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Understanding AI Agents for Data Scientists: The Basic Loop

The post breaks down AI agents into a repeatable loop that data scientists can leverage for automation and insight generation. It identifies seven core components—perception, reasoning, planning, execution, monitoring, feedback, and adaptation—that appear in virtually every agent architecture. By mapping these elements, the author shows how to build modular, extensible agents that integrate with existing data pipelines. The article positions the loop as a practical framework for turning large‑language models into task‑specific assistants.