Understanding AI Agents in 10 Minutes

The core loop

An AI agent wraps a language model in a loop: observe the current state, decide on an action, execute that action through a tool, observe the result, and repeat until the goal is satisfied. That loop — not the model alone — is what turns a chatbot into something that can actually get work done.

The three building blocks

Planning breaks a goal into steps; memory keeps track of what's already happened across a long task; and tool use lets the agent call real APIs, browse the web, run code, or query a database instead of just producing text about doing so.

Where it gets hard

Reliability, not raw capability, is the bottleneck for production agents — recovering gracefully from a failed tool call, avoiding infinite loops, and knowing when to hand off to a human are the design problems that separate a demo from a system you can trust with a real workflow.