AI agent

An AI agent is a language model set up to pursue a goal over several steps, using tools to act in the world. Instead of answering once, it plans, takes an action (search the web, run code, read a file, call an API, click in a browser), looks at the result, and decides what to do next, repeating until the task is done or it needs help.

Coding agents that edit files and run tests, research agents that read dozens of sources, and computer-use agents that operate a browser are common examples. What makes something an agent is the loop of reasoning and acting with real tools, and a degree of independence in choosing the next step.

Agents can do far more than chat, which also means they can do more damage. Good agent design includes clear task briefs, limited permissions (read only where possible), human approval before irreversible actions such as sending, paying or deleting, protection against prompt injection from content the agent reads, and logs of what the agent did. Most successful agent setups start narrow and earn more freedom over time.

Example

Asked to "find why the checkout test fails and fix it", a coding agent reads the test output, opens the relevant files, forms a hypothesis, edits one function, reruns the tests, sees a new failure, adjusts its fix, and stops when all tests pass, then summarises the change for review.

Common mistake

Giving an agent a vague goal and broad access, then leaving it alone. Agents act on exactly what they understand, and small misunderstandings compound across many steps. Be specific about scope and success, start with read-only or draft-only permissions, and review its work.