StarHarness: stratified search, proposer-hidden selection, then held-out enterprise transfer
Aug 25 Esakkiraja et al. (ServiceNow/Mila): evolve prompts/tools/skills/MCP/subagents with failure-mode strata + hidden selection; +20–35 pp on ITBench / EnterpriseOps-Gym / AutomationBench, frozen transfer across GPT and Qwen.
Source: StarHarness: Evolving Harnesses with Stratified Search for Enterprise Environments
Esakkiraja, Akhiyarov, Yadav, Rajeswar, Bechard, Nemala, and Davasam ask whether a frozen model can climb stateful enterprise tools by editing only the harness — and whether those edits generalize past the search set. StarHarness keeps weights fixed and searches an editable Stirrup surface (prompts, tool schemas, skills, MCP providers, subagents, finish logic) via a Pi-based coding proposer. Before search it stratifies tasks by baseline failure mode, score, and verifier pass rate; splits the evolve pool into proposer-visible search vs proposer-hidden selection; and reserves a true holdout. Candidates are scoped git diffs with leakage guards (no task-ID branches, no verifier text in prompts), a smoke flip, then promotion only when hidden selection mean improves. Hill-climb and tree-search modes share the same acceptance rule; a ledger carries accepted hypotheses and discarded attempts across iterations.
Across ITBench SRE, EnterpriseOps-Gym ITSM, and AutomationBench Finance, 4–12 accepted patches per environment lift full-benchmark scores by roughly +20–35 pp over the default harness, with held-out gains in the same band (e.g. ITBench evolution +45 / held-out +31.7). The same GPT-5.4-evolved artifacts transfer without re-evolution to GPT-5.4-mini, GPT-5.5, and Qwen3.5/3.6 — including ITBench Qwen 25.6% → 70.0%. Trace analysis attributes wins to interface repairs, explicit environment conventions, and search-compression tools; EnterpriseOps-Gym cuts turns ~18 → 10 and estimated cost ~53%. Prompt-only GEPA on Pi trails the evolved Stirrup harness by double-digit points on every bench.
Why it matters for code review
Overnight harness factories under sustained load fail when promotion optimizes the tasks the proposer already saw. Review harness-evolution PRs the way StarHarness accepts: stratified coverage, a selection set the proposer never reads, holdout receipts, and diffs that repair interfaces rather than hard-code answers. Steady harnessed throughput compounds when FOMO for idle enterprise agents funds transferable environment contracts — not another peak-session prompt burst that only greens the search slice.