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Concept

Control Drift in Multi-Task Harness Optimization

Control drift is an optimization defect that emerges when iteratively adapting an agent harness across a heterogeneous benchmark suite. When developers or hyper-agents attempt to resolve failures on individual tasks one at a time, localized rules and checks introduced to fix a specific task can impose unnecessary procedural overhead, over-constrain the model's action space, or inadvertently degrade performance and cause regressions on unrelated tasks across the benchmark.

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Updated 2026-09-21

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Prep Sessions

Long-Horizon Agent Reliability: Stateful Scaffolding and Runtime Verification @ University of Michigan - Ann Arbor

Ch.3 State Persistence and Continuous Optimization - Long-Horizon Agent Reliability: Stateful Scaffolding and Runtime Verification @ University of Michigan - Ann Arbor

Failure-Driven Harness Optimization and Procedural Memory - Long-Horizon Agent Reliability: Stateful Scaffolding and Runtime Verification @ University of Michigan - Ann Arbor