The golden set stopped catching regressions the day traffic changed
Article summary
Quick briefing — cleaned from the original RSS feed
TL;DR. Our overall eval pass rate read 0.88 through a model change and looked stable. Sliced by request language, German had fallen to 0.60 while English held near 0.90. The aggregate hid that because German was a rounding error inside the golden set even though it had grown into almost a quarter of real traffic. A bigger golden set does not fix this. Slicing every run by the production distribution, and refreshing the set from real traffic, does. The dashboard stayed green while users…
1Key Takeaways
- Our overall eval pass rate read 0.88 through a model change and looked stable.
- Sliced by request language, German had fallen to 0.60 while English held near 0.90.
- The aggregate hid that because German was a rounding error inside the golden set even though it had grown into almost a quarter of real traffic.
- A bigger golden set does not fix this.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that our overall eval pass rate read 0.88 through a model change and looked stable.
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