AI agent development: define the business workflow before the chatbot

Write a one-page job description

Describe the person the agent helps and the result that should follow a successful interaction. “Answer questions” is too broad. “Identify a property enquiry, collect the stated requirements and prepare a viewing request for a salesperson” provides a workflow that can be tested.

List the information the agent may use and the systems it may change. Reading a catalogue, drafting a reply and changing a CRM record are different permissions. Keep them separate in the project scope.

Define the point where conversation becomes action

Map the steps from a visitor’s request to an approved outcome. For each step, identify its input, responsible system and confirmation evidence. A booking should not be described as confirmed merely because the assistant proposed a time.

• What information is mandatory before proceeding?
• Which actions require a person’s approval?
• What should happen when a source is unavailable?
• How are repeated requests and retries handled?
• Where does an unsupported question go?

Test exceptions alongside successful conversations

Use synthetic enquiries that change requirements, omit important details or request an unsupported service. Include a connection failure after an action has been submitted. Check whether the agent can identify uncertainty without repeating an external action.

Review the interaction and the receiving system together. A fluent response can hide an incomplete handoff if only the chat window is inspected.

Pilot a result you can measure

Count acceptable completed outcomes, unresolved handoffs and staff correction time. Include model, messaging, telephony and integration costs where relevant. These observations provide a practical basis for expanding the workflow.

Review Techspa’s AI agent development scope for a custom build, or compare available AI products when an existing workflow may fit. Agree on the connected actions before choosing between them.