What I'm learning, shared.
No content for content's sake. Honest notes drawn from real AI systems in production: RAG, agents, costs, on-prem. I write up what's been useful to me, to save you time.
Use cases
The case that looks like yours.
Five shapes the work takes, from the simplest to the deepest. Each one opens onto what I have written about it, in detail and without jargon. If yours isn't here, that is exactly what the first exchange is for.
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Five cases among others. The full library runs to twenty-eight pieces.
All articles
Quick reads, ideas that hold up.
RAG, agents, LLM costs, production reliability: what I actually see in the field, no fluff.
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