VeRO: A Harness for Agents to Optimize Agents
An important emerging application of coding agents is agent harness optimization: the iterative improvement of a target agent by editing and evaluating its code. Despite its relevance, the community lacks a systematic understanding of coding agent performance on this task. Harness optimization differs from conventional software engineering: agent harnesses interleave deterministic code with stochastic LLM completions, requiring structured capture of both intermediate execution traces and downstream outcomes. To address these challenges, we introduce (1) VeRO (Versioning, Rewards, and Observations), an outer harness that provides versioned snapshots, budget-controlled evaluation, and struc...
| Authors | Varun Ursekar, Apaar Shanker, Veronica Chatrath et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 February 2026 |
| Last updated at source | 2 June 2026 |
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