Runbooks + RAG: How I Gave My AI SRE Agent the Context It Was Missing

This story was originally published on HackerNoon at: https://hackernoon.com/runbooks-rag-how-i-gave-my-ai-sre-agent-the-context-it-was-missing. Learn how retrieval-augmented generation (RAG) helps AI SRE agents use runbooks, postmortems, and documentation to investigate real production incidents. Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #site-reliability-engineering, #devops-knowledge-retrieval, #ai-postmortem-retrieval, #vector-database-runbooks, #sre-agent-architecture, #ai-runbook-retrieval, #ai-sre-agent, #hackernoon-top-story, and more. This story was written by: @armeesala. Learn more about this writer by checking @armeesala's about page, and for more stories, please visit hackernoon.com. Large language models understand infrastructure, but they don't understand your infrastructure. This article explains how a retrieval-augmented generation (RAG) layer gives AI SRE agents access to runbooks, postmortems, architecture docs, and service ownership information at investigation time. It covers the two-plane knowledge model, vector retrieval, real-world failure modes, and practical lessons for keeping an AI knowledge base accurate, current, and trustworthy.