Evaluation
Draft · 14 min read
Evaluation-first AI development: a practical guide
Retridge Engineering
RAG & evaluation practice
Draft · not yet published
This note is on the editorial calendar. The outline below shows the intended structure; the article layout, code styling, and diagram treatment are the same as published notes.
Planned outline
Building a first query set from production logs
Labelling gold chunks, not just gold documents
Scoring retrieval and generation as separate stages
Choosing metrics you will actually act on
Gating releases on regression evaluations in CI
Keeping the dataset alive as the corpus changes
In the meantime, the published note on retrieval-versus-correctness covers the measurement approach these all build on.
RAG Engineering Notes
One note a month on retrieval quality, evaluation, and AI security. No marketing.
Related notes
Why your chatbot retrieves the right document but still answers wrong
AI Engineering
The 5 failure modes we find in almost every RAG audit
Case Notes
Prompt injection: the security hole most AI teams ship with
AI Security
Seeing this pattern in your own system? The audit measures all five gates in two weeks.
Book a free consultation