Reviewing AI-Written Code
From AI output to code you can trust
12 lessons1 hr 34 minPlus
Lesson 1 is free now. The rest comes with Plus.
What's inside
- Why AI code needs different review patterns
- Setting up project-wide guardrails
- Building a review checklist for AI output
What you'll gain
Systematic review of AI-generated and human code to catch what linters and tests miss.
- You'll set up technical guardrails, review AI-written code for safety and standards compliance, and produce reusable review artifacts that the entire team can use across projects.
When to use it
- Setting up guardrails for a scaffolded project
- Reviewing a new feature built by AI
- Establishing team-wide code standards for AI output
You'll reach for it: Every feature or PR
What you leave with
3
Links
3
Prompts
1
Skill
Syllabus
12 lessons · 1 hr 34 min1
Why AI Code Fails (and Where to Always Look First)
AI code looks right, and that's what makes it dangerous. We introduce the First Five checklist, five checks that catch the most common issues in no time.
8 minFree
2Structure a Code Review So Nothing Slips Through
Stop reading diffs top to bottom. Learn a four-pass review order that catches issues faster, and a method called Claim → Verify → Trace for interrogating any block of code.
9 min
3Break Code Before Users Do
Your users will find the edge cases you didn't test. The ZOMBIES heuristic gives you a fast mental model for generating adversarial inputs. Then, you turn what breaks into real tests.
9 min
4Reverse-Engineer Code You Didn't Write
No prompt context. No idea what the author intended. No problem! Reverse-engineer intent from code alone, spot the telltale signs of unreviewed AI output, and structure feedback that actually gets acted on.
8 min
5Decide What Not to Review
Not every file deserves the same attention. Triage a diff by feature and risk in 60 seconds, then build a skill that does it for you on every PR.
5 min
6Identify Dangerous Side Effects
AI hides actions where you don't expect them. Run a side-effect sweep to find every place the code reaches outside itself, before it finds your users.
5 min
7AI Code Security: The Five Checks That Matter
You don't need to be a security expert. Five patterns AI gets wrong every time, and a checklist that catches them in under five minutes.
5 min
8AI-Generated Tests: When Green Doesn't Mean Good
A passing test suite might be lying to you. We’ll cover four patterns of useless AI-generated tests and three questions that expose them instantly.
11 min
9Reviewing AI's Dependency Choices
Not every package AI adds belongs in your project. The WARM check gives you a fast, repeatable way to evaluate any dependency, whether it's worth it, whether it's maintained, and whether it's safe.
6 min
10Automate Your PR Reviews
Some checks are the same every time. Set up automated PR reviews so every PR gets a baseline review without you thinking about it.
6 min
11Turn Reviews Into Better Future Output
Every recurring issue is a rule waiting to be written. Build a system where every review makes the next one faster.
5 min
12Close the Loop: One PR, Every Technique
One PR. Every technique. Watch the full review workflow in action as we walk through a real feature, catch real issues, fix them, and feed the findings back into our system.
17 min
Access
It's part of Plus. Lesson 1 is free to watch for everyone, no account needed, and so is the brief above.
Every lesson of every course, the full notes, transcripts and prompts, and the Unlearn-built tools. Blog posts and the tools that are public on GitHub stay free for everyone.
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Next step
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