Building a Self-Healing RAG Pipeline With LangGraph, LangChain, and LLM-as-Judge
A walkthrough of the guardrails, retrieval validators, retry orchestration and feedback loops I added after my RAG system started confidently returning wrong answers with no errors anywhere in the stack.
1. The Answer Was Wrong, and Nobody Knew
The retrieval was working & I could verify that. The right document was coming back, sitting at the top of the results with a strong similarity score. The LangChain chain was executing cleanly. No exceptions, no timeouts, no retries. The LLM was receiving the correct context in its prompt window. And then it was generating an answer that directly contradicted what it had just been given. Not occasionally but rather regularly and confidently, with the same smooth tone it used when it was right.
I only found it because a user happened to flag a specific response that they could verify against a document they had open in another tab. When I...
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