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Diagram comparing a one-off human shipping decision with a continuous evaluation system that learns from production and ships improved agents.
Closing the loop: Evaluating and improving Replit Agent at scale
Most Replit Agent users start with an idea. They describe the goal in natural language — without a repo, test suite, or chosen framework — and expect the agent to turn it into a functioning app. The result might be a website, slide deck, mobile app, several connected artifacts, or something else entirely.