AI agents explained: when a conversation can take actions

A workflow and an agent are not identical

A workflow follows a defined sequence, such as receiving a form and saving a row. An agent can choose intermediate steps based on what it encounters. Many useful systems combine both. Anthropic's engineering guidance distinguishes predefined workflows from agents with more flexible control over tool use. Anthropic: Building effective agents

The label “agent” alone tells you little about reliability. Ask what tools are available and what permissions those tools carry. An assistant that can only read a document has different consequences from one that can delete files or send customer messages.

Describe the goal and boundaries

For a research task, specify the question, sources, output format, and when to stop. For file organization, specify the folder and whether the agent may rename or move files. For communications, distinguish preparing a draft from sending it. Keep ambiguous external commitments under review.

Organize these sample files into proposed categories. Show the proposed filenames and destinations first. Work only within the supplied project folder. Do not delete files or send anything to an outside service. Report any file you could not read.

This is a bounded task with an inspectable result. If the system cannot enforce the requested limits, use a less powerful tool or perform the actions manually after reviewing the proposal.

Understand prompt injection

An agent may read a web page, email, or document containing instructions planted by someone else. Those instructions can attempt to redirect the agent or expose information. The application should treat such material as untrusted content and maintain the user's task and permission boundaries.

Do not assume a polite instruction to “be careful” solves the problem. Limit the accessible data, restrict tools where possible, and require review for consequential actions. The narrower the legitimate task, the easier it is to notice a step that does not belong.

Check the finished work

Look at the generated file, changed records, or service confirmation. Ask for a clear distinction between completed steps, failed attempts, and remaining work. If an action failed, the assistant should not substitute a success-sounding explanation.

Begin with reversible tasks and sample data. Keep backups or version history. Expand autonomy only after repeated use shows that the system handles ordinary exceptions correctly. The benefit of an agent is completed useful work; a long chain of actions is not valuable by itself.