RAG pipelines in production: what breaks after the demo
Chunking, retrieval quality, cost and evals - the four places where a RAG demo quietly dies on the way to production, and what to do about each.
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Notes on full-stack & AI/LLM engineering - what actually works in production.
RSS feed ← Back to portfolioAI code review in a real team: CodeCritic lessons
What a year of running AI code review on real pull requests taught me about prompts, noise, trust and where AI actually saves review time.
How I run 1-2 week sprints with demos
The sprint format I use with clients: fixed scope, weekly demo, honest estimates - and why it keeps projects predictable.