Training repo-level code editing into weights to ditch heavyweight agent scaffolds
burkov · x · 2026-10-14
Andriy Burkov highlights research questioning today's SOTA approach to repository-level software engineering, where heavyweight agent scaffolds with multi-turn loops bring compute overhead, error propagation, and murky attribution of success. The work explores embedding repo-level code editing directly into model weights by transforming noisy open-source pull requests into rigorously verified training data — a path toward lighter, cheaper, more attributable coding models.
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