The developer of nano-harness, a coding agent built with approximately 970 lines of Python, has shared their experience and benchmark results. The agent achieved a 59.6% score on the Terminal-Bench 2.0 suite, utilizing Claude Opus-4.8. An independent review of the code by GPT-Sol-5.6 provided valuable feedback, contributing to the project's development. The project emphasizes a "score-per-line-of-code" philosophy, aiming for a small, readable harness that delivers meaningful benchmark numbers. AI
IMPACT Demonstrates a practical approach to building and evaluating coding agents with minimal code, potentially influencing future agent development.
RANK_REASON The item describes the creation and benchmarking of a specific AI agent/tool, not a frontier model release or significant industry event.
- Andrej Karpathy
- Claude Opus-4.8
- GPT-Sol-5.6
- LLM Wiki
- Nanochat
- nano-harness
- Python
- PyTorch
- Terminal Bench 2.0
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