@aiwithmayank: Holy shit…Karpathy dropped autoresearch and the internet rebuilt it 40 different ways in weeks. Someone just cataloged …
Summary
Andrej Karpathy released autoresearch and the open-source community rapidly created over 40 forks and ports, including an Apple Silicon macOS version.
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@GitHub_Daily: AI guru Karpathy previously built an autoresearch script that lets the model automatically run hundreds of rounds of experimental tuning overnight. The Autoresearch open-source project brings the same approach to Claude Code and Codex. Give it a goal and quantifiable metrics, …
The Autoresearch open-source project ports Karpathy's autoresearch approach to Claude Code, OpenCode, and Codex, letting AI agents automatically loop through code changes, run validation, and roll back based on goals and quantitative metrics. It provides 14 subcommands and 9 safety hooks.
@smallnest: I ported @karpathy's autoresearch to automated software development, and after various optimizations, the results are phenomenal.
A developer adapted Karpathy's autoresearch framework for automated software engineering, implementing multiple optimizations that yielded remarkable results.
@lftherios: 1/ Autoresearch from @karpathy has been one of the most interesting agentic patterns to emerge this year. The challenge…
Andrej Karpathy's autoresearch pattern highlights how current AI agents run experiments in isolation, wasting compute by duplicating work and rediscovering dead ends.
@yibie: awesome-autoresearch periodic review, 1 new entry (discussions): Karpathy's Autoresearch for Software Engineers: applying the three-file model of autoresearch (...
awesome-autoresearch is a curated list of autoresearch use cases. This new entry applies Karpathy's autoresearch pattern to everyday software engineering scenarios, providing concrete templates to lower the adoption barrier for engineers.
@AlphaSignalAI: Karpathy automated experiments. AutoResearchClaw automated the whole lab. Most AI research tools handle one step. This …
AutoResearchClaw is a GitHub repository that automates the entire AI research pipeline from an idea to a full conference paper with real experiments, verified citations, and working code, outperforming previous autonomous research systems by 54.7% on a 55-topic benchmark.