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Lesson 3: Verify & Ship

Where We're Starting

After Lesson 2, you've got a decomposed backlog, skills for consistency, and a manual review process that checks AI output against your acceptance criteria. You've felt the power of criteria-based review. No more vague "looks good" calls. Pass or fail.

But you've also felt the honest tradeoff. Manual review works, but it's slow. Every feature gets walked through by hand. And every time you add something new, there's a nagging question: did that change break something you already verified? You won't know unless you re-check everything, and you don't have time for that.

That's the tension this lesson resolves. Your acceptance criteria are already doing double duty as spec and test. Now you'll learn to turn them into automated checks that run themselves, and then ship your verified work to a live URL.

After Challenge 2, you have skills and a review process working for you. Check in on where you are between these two levels:

  • Doer. You use AI regularly to get things done. You can write effective prompts, build with AI assistance, and troubleshoot when things go sideways.
  • Delegator. You define the work and hand it off. You write clear specs, user stories, and acceptance criteria that tell AI what "done" looks like.

Your slider value moves your avatar on the progress board. Be honest about where you feel right now.

What You'll Learn

  • Why your acceptance criteria in Given/When/Then format are already test specifications, and how to have AI turn them into automated tests
  • The closed loop (criteria → tests → fail → implement → pass) that replaces manual re-checking
  • How visual verification extends your safety net to cover what users actually see
  • How to deploy your verified application: tests pass, then it ships

Sections

  1. Your Criteria Are Already Tests - The acceptance criteria you wrote are test specifications in disguise
  2. The Safety Net - AI-generated tests, the closed loop, and visual verification
  3. Ship It - Tests gate deployment: verify it, then ship it to a live URL

By the End of This Lesson

  • You can explain why manual review doesn't scale and what the two-week cliff looks like
  • You understand that Given/When/Then acceptance criteria map directly to automated test structure
  • You've had AI generate tests from acceptance criteria and seen them run
  • You understand visual verification as a way to check what users see, not just what code does
  • You've deployed your application to a live URL
  • You're ready for Challenge 3 with automated tests as your safety net