How pdlc-skills Keeps Quality Up When AI Writes the Code

Useful takeaways from this story.

The faster it runs, the sharper an old question gets: who vouches for the quality of what the AI produces?

That's why in pdlc the model's self-check is recorded in its own column and never feeds into any stop-or-continue decision.

This post is about how I handle that in pdlc: not with one gate, but with a chain of seven links.

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The useful part

This post is about how I handle that in pdlc: not with one gate, but with a chain of seven links. The faster it runs, the sharper an old question gets: who vouches for the quality of what the AI produces? Why quality matters more when AI writes the code Code quality used to rest on two things: the person writing it had a feel for whether it was right, and there wasn't so much of it that reviewers couldn't keep up.

How it works

It has no "feel for whether it's right." Ask an AI to grade its own work and it grades generously.
That's why in pdlc the model's self-check is recorded in its own column and never feeds into any stop-or-continue decision.
It clearly can't be a human reading every line, because that hands back the time you just saved.
Requirements в†' Design в†' TDD в†' Implementation в†' Unit tests в†' E2E в†' Review by a different AI The first two are written by AI, reviewed by AI, and checked once by a human at the end.

What to take from it

The middle four are enforced by machine with no room for argument: TDD sets t...

Details worth keeping

In one afternoon it can write more code than a person can review in days. The faster you go, the further a mistake travels before anyone notices.

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