英伟达sol-pi通过优化harness将编码代理的token使用量削减近一半
英伟达的sol-pi系统通过优化编码代理的harness，将token使用量减少近一半，而性能保持不变。
nvidia's sol-pi system targets the harness, the control layer between the model and environment used by coding agents like codex and claude code. sol-pi uses a research ai to analyze agent traces, propose harness changes, and test them in prepared environments. the system explored 152 directions across 535 executable environments, generating over 3,000 runs and 60,000 agent-environment interactions. sol-pi produced four mechanisms to eliminate wasted work: action fusion, online context compact, observationpack, and the evidence-preserving reducer. these changes resulted in a 50% reduction in token usage compared to codex and 54.3% compared to claude code on edgebench, without sacrificing performance.