The Anatomy of an AI Agent (allen.hutchison.org)

In the first installment of The Agentic Shift, the author lays out a clear anatomy for modern AI agents: perception, reasoning, and action. Rather than a lone model, an “agent” is a system built around a large model (the brain) that consumes digital inputs—APIs, data streams, file systems (the senses)—and executes via tools/APIs (the hands). That cycle—sense, plan, act, observe—creates a dynamic feedback loop enabling goal-directed behavior, exemplified by a simple weather-forecaster agent that queries a weather API, reasons about precipitation probability, and proactively notifies a user. The piece emphasizes the technological convergence making this possible: LLMs that can reason and widespread API-accessible digital environments. The write-up stresses why this matters for AI/ML practitioners: agentic systems are not just smarter UIs but emergent, pro-active actors with autonomy and goal-orientation, shifting human roles from micromanagement to high-level direction. That power brings new design and safety challenges—memory, toolkits, instruction design, guardrails, and multi-agent coordination—which the series will tackle in subsequent posts. For builders, product leads, and researchers, the anatomy provides a shared mental model to design, evaluate, and govern agents as they move from passive models to active collaborators.