x.com/i/article/204046441296… [Translated from EN to English]
→ View original post on X — @langchain, 2026-04-04 16:34 UTC
@langchain
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LangSmith Arrives in New York City
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Had to hop on the wrong train to get this photo, but LANGSMITH IS IN NYC!
→ View original post on X — @langchain, 2026-04-03 23:10 UTC
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Claude Code Integration with LangSmith for Enhanced Tracing
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👾 Claude Code 🤝 LangSmith 🦜 We've shipped a new way to trace Claude Code runs to LangSmith! It's a plugin that traces subagents, tool calls, compaction runs, and more. You can run evals to test the impact of skills/MCPs, use LangSmith Insights to look for trends across your org, track token usage, and more! Docs: docs.langchain.com/langsmith… Repo: github.com/langchain-ai/lang…
→ View original post on X — @langchain, 2026-04-03 18:40 UTC
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Harrison Chase and MongoDB CEO discuss enterprise agents at Interrupt
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Join @hwchase17 and Chirantan "CJ" Desai, CEO of @MongoDB for a fireside chat at Interrupt — May 13-14 in San Francisco. MongoDB is the company behind one of the most widely used databases for modern applications — used by thousands of teams to power everything from real-time analytics to AI-native workloads. At Interrupt, Harrison and CJ will chat about how teams are building agents at the world's largest enterprises, and what's next for the space. Get your tickets: interrupt.langchain.com/
→ View original post on X — @langchain, 2026-04-03 16:47 UTC
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LangChain Harness Engineering Day 5: Tool Setup and Teardown
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harness eng day 5: toolsets some tools need setup and teardown around the agent loop, like connecting to a tool server or spinning up a sandbox for example, @langchain's ShellToolMiddleware handles init and cleanup, and injects the shell tool into your agent's tool registry!
→ View original post on X — @langchain, 2026-04-03 15:48 UTC
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LangChain adds specific reviewer assignment to annotation queues
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we just added the ability to assign specific reviewers to an annotation queue. as building agents becomes more and more automated, human feedback being part of the loop will be as critical as ever. pic.twitter.com/UMYbJzKNan
— Sam Crowder (@samecrowder) 2 avril 2026we just added the ability to assign specific reviewers to an annotation queue. as building agents becomes more and more automated, human feedback being part of the loop will be as critical as ever.
→ View original post on X — @langchain, 2026-04-02 23:12 UTC
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Production Readiness: Handling Agent Failures with ModelRetryMiddleware
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harness eng day 4: production readiness deployed agents need to be resilient! model timeouts, rate limits, tool failures are inevitable @langchain's ModelRetryMiddleware handles retry logic with configurable retry count, backoff factor, and initial delay
→ View original post on X — @langchain, 2026-04-02 17:38 UTC
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Azure’s OpenAI Traffic Share Grows 4x in 10 Weeks
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The LangSmith Signal: Azure's share of OpenAI traffic grew nearly 4x in under 3 months. We're sharing how devs are building agents, by the numbers. While most orgs started by connecting directly to OpenAI, over the past 10 weeks we've watched Azure's share of that traffic grow from 8% to 29%. We've analyzed this trend via LangSmith Observability data across more than 6.7 billion agent runs. Our hypothesis: 💡 Early adopters moved fast and went direct, but the enterprise wave is now arriving in force 💡 Azure gives teams the compliance, security, and procurement infrastructure they already have in place 💡 Azure traffic 4x-ing in 10 weeks likely indicates AI development is maturing quickly
→ View original post on X — @langchain, 2026-04-02 17:00 UTC
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TierZero: AI Platform Automating Incident Response for Engineering Teams
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LangSmith for Startups Spotlight: TierZero
— LangChain (@LangChain) 2 avril 2026
Engineering teams are shipping code faster than ever, but production operations remain heavily manual and concentrated in the hands of a few experienced engineers. The result: slower incident resolution, constant interruptions, and… pic.twitter.com/DKWXhzK4POLangSmith for Startups Spotlight: TierZero Engineering teams are shipping code faster than ever, but production operations remain heavily manual and concentrated in the hands of a few experienced engineers. The result: slower incident resolution, constant interruptions, and growing operational toil as systems scale. TierZero is the AI platform that helps engineering teams run production systems reliably at scale. Their agents automate incident response, surface reliability risks, and give engineers instant answers to production questions. High-scale teams like Discord, Drata, Framer, and WeightWatchers trust TierZero to accelerate incident resolution and reclaim engineering capacity. At Drata, TierZero reduced issue time-to-resolution by 42% and saved 7000+ engineering hours annually. LangSmith plays a central role in how the team builds agents. Learn more 👉 tierzero.ai Reach out to the team for a free 30-day trial 👉 cal.com/tierzero-az/45min
→ View original post on X — @langchain, 2026-04-02 16:38 UTC
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LangChain at Google Cloud Next 2026 Booth #5006
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Heading to Google Cloud Next? Our team will be at Booth #5006 running demos and available for technical conversations on what you're building with AI agents. See what's happening with LangChain at Next: blog.langchain.com/join-lang…
→ View original post on X — @langchain, 2026-04-02 16:00 UTC