SOURCE-LINKED INTELLIGENCE
An Empirical Study of Harness Design for Coding Agents
Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing work typically evaluates harnesses as monolithic systems, leaving the effectiveness of individual components unclear. To enable component-level comparisons, we study this question with a lightweight coding harness whose execution loop is fixed while three components are varied: planning, action space, and context management. Across four models evaluated on SWE-Bench Verified and Terminal-Bench 2.1, we evaluate 176 matched settings spanning five conte
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Evidence & attribution
- arXiv · Artificial Intelligence · 2026-09-17T17:58:07.000Z
- arXiv · AI, language, vision and robotics · 2026-09-17T17:58:07.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.