RAG Works Better When Your Data Is Already Tidy
Every retrieval project I've watched go badly went badly for the same reason.
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Things I've had to work out, written down before I forget them. Pipelines, platforms, and the parts of AI that turn out to be data engineering. Aimed at senior engineers who would rather skip the intro.
Every retrieval project I've watched go badly went badly for the same reason.
Read the articleA job failed at four in the morning. Whose was it?
Read the articleGold layers get the demos. Bronze to silver is where the numbers get earned.
Read the articleBranches for tables, and what that does to the way releases feel.
Read the articleWhat to write down, and who you're writing it for.
Read the articleFive things I keep coming back to. None of them are clever.
Read the articleRoughly. It depends on what breaks.
Testing, failure modes, and what to do at four in the morning.
Internal tooling, developer experience, and why year two is harder than year one.
Making it useful without three new services in the stack.