Test-Driven Development with Python, 3rd Edition

Preface to the Third Edition: TDD in the Age of AI

Is there any point in learning TDD now that AI can write code for you? A single prompt could probably generate the entire example application in this book, including all its tests, and the infrastructure config for automated deployment too.

The truth is that it’s too early to tell. AI is still in its infancy, and who knows what it’ll be able to do in a few years or even months’ time.

AI Is Both Insanely Impressive and Incredibly Unreliable

What we do know is that right now, AI is both insanely impressive and incredibly unreliable.

Beyond being able to understand and respond to prompts in normal human language—it’s easy to forget how absolutely extraordinary that is; literally science-fiction a few years ago—​AI tools can generate working code, they can generate tests, they can help us to break down requirements, brainstorm solutions, quickly prototype new technologies. It’s genuinely astonishing.

As we’re all finding out though, this all comes with a massive “but”. AI outputs are frequently plagued by hallucinations, and in the world of code, that means things that just won’t work, even if they look plausible. Worse than that, they can produce code that appears to work, but is full of subtle bugs, security issues, or performance nightmares. From a code quality point of view, we know that AI tools will often produce code that’s filled with copy-paste and duplication, weird hacks, and undecipherable spaghetti code that spells a ...