Why your agent benchmarks are lying to you
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We deployed a coding agent that hit 94% on the industry benchmark. It failed in production on the first real edge case because the benchmark measured single-turn success and our actual work was multi-turn refinement. The model could not update its beliefs correctly when new evidence arrived, something no single-turn eval would catch. This is not a hypothetical. I have watched agents shine in demo and disintegrate on the messy input that production actually serves. The gap between what we…
1Key Takeaways
- We deployed a coding agent that hit 94% on the industry benchmark.
- It failed in production on the first real edge case because the benchmark measured single-turn success and our actual work was multi-turn refinement.
- The model could not update its beliefs correctly when new evidence arrived, something no single-turn eval would catch.
- I have watched agents shine in demo and disintegrate on the messy input that production actually serves.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that we deployed a coding agent that hit 94% on the industry benchmark.
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