers

49,662 次观看 • 7 个月前 •via X (Twitter)

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12 条评论

WildPinesAI 的头像

WildPinesAI7 个月前

@hwchase17 piping LangSmith traces directly into your coding agent so it debugs your other agents — agents improving agents is a literal workflow now. CLI-first was the right call

Sadi Moodi 的头像

Sadi Moodi7 个月前

This is the future of agent engineering. Key insight: when agents can debug their own traces via CLI, you get compounding improvements. My checklist for agentic workflows: 1) instrument every step with trace IDs, 2) build feedback loops where agents learn from failed runs, 3) keep agents in terminal where they're most productive. The 50% VRAM reduction from Unsloth + LangSmith = serious edge deployment potential.

Samuel Ekpe 的头像

Samuel Ekpe7 个月前

Nice

danfiru 的头像

danfiru7 个月前

the toolchain is eating itself. agents improving agents. the question is whether this feedback loop converges on better software or just more software. best stacks will be the ones that know when to stop generating.

Verivus Open Source 的头像

Verivus Open Source7 个月前

check out to get sqry, ships as an MCP server (33 tools). Claude Code, Codex, Gemini can query the actual call graph instead of guessing. make @LangChain smarter.

Prakhar Khatri 的头像

Prakhar Khatri7 个月前

Gonna try it Looks good

lakshya 的头像

lakshya7 个月前

Thank you! I was making do with the locally hosted MCP server and it was quite finicky.

anil kalm 的头像

anil kalm7 个月前

Agents improving agents via traces + CLI feels like the toolchain finally eating itself in the best way. One thing I'm wondering: how are you all thinking about stopping conditions or 'convergence' in these self-improvement loops so it doesn't just keep generating more code forever?

Vikas Kumar | Agent Engineer 的头像

Vikas Kumar | Agent Engineer7 个月前

We're getting closer to agents running the full engineering loop: build → debug → eval → improve.

Chris Ruppelt 的头像

Chris Ruppelt7 个月前

Awesome, would be cool to get some example usages. How do i get claude code running to fix a specific langgraph call given the langsmith run/trace id?

VibeCodes 的头像

VibeCodes7 个月前

Agents improving their own traces via CLI is a huge step. Self-improving workflows > one-shot execution. We're building on this vision at @getvibecodes — AI agents as persistent team members across the full dev lifecycle. LangSmith Skills makes the ecosystem stronger for everyone.

tommyt 的头像

tommyt7 个月前

The AI slop replies on langchain X posts are unbearable

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19,847 次观看 • 5 个月前

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