thats a good idea, cc @bentannyhill we should probably make it possible to bring your own mcp server?
@hwchase17
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Troubleshooting and Monitoring AI Agents
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Not exactly. It looks at your agents running and tries to identify what’s going wrong
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LangChain introduces SmithDB and LangSmith Engine for agent observability
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which was your favorite launch? SmithDB (database purpose built for agent trace data): https://
langchain.com/blog/introduci
ng-smithdb
… LangSmith Engine (agent for improving your agents based on trace data): https://
langchain.com/blog/introduci
ng-langsmith-engine
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AI engine convergence through action memory
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Engine has knowledge of previous actions, so should converge
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Launch of LangSmith Engine for AI Agent Trace Monitoring
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🚀Launching: LangSmith Engine
— Harrison Chase (@hwchase17) 13 mai 2026
LangSmith Engine is an agent that sits on top of your traces
It runs in the background and automatically identifies issues
It then proactively suggests action items (code changes, evaluators to add)
Try it today: https://t.co/f2ZRkogGGS pic.twitter.com/R1e2B69jdRLaunching: LangSmith Engine LangSmith Engine is an agent that sits on top of your traces It runs in the background and automatically identifies issues It then proactively suggests action items (code changes, evaluators to add) Try it today: http://
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Using LangSmith for Organizational AI Agent Collaboration
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one way to view langsmith is as a platform for the whole org to collaborate on building agents helps speed up that feedback loop between different personas
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Managing AI Agents as Iterative Systems and Team Dynamics
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viv always says it better than me lots of talk recently of thinking of agents as systems to measure and iteratively improve but – thats not JUST a technical thing. its also a human & team thing
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Governance requirements for multi-agent AI systems
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and when you do it with 100 diff agents you need some organizational governance