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How To Build a Self-Improving Agent with LangSmith Engine and Context Hub
Building Frontier CX Agents | Interrupt 26
The Future of AI Agents: What Will Interrupt 2027 Look Like | Interrupt 26
Agents in the Enterprise with MongoDB | Interrupt 26
The Agent Development Lifecycle: Build, Test, Deploy, Monitor | Interrupt 26
Introducing LangSmith Engine
Interrupt 26: The Agent Conference by LangChain
Why We Built LangSmith for Improving Agent Quality
Make Legal Write Your Evals: Building Jade, Chime’s Financial Copilot | Interrupt 26
The Future of AI Agents with Andrew Ng | Interrupt 26
Getting Evals Right for LLM Applications | Interrupt 26
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Last Updated: September 6, 2026
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Summary
Until now, improving your agent has been a manual process of reading traces, looking for patterns, writing evals, and creating ... Nick Ung, ML lead for safety and customer care at Lyft, breaks down how his team Most agents don't learn from their mistakes, they just leave traces. Jake Broekhuizen walks through how to close that loop using ... Harrison Chase, Brace Sproul, and Caroline di Vittorio kicked off Day 2 of Harrison Chase sits down with CJ Desai, CEO of MongoDB, for a fireside chat at Most teams building agents today have traces. What they don't have is a clear answer to the question that actually matters: how ... Harrison Chase (CEO of LangChain) sits down with Bagatur ( Philipp Comans, software engineer at Chime, explains how his team Andrew Ng sat down with Harrison Chase for a wide-ranging fireside chat at Shreya Shankar and Hamel Husain have taught evals to over 4500 people across dozens of companies, and they keep seeing ...
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