Jon Radoff 👾/acc 🎮 Metavert

Just spent $500 in compute vibe coding my own Civilisation RPG but with unbounded natural language diplomacy.. meet Uncivilised. ask me anything.

🚨BREAKING: This paper should terrify every Physics PhD student. AI agents just ran a full particle physics experiment. Alone. No human in the loop. Researchers tested whether LLM-based AI agents could autonomously execute a complete high energy physics analysis pipeline. Not help with it. Not co-pilot it. Do the whole thing. They built a framework called JFC (Just Furnish Context) that combines autonomous analysis agents with literature-based knowledge retrieval and multi-agent review. Here's what the AI agent did on its own: - Event selection - Background estimation - Uncertainty quantification - Statistical inference - Paper drafting It ran real experiments on open data from ALEPH, DELPHI, and CMS. It performed electroweak, QCD, and Higgs boson measurements. The tool used? Claude Code. The scariest line from the paper: "The experimental HEP community is underestimating the current capabilities of these systems." Researchers argue most proposed agentic workflows are too narrowly scoped. The AI can already do far more than anyone is building for. But here's the nuance people will miss. This isn't about replacing physicists. It's about offloading the repetitive technical burden so researchers can focus on actual physics insight and novel method development. The real takeaway: if AI can autonomously run one of the most complex experimental sciences on earth, the question isn't whether your field is next. It's whether you're already behind. Authors: Eric A. Moreno, Samuel Bright-Thonney, Andrzej Novak, Dolores Garcia, Philip Harris

Just spent $500 in compute vibe coding my own Civilisation RPG but with unbounded natural language diplomacy.. meet Uncivilised. ask me anything.