My performance optimization silently disabled the feature the app exists for

This is a submission for DEV's Summer Bug Smash : Smash Stories. TL;DR. I bounded a database read to make my analyzer faster. I derived the bound carefully, wrote the reasoning into the KDoc, and shipped it behind five passing tests. The bound was wrong in a way none of those tests could see. The result: if a lifter deloaded once in the middle of a stall, which is the correct thing for a lifter to do, my app stopped telling them they had plateaued. No crash. No error. No log line. The feature just quietly stopped being true for the people using the app correctly. The setup WhyRep analyzes your training rather than just recording it. The core promise is that it tells you when you have stalled and what to change about it, and that every verdict traces back to a methodology document rather than to something a language model made up. The architecture decision underneath that promise is that nothing is precomputed . Verdicts are derived from raw set logs on read, every time, so there is no cached judgement to go stale when the rules change. Which means every read walked the lifter's entire history for every exercise in the session. That is fine at ten sessions. It is not fine at three hundred. The obvious optimization is to bound the read. The obvious bound is "it only needs the last two weeks." That was my first wrong answer, and it is worth thirty seconds before I get to the interesting one. The plateau rules are not measured in calendar time. They are consecutive-miss counts, and the count varies by lifter tier and by whether the movement is a big or small joint action. The widest window in the signed methodology is an elite lifter on a small joint action: 14 consecutive sessions without progress. Train a lateral raise once a week and 14 sessions is over three months of data. A 14-day cutoff could never have fired a plateau for anyone above beginner tier. It would not have thrown. It would have quietly stopped detecting the exact thing the product exists to detect. Th