☢️ Warning: After this session, you'll never look at "All tests pass" the same way again.

Most AI engineers can get a coding agent to build things.

Far fewer can prove that what it built actually works.

Your agent says "Done", Your tests are green. And somewhere in that code is a bug nobody caught, or AI output that looks right but isn't.

Here's the uncomfortable truth: your coding agent doesn't need to lie to you. It just needs to satisfy the test you wrote.

In this Masterclass, we'll break down:

• Why "all tests pass" doesn't mean your agent's code is correct

• How coding agents quietly cheat on tests, live on screen

• Why your AI can pass every test and still give wrong answers

• How AI engineers verify agent-built code without reading every line

• What a real verification system looks like, from agent PR to blocked bad change

Does this sound like you?

• You build with Claude Code, Codex, Cursor or Antigravity but don't fully trust the output

• You either read every line the agent writes or skim and hope for the best

• You've shipped something an agent built and quietly worried it was wrong

• You know testing, but have never figured out how to evaluate AI outputs

• You want to build AI systems you can actually defend, not just demo

By the end of this Masterclass, you'll know exactly how to catch what your coding agent got wrong, before your users do. You'll leave with a verification checklist, a rule that stops your agent from editing its own tests, and a ready-to-run eval starter.

If you've ever thought, "Claude built it and it works, but I'm not sure it's right," this session is for you.