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cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture ๆŠ•็จฟใฏๅ€‹ไบบใฎๆ„่ฆ‹ใงใ™ใ€‚
๊ฐ€์ž… May 2026
280 ํŒ”๋กœ์ž‰ ์ค‘    415 ํŒฌ
๐Ÿ’ฐ Same model, same task, but swap the software wrapper (harness) around it and the cost can jump 5x while success rate barely moves. Title: HarnessTax: How Much Does the Harness Matter for Coding Agents? URL: UC Berkeley and Arena compared three coding agent harnesses, Claude Code, Codex CLI, and Pi, across 7 models and 21 model-harness pairs. Here are 3 highlights. ๐Ÿ“Š Statistically, harness barely moves success rate Out of 42 within-model harness comparisons, only 1 was statistically significant (chance alone predicts about 2), and none survived correction for multiple comparisons. ๐Ÿ’ธ Cost can differ 5x at the same success rate On GPT-5.6 Luna, Claude Code cost $0.15/task at 55.6% success, while Pi cost $0.03/task at 53.3% success, nearly identical accuracy, 5x the price. ๐Ÿชถ The minimal open-source harness holds its own In 9 of 12 model comparisons, a non-vendor harness (Pi or Codex CLI) achieved the top success rate, showing a stripped-down harness can genuinely compete. The practical takeaway: prioritize cost and reliability over flashy add-on features first. #CodingAgents# #LLMCostOptimization#
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