The Death of model.fit(): What Data Scientists Actually Do in the Age of AI Agents
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A data scientist at monday.com reflects on joining an AI agent team where there was no model to train, no Python, and no traditional ML workflow. The post argues that the data scientist's role in the agentic era shifts from model training to systematic evaluation and quality ownership. Key responsibilities include building
Table of contents
The Empty Notebook Is the PointThe Real Problem isn’t Building Agents. It’s Knowing If They WorkEvaluation-Driven Development: Your New Training LoopWhat the Work Actually Looks LikeThe Sprint Velocity TrapWhere DS Ends and Engineering BeginsSo Is It All About Evals?The Quiet Case for MeasurementSort: