Agents All the Way Down: When Science Becomes Executable
Opening — Why this matters now For years, AI for Science has celebrated isolated breakthroughs: a protein folded faster, a material screened earlier, a simulation accelerated. Impressive—yet strangely unsatisfying. Real science does not happen in single model calls. It unfolds across reading, computing, experimentation, validation, revision, and institutional memory. The uncomfortable truth is this: as AI accelerates scientific output, it is quietly breaking the human systems meant to verify it. Peer review strains. Reproducibility weakens. “It worked once” becomes the dominant success metric. ...