Developer Uses OpenAI Codex to Automate Kernel Research, Achieving 232x Speed Gain

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A developer shared how they used OpenAI's Codex model to automate kernel optimization research, resulting in a 232x performance improvement. The project, dubbed 'auto-research,' leveraged Codex to iteratively explore and refine low-level kernel code. The approach reduced the manual effort typically required in performance engineering by automating the experimentation cycle. The write-up was published on the developer's personal blog and gained traction on Hacker News, attracting community discussion around AI-assisted systems research.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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