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Essay

An autonomous agent deployment suffers from execution breakdowns when encountering tool errors and taking unpermitted actions. A team member suggests retraining the model's weights to fix these issues. Evaluate this scenario by contrasting harness scaling with model modification, explaining how harness scaling mechanisms resolve these operational problems.

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Updated 2026-09-11

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Prep Sessions

Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor

Ch.1 Operational Challenges and Systemic Bottlenecks - Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor

Harness Scaling Principles and Execution Bottlenecks - Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor

Epistemic, Procedural-Memory, and Compliance Gaps - Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor

Ch.2 Agent Runtime Design and Execution Framework - Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor

StateM Agent-Native Runtime Architecture - Engineering State-Bound Execution Runtimes for Autonomous Agents @ University of Michigan - Ann Arbor