LangChain’s Post

🚀 Deep Agents: The Weekly Roundup 🚀 Dive into our latest resources to help you build, observe, and evaluate Deep Agents capable of handling complex, long-running tasks. 📊 How to Observe Deep Agents - Agents are running longer and getting more complex, which demands new debugging workflows beyond simple LLM apps. We wrote a blog on the trends behind this shift— and why tools like LangSmith Polly and Fetch are needed. Read more: https://lnkd.in/g4-XCwHN ✏️ LangSmith Polly - We launched an AI assistant for AI engineering that helps you understand traces, threads, and improve prompts. Polly shines with Deep Agents, which can have traces with hundreds of steps. Read more: https://lnkd.in/g-KjGEeN & watch the video: https://lnkd.in/gT2M6qsN 🔎 LangSmith Fetch - This week, we launched a CLI for equipping coding agents like Claude Code or DeepAgents CLI with debugging capabilities. Read more: https://lnkd.in/gcTT_ks4 & watch the video: https://lnkd.in/gKse5dWN 📚 LangChain Academy Course - If you’re not sure how to get started, our free LangChain Academy course covers the four features that set Deep Agents apart: planning, file systems, sub-agents, and prompting. By the end, you'll design, implement, and deploy your own. Enroll now: https://lnkd.in/gVhdxn8W