Separate behavior from evidence
Classify AI project data as retrieval knowledge, fine-tuning examples, or evaluation cases.
The move: stop calling every artifact training data. CRISP-DM treats data understanding and preparation as real project phases, not clerical setup. For fine-tuning versus RAG, that discipline prevents a common mistake: feeding every available document into whichever system the team happens to be building. Different artifacts serve different controls. Retrieval knowledge is authoritative source material: policies, catalog records, runbooks, help articles, contracts, product docs, or approved knowledge-base pages. It should be chunked, permissioned, versioned, and citeable. Fine-tuning examples are pairs of input and desired output that demonstrate behavior: how to classify a case, how to write the final answer, how…
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