How to build an app with AI: from an idea to a tested workflow

Instead of “build a modern logistics app,” write: “An operations coordinator receives a delivery exception, checks the order and assigns a follow-up owner.” Identify what the user knows at the start and what must be true at the end.

List the records involved, their owners and who can read or change them. Include examples of valid inputs and awkward cases. An application brief should explain failed and incomplete work as clearly as the happy path.

Ask the assistant to turn your description into a user journey, data model and list of unanswered questions. Review each assumption. Request several representative scenarios and check whether the proposed rules produce the outcome your team expects.

Keep the approved decisions in a short project brief. When the conversation becomes long, update that brief rather than relying on an old message buried among code changes. Label open questions separately from confirmed requirements.

Implement the smallest workflow that includes the interface, data storage and required integration. A convincing screen with sample data is not evidence that authentication, persistence or permissions work.

For the delivery example, create an exception, assign it, reload the page and verify it with another authorised account. Test an unauthorised account as well. Check the database or API outcome rather than relying only on a success message in the interface.

• Keep code in version control and inspect meaningful changes.
• Test inputs, errors, permissions and recovery paths.
• Keep credentials outside source code and the public browser bundle.
• Verify dependencies and integration behaviour against current documentation.
• Use representative data with permission, minimising sensitive information.

Ask the assistant to explain the evidence for each completed feature. “The build passed” establishes that the code can compile; it does not prove the business workflow works in the deployed environment.

Agree hosting, backups, monitoring, support ownership and a rollback process. Check domain configuration, production integrations and mobile use. If the application handles important business records, practise restoring them.

AI-assisted development is most useful when feedback is specific: reproduce a failure, describe the expected outcome and verify the repair. Treat the assistant as a capable collaborator whose work still needs clear requirements and evidence, rather than as a substitute for product ownership.