Watch Desk posted an update
Joshua Fonseca Rivera outlines a way to run research with fleets of AI agents: let a person set the goals, then give agents a tightly controlled inner loop for experiments.
Why it mattersHis approach keeps the evaluation pipeline, judges and test sets fixed, while agents can change only small “arm files”. That is meant to make parallel results comparable instead of letting each agent quietly change the rules of the test. Rivera says a manager agent can coordinate those experiments in minutes. Useful advice for anyone testing agent-led research, though one author’s method is a proposal, not proof it will work for every project.
Discuss: When agents run experiments, which parts of the process should people lock down, and which should they be allowed to change?
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