Last updated June 9, 20263 min read

Edit: Fix What the Build Got Wrong

Outcome

A short, prioritised list of what must change before launch - and the confidence that the rest was actually checked, not assumed.

An AI review dashboard checking a finished website with a final review lens, checklist signals, and launch-readiness indicators.

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Table of Contents

What this stage settles

The build is done and nothing has been verified. This stage answers one question: does the site do what the spec said, on the devices people will use?

It is not a redesign. New ideas that arrive here are next-version scope; the output is a fix queue, not a second build.

Two passes, and they are different jobs. First you check the site against the spec. Then someone who did not build it walks it and reports what they find.

Steps

Guide

  1. Lock The URL Scope First

    Start with scope, not opinions. Agent Mode needs to know which local, staging, or production URLs belong to the launch review.

    List the homepage, priority conversion pages, content templates, legal pages, form paths, confirmation states, and any translated or responsive variants that matter.

    Also name what is out of scope. If old routes, hidden experiments, or unfinished pages are not part of launch, the agent should not create tasks for them.

  2. Check it yourself, on both screens

    Desktop, mobile, the flows a visitor actually takes, and the SEO, accessibility and consent basics.

    The Pre-Launch Check: Desktop, Mobile, Flows

  3. Get a second point of view, then queue the fixes

    A stakeholder or Agent Mode walks the site and reports. You sort what comes back into blockers, week-two work and next version, hand over only what is approved, and confirm it without reopening the project.

    The POV Review and the Fix Queue

  4. Decide what ships broken

    Not everything on the queue blocks a launch. Decide which items do, say so out loud, and let the rest wait. A launch delayed by a week-two ticket is a decision nobody made on purpose.

About the author

Nikita Goncharenko

Nikita Goncharenko

AI Fast Integrator

Nikita Goncharenko uses AI as a practical delivery layer for research, coding, documentation, content systems, and faster decisions.