> Specs are meta solutions. They describe the general shape of the solutions by refusing to make any technical decision that would leads to incidental problems and thus only needs to focus on the essential ones.

Yes, this is a feature not a bug. Then, code review ensures that the actual code makes the requisite technical decisions in a desirable way. This is much faster.

> Generating code with AI is rolling the dice every time said generation is done. Proper implementation happens because with making decisions and going down a path, backtracking if necessary when it's no longer working. Going with AI is breaking down that continuity because they restart from scratch everytime.

False. You only do the initial code generation an initial time, and then update the spec to specify (at a high level, ideally) the constraints that are missing. But then you have the AI modify the existing code to meet the new spec, not start from scratch. AI does not "restart from scratch everytime", it takes an updated spec plus existing code and updates the code to match the updated spec.

It's still "making decisions and going down a path," which you call proper implementation. That's the whole point.

The reason people don't bother with specs is that they're extraordinarily verbose, ambiguous, and simplistic at the same time. Which is why we have invented formal notations, because they're short, have one definition, and enough to create the whole thing, if not to understand the why. The latter can still be done in prose.

What a spec is truly useful for is that it lets you manipulate the solution at the idea stage, without tainting it with real world concerns. But to do it requires a lot knowledge about those real world concerns, so that your assumptions are not straight lies.

This is good for iteration. But any implementation ossifies your specs, and while code are more malleable than most, there's a certain points when the specs should be discarded and the actual implementation being the source of truth for any further development. In any project, that is done with Change Request, which only outline the specific area of changes, assuming the rest as being immutable.

> AI does not "restart from scratch everytime", it takes an updated spec plus existing code and updates the code to match the updated spec.

Maybe you can share an example of that workflow and an actual argument that would make it sustainable.

I've written the formal version of a spec (a suite of tests) and if there's one thing that would make the above idea ridiculous is how much wiggle room there is to follow the specs and be at the same time unusable.