In this article
An AI website development workflow turns approved requirements into reviewed implementation and a tested release. Use AI for bounded tasks, keep changes understandable and verify the behavior against the brief. Developers own technical review, while business owners approve content and customer journeys. A website is ready for production when the relevant checks pass, not merely when a generated preview opens.
The workflow should make correction easier. A large generated application with unclear assumptions is harder to assess than a small change with a clear purpose and an agreed test.
Define the behavior before asking for code
Write requirements as observable actions. For a contact form, describe the required information, destination, success message and failure behavior. Identify which fields the business needs and which information should not be collected.
Include representative content and design rules. A component built around short placeholder text might fail when the actual service name appears. State the responsive and keyboard behavior important to the experience.
Separate public content from private operations. Identify which tasks require authentication and which account roles are allowed to perform them. A visual control should not be treated as an authorization rule.
Approve the requirement before implementation so the team tests against a shared expectation.
Give the AI a bounded task and trustworthy context
Provide the relevant project conventions, existing components and approved brief. Ask for one coherent change with a description of assumptions and tests.
For example: "Implement the approved inquiry form using the existing form components. Preserve the required fields and destination behavior. Explain any missing configuration. Do not add unrelated dependencies or change other page routes. List the tests needed for success and failure cases."
Review the proposed scope before accepting the change. If the task requires a new service or dependency, assess the reason and operational responsibility first.
Keep sensitive credentials out of prompts and public files. Use the project's approved configuration process and limit access to the work required.
Review generated changes in understandable increments
Read the implementation against the requirement. Check whether the code solves the intended problem and fits the project's structure. Verify proposed dependencies and interfaces against their actual documentation.
GitHub's review guidance recommends functional checks, attention to project context and scrutiny of dependencies. Automated review supports the process, while human assessment still needs to address the meaning of the change. [1]
Avoid accepting a test change which simply hides a failure. Ask whether the expected behavior changed, or whether the implementation still needs correction.
Keep a record of the approved change and the reason behind the decision. This helps the next developer understand the website without reconstructing the original conversation.
Test behavior rather than appearance alone
For each important customer journey, test normal completion and relevant failure cases. A booking page should handle a successful booking and an unavailable slot. A search feature should handle a valid result and no match.
Verify data validation beyond the browser interface. OWASP recommends server-side validation because client-side checks are bypassable. The technical owner should also review the broader security requirements of the application. Input validation alone does not establish complete security. [2]
Use synthetic records for testing. Confirm requests arrive at the intended destination and unexpected errors produce a usable response.
Repeat the important tests in the release environment. Configuration differences between a preview and production deserve explicit checks.
Include accessibility in the release review
Check the actual experience with keyboard navigation, visible focus and understandable labels. Review the content order and whether an error is explained where a visitor needs help.
Automated tools identify some issues, but W3C notes their limits. Include human evaluation rather than accepting an automated score as proof of complete accessibility. [3]
Fix repeated component problems at the reusable level when practical. Correcting one shared form component is more maintainable than applying unrelated fixes across every page.
Keep unresolved accessibility findings visible in the release record, with an owner and a decision about completion.
Measure performance using the right evidence
Core Web Vitals cover loading, interaction and visual stability. Google's web.dev guidance gives good-experience thresholds of LCP at or below 2.5 seconds, INP at or below 200 milliseconds and CLS at or below 0.1. Assessment uses the 75th percentile of page loads, with mobile and desktop segmentation. [4]
| Metric | Experience measured | Good threshold |
|---|---|---|
| LCP | Main content loading | 2.5 seconds or less |
| INP | Interaction responsiveness | 200 milliseconds or less |
| CLS | Visual stability | 0.1 or less |
Use laboratory testing to investigate before release and review available field evidence after real visitors use the site. A single high lab score does not establish the experience of every visitor.
Investigate large images, unnecessary scripts and unstable layout behavior based on actual findings. Avoid adding optimization tools without understanding the problem being addressed.
Release with ownership and a recovery route
Record the approved version, configuration and completion checks. Name the person authorized to release the website and the person responsible for responding if an important journey fails.
Confirm administrator access, domain control and the handover materials. The business should know how content changes reach production and how to request technical support.
Prepare a practical recovery approach before the release. Define which problems require a rollback and which are safe to correct in a small follow-up change.
After launch, verify the public routes, forms and measurement. Use the findings to improve the next release instead of treating launch as the end of development.
Frequently asked questions
Is AI generated website code ready for production
Not by default. Review the code against requirements and test the relevant behavior, security, accessibility and performance. The necessary depth depends on the website's functions and risks. A working preview is one check, not the complete release decision.
Should the same AI write and approve the code
AI review offers another source of feedback, but approval needs an accountable technical owner. Independent checks, automated tests and human review address different kinds of errors. Decide the approval process before consequential changes reach production.
What should a website handover include
Include the agreed project files or platform access, configuration instructions, content workflow and maintenance responsibilities. Record third-party services and recovery steps. Confirm which parts of the website depend on hosted features rather than assuming all files transfer unchanged.
Keep human judgment close to implementation
Talk to AVP Marketo about your website requirements and release process. Use AI assistance within a delivery model with clear review, ownership and measurable completion criteria.
