Claude Academy
Loading

Stand behind what you build

Lesson 815 min
In this lessonBy the end, you’ll be able to
  • Articulate what you own when you ship something AI helped build
  • Identify the technical realities that surface at ship time and build feedback loops that catch them
  • Make the call: ship it, fix it, or stop it

Diligence & sharing your work

Loading

Diligence & sharing your work · 3 min

SummaryTranscript

Diligence in the builder model is full ownership: you’re responsible for the product from whether it should exist to whether it’s serving users after launch. This lesson covers what it means to ship, the technical realities AI won’t warn you about, why tests become your safety net the moment something is live, and the underrated skill of deprecating your own work.

Key takeaways

  • You own the outcome, not the output. “AI wrote it” explains nothing and excuses nothing.
  • Shipping has its own technical vocabulary (migrations, versioning, rate limits, feature flags) that AI will not surface unless you ask.
  • Tests make post-launch iteration safe. The test-first habit is why you can keep changing things confidently.
  • Prototype freely, ship selectively. Cheap code creates value only when paired with honest evaluation.
  • Access is a design decision. Check who your assumptions exclude before you call something shipped.

Exercise

Ship the Clinic app

Shipping is where diligence becomes real — before you deploy, answer each of these honestly.

Once you’ve worked through these, deploy your app or host it as a prototype, share it with three real users, and make one iteration based on what you learn, with tests that verify the change.

  • Understanding — Can you explain what your code does, not just what it should do?
  • Testing — Do your acceptance tests still pass? Have you tested edge cases — closed clinic, missing data, zero wait time?
  • Access — Who does your build not serve well?
  • Responsibility — Could this output be misread or misused? Have you been transparent about AI’s role?
  • Feedback loop — How will you know if it’s working after it ships?

Lesson reflection

  • How has your thinking about AI integration changed from the beginning of this course?
  • What’s one thing you’ll do differently in your work with AI based on what you’ve learned?

What's next

You’ve built, evaluated, and shipped the Clinic Wait Time Checker. In the final lesson, you’ll bring the full 4D Framework together and leave with a real task already in motion.