ModularRSI Paper Names Three Defects in How Agent Harnesses Get Improved — and the Fixes
dair_ai · x · 2026-09-21
A paper on ModularRSI, a recursive self-improving agent harness, is drawing attention for diagnosing three defects in how harnesses get improved:
- Evolving against the eval benchmark makes reusable improvements indistinguishable from benchmark fitting; ModularRSI evolves on tasks disjoint from the benchmark.
- Updating from a single trajectory confuses systematic harness deficiencies with one task's reasoning details; ModularRSI contrasts successful vs. failed trajectories for the same task, then aggregates across tasks to find recurring behavioral deficiencies.
- A monolithic harness makes recurring problems hard to localize, and optimizing the whole entangles unrelated changes.
Directly useful for anyone maintaining agent harnesses and eval loops.
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