AI models vs AI agents: what is the difference?

A model can explain a supplied order record. An assistant connected to an authorised order API can look up the current status. An agent may decide which lookup to perform, interpret the result and choose a permitted next step.

If the customer asks to change delivery details, the system needs identity checks, business rules and an action API. The model should not be the only component deciding whether that change is allowed. Permissions and validation must also exist in the application and underlying systems.

A predictable process can use fixed steps: receive a request, classify it, retrieve a record and produce a draft for review. An agent is more useful when the route depends on information discovered during the task.

Start by drawing the steps a capable employee follows. Mark where judgement is needed and where a deterministic rule works. Adding autonomy to a process that is already well defined can increase cost and failure modes without improving the outcome.

• Tools expose specific information or actions with defined inputs and outputs.
• State records what has happened and what remains to be done.
• Permissions limit what the system can read and change.
• Evaluation checks whether the task was completed correctly.
• Human review handles ambiguous or consequential decisions.

“Memory” is not a magical understanding of the company. It is information stored and supplied by the surrounding application. Decide what is retained, for how long and who can inspect or delete it.

Giving an agent broad credentials because it might need them makes mistakes more consequential. Letting it repeat a failed write without an idempotency mechanism can duplicate transactions. Assuming a successful tool call means the business task succeeded can hide incomplete work.

For a delivery change, verify the resulting order record and communicate the confirmed state. If an API response is ambiguous, stop and reconcile rather than guessing that the request failed and trying again indefinitely.

A useful starting point is preparing a support response or assembling an internal research brief from approved sources. Define completion, tool limits and review. Add write actions only after you can observe and evaluate the read-only workflow. The goal is a dependable job outcome, not the largest possible collection of tools.