Improving 15 LLMs at Coding in One Afternoon. Only the Harness Changed

3 months ago

The article discusses the importance of the 'harness' in improving LLM coding performance, rather than focusing solely on the model itself.
Current edit tools like 'apply_patch' and 'str_replace' have limitations, leading to high failure rates and inefficiencies.
The author introduces 'Hashline', a novel edit tool that uses content hashes to tag lines, improving edit accuracy and reducing token waste.
Benchmark results show significant improvements with 'Hashline', with some models seeing tenfold increases in success rates.
Vendors like Anthropic and Google have been restrictive, banning tools and accounts, which the author argues is counterproductive to innovation.
The harness problem is identified as a key area for improvement, with open-source solutions offering the best path forward for all models.

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