LangChain + Aim: Building and Debugging AI Systems
Wrapping Up In conclusion, as AI systems become more complex and powerful, the need for comprehensive tracing and debugging tools becomes
Contact UsDebugging AI Server LPO
Home / Debugging AI Server LPO
This guide covers all of it: unit testing tool implementations, integration and end-to-end testing with mock LLM responses, regression testing with golden datasets, performance profiling, and the debugging techniques that make agent failures diagnosable rather than mysterious. Complete guide to debugging AI agents in production: 5 failure modes, debugging primitives, and when to use agent-first observability tools like Latitude. By Latitude · March 23, 2026 Key Takeaways Agent debugging requires thinking about failure at the session level — the failures that matter. DebugMCP is an MCP server that gives AI coding agents full control over the VS Code debugger. Instead of reading logs or guessing, your AI assistant can autonomously set breakpoints, launch debug sessions, step through code line by line, inspect variable values, and evaluate expressions — just like. Debugging production MCP servers requires moving beyond local STDIO to inspect raw JSON-RPC traffic, handle HTTP 429 rate limits, and normalize third-party API errors before they reach your AI agent.
