Originally published at tddbuddy.com.
AI writes code in seconds.
That's not the hard part anymore.
The hard part is knowing whether the code is correct. Whether it handles the edge case on line 247. Whether it respects the business rule that $99.99 orders don't get free shipping but $100 orders do.
Code review won't save you here.
Not at AI speed.
The Review Bottleneck Was Already Broken
Most teams don't review code carefully. They skim. They pattern match. They approve because they're behind.
That was true before AI.
Now an agent generates 500 lines in 30 seconds, and the same reviewer who was already skimming is supposed to reason about all of it?
They won't. Nobody does.
The ritual stays. The protection fades.
And here's the part nobody wants to say out loud: code review was never the safety net we pretended it was. Studies consistently show review catches about 60% of defects. The easy ones. The ones tests would have caught anyway.
Review is a social ritual dressed up as a quality gate.
Tests Are Specifications, Not Afterthoughts
This is where the mental shift happens.
Stop thinking of tests as something you do after writing code. Tests are the specification. The executable description of what the system must do.
When you write tests first, you're not "slowing down to test."
You're defining the contract.
- What are the inputs?
- What are the boundaries?
- What happens at the edges?
- What does "done" look like?
That contract is machine-readable. Any agent can code against it. Any CI pipeline can verify it. Any deployment can be validated by it.
A failing test suite is the clearest possible brief you can give an AI: here's exactly what's wrong, go fix it.
That's a tighter feedback loop than any human reviewer provides.
The Build-Test-Feedback Loop
The workflow that actually scales:
- Define the contract: write tests that specify behavior
- Let AI generate: speed is its strength
- Run the tests: instant, objective, complete
- Red? AI iterates: the failing test is the feedback
- Green? Ship it: the tests are the review
No PR sitting in a queue for 3 days. No rubber stamps. No reviewer missing the off-by-one error buried in a refactor.
The tests catch it or they don't.
And if your tests are good, they catch it.
Why This Matters Now
Teams practicing TDD will adopt AI agents faster and more safely than teams relying on code review.
Not because TDD is trendy.
Because the test suite is the interface layer between human intent and machine execution.
Without tests, an AI agent is generating code into the void. It has no feedback. No definition of done. Every PR it opens requires full human inspection, which defeats the entire point of automation.
With tests, the agent has everything it needs:
- Failing tests tell it what to build
- Passing tests tell it when it's done
- Test output tells it what went wrong
That's a complete feedback loop. No human required until the end.
The Uncomfortable Conclusion
If your codebase doesn't have good test coverage, it's not ready for AI agents.
You can generate all the code you want. Without automated verification, you're just producing unreviewed changes faster.
That's not productivity. That's risk accumulation with better tooling.
TDD isn't about slowing down. It never was.
It's about building the scaffolding that makes speed survivable.
The tests are the guardrail. AI is the engine. You're the architect.
And architects don't review every brick. They design structures that stand up on their own.
