Longer-form writing on LLM evaluation, benchmarks, and applied agent work.

Before You Score the Model, Score the Benchmark

A Skeptical View Into Current Agentic Software Engineering Benchmarks

Centre for Software Excellence Blog · · Radin Shayanfar, Keheliya Gallaba

Argues that dataset-side noise often dominates model-side signal in agentic SWE evaluation, and that the field doesn't audit its benchmarks nearly enough. Includes the FeatBench-Verified case study, where gold-patch resolution lifted from 37.31% (±1.88) to 99.81% (±0.10) after diagnosing harness and environment defects.