Practical notes on RAG chunking that retrieves

What to measure first

Log latency percentiles, token counts, and failure modes before changing models. Averages hide the pain users feel.

Minimal code check

Start with a tiny reproducible script so every experiment is comparable.

import time
t0 = time.time()
# run inference
print('seconds', time.time() - t0)

Ship checklist

Pin versions, add eval gates, and name an owner for the first week in production.

Takeaway: Measure, baseline, then optimize the bottleneck you can prove.