6 min read
RAG Pipelines in Production: What I Learned the Hard Way
The real-world challenges of running RAG in production: chunking strategies, embedding model drift, and the vector database gotchas I learned the hard way.
AIRAGDevOpsProduction
The real-world challenges of running RAG in production: chunking strategies, embedding model drift, and the vector database gotchas I learned the hard way.
When a bug is fixed, my pipeline runs git blame on the changed lines, asks GPT-4o which earlier commit caused it, and links that story in Azure DevOps.
Traditional CI/CD pipelines assume deterministic outputs. Here's how I adapted my pipeline practices for LLM-powered applications where 'correct' is fuzzy.