A practical way to choose a first AI workflow, define approval boundaries and evaluate the result.
Start with an observable task
An agent demonstration can look impressive without answering a business question. Begin by selecting one repeated task with a defined input, a known owner and a result that someone can assess. Preparing a draft response from approved information is a more testable starting point than asking an agent to “handle customer service.” Map the systems involved and decide which actions are actually necessary.
Separate preparation from permission
A useful design distinguishes reading, drafting and acting. Reading an approved document can have a different risk profile from updating a customer record or sending a message. Give each tool the minimum access needed. Require a person to approve consequential actions and make the proposed change visible before it happens. Retrieved pages and documents should be treated as data, not as instructions granting new permissions.
Build a small evaluation set before rollout
Collect ordinary examples, ambiguous cases and examples where the correct behaviour is to stop. Record the expected result and what a reviewer should inspect. Track completion quality, correction rate and operational cost alongside time saved. Add examples whenever the workflow fails; a polished demo is not a substitute for evidence from representative work.
Plan for interruptions and duplicate actions
External services time out. A request may succeed even if the caller does not receive confirmation. Use durable task identifiers, deduplication and a clear record of actions. An uncertain outcome should trigger investigation rather than a blind retry. Keep a manual route and assign someone to review failures.
A useful first brief
Write down the task, allowed sources, tools, approval points, success measures and stop conditions. That gives a development team something concrete to scope. At DXB Tech, this is the conversation we recommend having before choosing an agent framework.
Further reading
Prepared with AI assistance; technical references checked against the documentation linked above. These are planning considerations, not a guarantee of project results.
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