May 3, 2025 · 8min read

Understanding RAG for Real AI Systems

Most RAG tutorials stop at “embed documents, retrieve chunks, stuff the prompt.” Production systems fail on everything around that: stale indexes, permission-aware retrieval, evaluation, and the product question of when the model should refuse.

Treat retrieval as a product surface

If users cannot tell why an answer appeared, they will not trust it in finance or health. Cite sources. Show confidence. Log what was retrieved. That is UX as much as it is infrastructure.

LET'S WORKTOGETHER

I design and ship production-ready systems at the intersection of cloud infrastructure, full-stack engineering, and human-centred product thinking.

Send email · kuzagbechristopher@gmail.com
Understanding RAG for Real AI Systems · Christopher Kuzagbe