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AI-assisted coding: taking a prototype into production

HTML source code displayed in a code editor
Photo by Mohammad Rahmanion Unsplash

Describing a feature in plain language can produce a working prototype quickly. It can also produce an interface that appears complete while important questions about access, payments and recovery remain unanswered.

For a South African business owner, an AI-assisted prototype is useful evidence of an idea. Treat the move to production as a separate piece of work with its own scope and acceptance criteria.

Define what the prototype has demonstrated

Write down the task it performs, the sample data it uses and the assumptions behind it. Show which parts are connected to real services and which are simulated.

A dashboard with invented figures demonstrates a layout. A checkout that redirects to a success screen demonstrates navigation. Neither proves that the application records the right transaction or protects one customer’s information from another.

Test access on the server

Create separate test accounts and try to open one account’s records from the other. Test the request directly as well as through the interface. Removing a button from view is not enough if the underlying operation remains available.

Review where credentials are stored. Keep privileged keys out of browser code, screenshots and shared prompts. Make sure the business owns the accounts required to operate the application.

Test what happens when services fail

Disconnect a test device while saving a record. Submit the same request twice. Let an external request time out. Check whether the application shows a clear status and whether staff can establish what was actually saved.

Agree how backups are restored and releases are reversed. Ask someone other than the original builder to follow the recovery instructions. Missing steps are much easier to fix during a trial than during an outage.

Review personal information before using real records

Use sample information while developing the workflow. Before introducing customer or employee records, document the purpose, access, retention and external services involved.

Assess that process against the Protection of Personal Information Act. An AI tool’s generated privacy page or assurance in a chat is not evidence that your application meets its obligations.

Budget for maintenance

Keep the source code, deployment instructions, dependencies and account details together. Assign responsibility for updates, error reports and customer support. A product without a maintainer can become expensive even when the first version was cheap to build.

Ask for a production review based on actual risks and customer tasks. That review should identify what can launch, what needs repair and what should wait. Contact webrack with your prototype and the first workflow you want customers to use.