The page loads, the buttons respond and the result looks right. Your first AI-built tool is taking shape. You want to share it with the team.
Before sending the link, take a step back. A successful demonstration validates a journey under certain conditions. For everyday use, you also need to understand what happens when information is missing, two people work at once or someone accesses the wrong page.
Here are the questions to examine before deciding on your next step.
Does the tool perform the expected task correctly?
Return to your original objective and write down a few situations to test. For a sales calculator, prepare examples whose results you already know: an ordinary case, a zero value, an empty field and a value outside the expected limits.
Compare the answers with your business rules. A working button does not prove a calculation is right.
Also describe what the tool should reject. If a discount exceeds the allowed maximum, should it block the entry or display a warning? That decision is yours. The AI does not automatically know your internal rules.
Who can access the information?
If your prototype has multiple accounts, check access using separate test users. Can one person see or change another person’s information? What happens if they try to open a restricted page directly?
Hiding a button in the interface does not demonstrate that access is protected. As soon as the project involves accounts, confidential data or consequential actions, arrange an appropriate technical review.
Generated code can contain mistakes and vulnerabilities. GitHub reminds users that the output of coding assistants must be reviewed and tested. Read the limitations and responsibilities described by GitHub.
Do you know where the data goes?
Have the information flow described: what stays in the browser, what is sent to a service and what is stored. Then ask for those explanations to be checked against the application’s actual behaviour.
For example, can a sales preparation form work without a customer’s name? If so, that first version will be easier to try. If a connection to the customer database becomes necessary, treat it as a further stage of the project.
Also check export and deletion options. You should know how to retrieve useful information and remove what should no longer be kept.
What happens when something fails?
Try a connection interruption, a double-click on a button and a missing answer. Does the user understand what is happening? Can they try again without creating duplicates or losing all their work?
Suppose a tool prepares an internal request. If sending fails, displaying a success message would be misleading. Provide a clear message and a recovery option, such as keeping the draft or allowing the user to copy the summary.
These trials help identify situations where a user might believe an action has happened when it has not.
Who will be able to update it?
Record where the project is kept, the access it needs and how it works. Plan a backup or a way to return to an earlier version, depending on the solution you choose.
Also identify someone who can take it over. What will the team do if the person who created the prototype is absent? Who will step in if an update breaks the main journey?
For a limited trial, a small group and fictional data may be enough to continue exploring. For an application used every day, agree with the appropriate people on the checks and conditions for putting it into service.
Your prototype can then lead to a clear decision: continue testing, have specific issues fixed or prepare a rollout. You will know why you are moving to the next stage.
Want to review a prototype? Discuss your needs and next steps with eloRezo.