Happening today! https://
events.langchain.com/webinar/the-ag
ent-development-lifecycle-101/
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@langchain
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Langchain webinar on Agent Development Lifecycle 101 today
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Insights from running 350M GTM agents: caching, bounding, fairness
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At Interrupt, @Clay's Head of AI @jeffbarg shared insights from running 350m GTM agents a month.
— LangChain (@LangChain) 24 juin 2026
✅ Caching can cut LLM costs up to 70%
✅ Bounding tool calls often improves quality, not just cost
✅ Fairness queues matter once you have real multi-tenant load
Worth 12 minutes if… pic.twitter.com/2qbvyct3lxAt Interrupt, @Clay
's Head of AI @jeffbarg shared insights from running 350m GTM agents a month. Caching can cut LLM costs up to 70% Bounding tool calls often improves quality, not just cost Fairness queues matter once you have real multi-tenant load Worth 12 minutes if -
Teams lack a continuous improvement system for their agents
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Most teams building today have traces, what they don't have is a system for continuously improving their agents.
— LangChain (@LangChain) 23 juin 2026
The teams that do use an agent development lifecycle: build, test, deploy, and monitor.
The problem with this lifecycle? It scales at the speed of their engineers. pic.twitter.com/YlXt3BRrQ2Most teams that build today have traces, what they don't have is a system to continuously improve their agents. Teams that use an agent development lifecycle: build, test, deploy, and monitor. The problem
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LangSmith Engine identifies issues, clusters patterns, and fixes agents
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That's why we built LangSmith Engine, an agent built to improve your agent. Engine identifies issues from traces, clusters patterns, drafts fixes, and proposes evals to prevent regressions. Connect your tracing project + start improving your agent today:
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17-minute guide to transform LangGraph into a voice agent
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You can turn an existing LangGraph agent into a fully functional voice agent with @pipecat_ai.
— LangChain (@LangChain) 23 juin 2026
This 17-minute walkthrough shows you exactly how to do it. https://t.co/N28T4sQ153 pic.twitter.com/BNy9MygE3xYou can transform an existing LangGraph agent into a fully functional voice agent with @pipecat_ai. This 17-minute practical guide shows you exactly how to do it.
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Interpreters in Deep Agents: Embedded Code Execution
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Interpreters in Deep Agents: Small embedded runtimes where agents can write and execute code inside the agent loop. An explainer by @huntlovell from the @LangChain_OSS team https://langchain.com/blog/give-your-agents-an-interpreter …
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The Art of Loop Engineering with Deep Agents
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The art of loop engineering, powered by Deep Agents! https://langchain.com/blog/the-art-of-loop-engineering …
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A great opportunity to learn the Agent Development Cycle with hwchase17
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A great opportunity to learn the Agent Development Cycle with @hwchase17
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LangSmith Fleet: Two Types of Agents, General and Specialized
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LangSmith Fleet offers two types of agents: General-Purpose Chat and Specialized Agents. An analysis of why this choice is deliberate and the use cases for each.
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Discover how to comply with the AI Act using LangSmith
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Ready to discover how you can meet the core technical requirements of the EU AI Act with LangSmith?