An AI agent combines a language model with tools that retrieve information or propose actions. Its main difference from a simple chatbot is access to a workflow. That access needs clear boundaries.
Start with a defined task
For example, prepare a response to a support request. The agent may search documentation and write a draft. A staff member checks the response before it is sent.
Separate reading from changing
Grant access only to information required for the task. Distinguish between retrieving data, proposing a change and executing it. Require approval for consequential actions such as changing an order or sending a message.
Design for failures
Decide what happens when information is missing, an integration fails or a request arrives twice. Provide a clear handover to a person, limit the number of steps and record completed actions.
Evaluate independently of the model
Compare setups using, for example, ChatGPT, Claude or locally served models on the same tasks. Measure correct completion, required corrections and cost per completed request. Expand permissions only after the limited workflow operates reliably.
