AI Agent

How it works

An agent consists of a language model, tools and a loop. The model plans the next step, calls a tool (search, database, calendar, email), evaluates the result and decides whether to continue or whether it is done. This lets it handle multi-step tasks that a single prompt cannot manage.

A practical example

An agent reads incoming requests, looks up matching information in the internal system, drafts a reply and submits it for approval.

What you should know

• Agents make mistakes: they misunderstand requests or fail on unexpected data. That is why clear limits, logs and approval steps (human-in-the-loop) are needed.
• Fewer permissions are better: give an agent only the tools and rights it needs for the task.
• Agents often deliver the most with frequent small interruptions in everyday work, not with the most elaborate tasks.