Kent Beck argues that the claim "AI is better at coding than humans" is nonsense: LLMs (which he calls "the genie") produce plausible code that often doesn't actually work, so programmers and buyers now need an adversarial posture toward AI-generated software. His central model is a tradeoff between features (visible progress) and futures (optionality to change), and he says the real skill is pausing between features to restore optionality rather than racing to the zero-option mess that AI now lets you reach in a week instead of a decade. He dismisses spec-driven development as rebranded waterfall, explains why formal methods still leave a gap, and closes by warning that lines of code and PR counts measure effort and output, never mission.
- Beck calls the claim that AI is better at coding than humans "boulderdash": the genie produces syntactically correct, plausible programs that frequently don't work, citing the $10,000-in-tokens "C compiler" that can't actually compile hello world.
- Trustworthiness you used to be able to infer from code — built-by-construction correctness, whole classes of bugs being impossible — can no longer be assumed, so you must take a cynical, adversarial stance toward AI output.
- The craft activities Beck wrote three books about (naming, decomposition, structuring for human readability) have lost much of their leverage, though readable systems are still preferable because the genie can explain code faster.
- His core model: every project trades futures (options for change) for features; keep spending futures and you reach zero optionality — a state that used to take 100 people 10 years and now takes one person one week.
- The fix is alternating rhythm — implement a feature, then refactor, remove duplication, or throw the work away and redo it to rebuild futures — because "you can't wipe the knife while you're cutting."
- Spec-driven development is waterfall under a new name; Royce's original paper said on the same page that it doesn't work, and the people excited about one-shot specs "don't sound like they've ever had a billion users."
- Formal methods have two problems for Beck: they feel one-shot and discourage change, and there's still an unbridged gap between a verified specification and a running implementation.
- Measuring effort (lines of code) or output (PR count) is by definition not measuring mission, and Goodhart's law is worse than advertised — people distort the system and lose actual mission progress, not just visibility.
- The best software he's worked on came from maximizing learning and throwing off software as a side effect, illustrated by Ward Cunningham switching off the computer and the pair rebuilding an afternoon's work in 15 minutes the next morning.
The sharpest framing of the features-versus-futures model and the clearest statement of how AI accelerates the wrong thing.
It used to take us a hundred people 10 years to get to this absolute zero state where we can't make any changes without breaking something else. And now with AI, I can do this in the privacy of my own office. One person, one week, and I can make a complete mess.
Beck connects today's hottest AI workflow to a failure mode the industry already documented and forgot, including what Royce's own paper said.
There's such a temptation in spec-driven development to go down the path of I'm going to write a spec and the genie is going to produce the software and if the spec is good enough, the software is going to be good enough. And there's a word for that. That's exactly waterfall development.
I call it the genie because it grants your wishes, but it ends up not being what you really wanted.
Genie is really good at plausible, but actually working, no.
You can't wipe the knife while you're cutting.
Anything which is a measure of effort or a measure of output is per definition not a measure of mission.
This is a learning process that throws off software as a side effect.