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AI agents recursively improve codebases with Ouroboros system

By PulseAugur Editorial · [1 sources] ·

Daniel Krydynski has developed Ouroboros, an open-source system that enables AI agents to continuously improve a codebase through a recursive development loop. This system, built on top of Nous Research's Hermes agent harness, operates through five stages: scouting for work, creating tickets, implementing changes in a disposable worktree, reviewing proposed code, and finally, merging approved changes to the main repository. The core principle is that the harness never trusts the agents, requiring tests to pass and a human reviewer's sign-off before any merge occurs, ensuring safety and control. AI

IMPACT Enables automated code improvement and maintenance, shifting human roles to oversight and curation.

RANK_REASON The item describes a software tool/framework for AI-assisted development, not a core AI model release or research paper.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI agents recursively improve codebases with Ouroboros system

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14 / 100
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The item describes a software tool/framework for AI-assisted development, not a core AI model release or research paper.
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product, infra
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Daniel Krydynski ·

    Ouroboros: A Recursive Dev Loop Where AI Improves Code — Safely

    <h1> Ouroboros — the recursive dev loop, a walkthrough </h1> <p><em>Built by Daniel Krydynski, with Kiko. A harness that lets AI agents<br /> continuously improve a codebase — safely. This is the inside-out<br /> explanation of the public project at<br /> <a href="https://github.…

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