NVIDIA's SoL-Pi lets AI rewrite agent harnesses, cutting tokens 44.7-49%

alex_verem · x · 2026-09-23

A paper from NVIDIA, NTU and MIT (SoL-Pi, arXiv:2609.20519) hands harness tuning — the software layer around coding agents that reads files, runs commands and manages memory — to an AI instead of humans.

The research AI proposed and tested harness changes across 150 research directions, 500 environments, 3,000+ runs and 60,000+ agent-environment interactions, keeping only token-saving fixes that didn't hurt results.
Four surviving mechanisms: merging file edit + test run into one call; compressing memory when a subtask ends only if cheaper; replacing repeated large tool outputs with a 1KB excerpt plus on-demand pull; delegating log summarization to a cheap model with a verifier rejecting evidence-dropping summaries.
On the 51-task EdgeBench, token traffic fell 44.7–49.0% and API cost by 1/3 vs Pi; it runs 50% cheaper than Codex's native harness and 54.3% cheaper than Claude Code's, holding 94% of baseline scores. Built on GPT-5.6 Sol, it transferred unchanged to Opus 5 saving 44.7% tokens.
Takeaway: much of the waste sits in software around the model, and AI finds it faster than humans; the team's next step is rerunning the search with the cheaper harness.

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NVIDIA's SoL-Pi lets AI rewrite agent harnesses, cutting tokens 44.7-49%

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