RAG Was Failing for 3 Weeks — And No One Noticed скачать в хорошем качестве

RAG Was Failing for 3 Weeks — And No One Noticed

For three weeks, our RAG system was returning degraded answers. No errors. No timeouts. All dashboards were green. Retrieval didn’t break. It just got worse — slowly. If you want to build RAG systems the way real production teams do — with: Guardrails Orchestration Observability layers Explore the full RAG systems program here: 👉 https://rag.nachiketh.in Join the serious builders community: 👉 https://community.nachiketh.in The root cause wasn’t embeddings. It wasn’t Pinecone. It wasn’t the LLM. It was silent retrieval degradation caused by a chunking configuration change that created a mixed semantic index. Cosine similarity stayed “valid.” Latency improved. Infrastructure metrics were healthy. And yet, generation quality drifted. This video breaks down: Why silent retrieval failures are the most dangerous RAG production issue Why cosine similarity is not a quality signal The observability gap in most RAG systems How to design semantic SLOs Judge-model based retrieval evaluation Version fingerprinting for ingestion pipelines How to convert silent degradation into detectable signals If you’re running RAG in production, assume something is silently drifting right now. You just don’t have instrumentation to see it. 🔧 Build Production-Grade RAG If you want to build RAG systems the way real production teams do — with: Guardrails Orchestration Observability layers Explore the full RAG systems program here: 👉 https://rag.nachiketh.in Join the serious builders community: 👉 https://community.nachiketh.in No toy demos. No theory-only walkthroughs. Only production architecture.