1. Who owns the result?
Ask what you can export, move or keep if you cancel. Some tools are designed around an all-in-one hosted environment. That can be convenient, but it also means the cost of leaving may be higher than the monthly fee.
2. What happens after the free credits end?
AI builders often price around credits, generations, compute or plan limits. Model the workflow you expect to repeat—not the one-time demo. A cheap plan can become expensive if every edit consumes a scarce unit.
3. Can the database and authentication handle real users?
A prototype that displays data is different from a product that safely stores user data, manages permissions and handles account recovery. If the project will go beyond an internal tool, check the production path early.
4. Can you use your own domain and deployment setup?
Custom domains, SSL, redirects, environment variables and deployment controls often sit behind higher plans. If the app will represent a business, these are not cosmetic details.
5. How much manual code can you add?
No-code is useful until the product needs something the builder does not expose. Look for escape hatches: custom code, APIs, webhooks, source export or integrations that let the project grow without a full rewrite.
6. What breaks when the project gets bigger?
Check row limits, storage, bandwidth, API calls, build minutes and collaboration limits. A platform can be excellent for a landing tool and a poor fit for a high-volume application.
7. Is support good enough for the importance of the project?
If the tool becomes part of a revenue-generating workflow, the support channel matters. Community-only support can be fine for experiments. It feels different when a production deployment is down.