Guide
Prototype to Production: What Needs to Happen Before a Tool Goes Live?
AI-assisted prototypes can be powerful, but production systems need proper review, testing, security, documentation, deployment planning, support and governance.
What a prototype is good for
A prototype proves the concept, shows the workflow and lets people test the idea. It is not production-ready and should not hold real data, make real decisions or replace existing business systems without review.
What production means
Production means the tool is used by real people for real work. It needs to be reliable, secure, documented, supported and governed. The checklist below covers the key areas.
Testing happy paths and edge cases — does the tool work for normal use and handle unexpected inputs gracefully?
Permissions and access control — who should be able to see, edit or delete data?
Data storage and retention — where does the data live, how long is it kept and who owns it?
Error handling — what happens when something goes wrong? Are users shown a clear message?
Documentation — is there a clear note for users and maintainers covering assumptions, limitations and contacts?
User training — does the team know how to use the tool, when to escalate and how to report issues?
Ownership and support — who looks after the tool after launch? What happens when something breaks?
Change control — how are updates requested, tested and deployed without breaking existing use?
Go-live checklist — is there a final review before real data goes in and real people start relying on the tool?
Go-live checklist
Before a tool goes live with real users and real data, run through this final review.
Help moving from prototype to production?
WorkFlint can review, test and support your AI-built tool so it is ready for real business use.