Autoresearch with Coding Agents: Generalizers and Metric-Maximizers on Quran Recitation Data
Coding agents can now be left alone to improve software against a score. In this pattern--recently popularized as "autoresearch"--the agent receives a dataset, an evaluation script, and one editable file, and iterates without supervision: modify the code, measure, keep the change if the score improves. But what does the agent actually optimize--the developer's intent, or the literal number? We ran this loop on a real production task: deciding which Quranic verses appear in a noisy speech-recognition transcript and splitting the transcript by verse. Two frontier coding agents, Claude Code and OpenAI Codex, started from the same blank file with the same instructions, budget, and reasoning e...
| Authors | Nursultan Askarbekuly, Mohamad Al Mdfaa, Ahmed Helaly et al. |
|---|---|
| Primary category | cs.SE |
| Published | 20 July 2026 |
| Last updated at source | 27 August 2026 |
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