Coding-agent harnesses cost more without better benchmark scores
Harness swaps changed outcomes about as often as reruns, while system prompts made some tasks cost up to three times more.
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Harness swaps changed outcomes about as often as reruns, while system prompts made some tasks cost up to three times more.
Parsimony ranks AI coding models by net syntax units added on SWE-bench Verified patches.
SWE-Duel has coding agents author and repair hidden bugs so difficulty scales with participants.
Paper models multi-agent LLM orchestration as a bilevel game, proving transcript-only gating limits and introducing grounded-memory SRMA.
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