A demo answers an important question: does this idea make sense? Delivery asks another: can people rely on it in their actual workflow? We use different checks for those different questions, especially when AI and external services are involved.
Check beyond the visible screen
For an illustrative example, take a request form in an ERP, FMS, or CMS. Seeing a success message is useful, but incomplete. Was the request stored correctly? Can an authorized teammate find it? Does it survive a reload? What happens if the user submits twice or the next integration is unavailable?
Use each test for what it proves
A focused test can check validation or a state transition. A simulated integration can check how we handle a response. Neither proves that a real provider accepts the request or that the complete browser journey works. We keep those limits clear and choose additional checks based on the change.
- Focused checks for business rules and regressions.
- Integration checks for boundaries and failure handling.
- Browser checks for the complete user journey.
- Deployment checks when the change is released.
AI needs the same discipline
AI-generated code still needs review. An AI answer still needs evidence. A tool-driven action still needs the right permissions and an observable result. A plausible response from a model or a mocked service is not proof that the intended action happened.
Make delivery easy to understand
We aim to communicate the outcome in plain language: what changed, what was verified, and what remains uncertain. That gives the client a useful picture of progress and gives the engineering team a clear basis for the next decision. Technical ownership includes carrying the idea through to a checked result.