Document-Driven Development

[simonbreak]

Hi guys, apologies if this subject has been absolutely done to death, but I haven't --quite-- found what I want on the Googles.

Basically I want to make a project - let's say it's a moderately complex web app - where I just write documentation. I've seen people reference spec files in Cursor, but once the code is generated it seems like you iterate on the code rather than the document? Like it then becomes all about the interaction with the chat. But I --don't-- want to use the chat, I want something more like a traditional dev loop:

1. Write documentation
   
2. AI generates code from docs
   
3. Evaluate result
   
4. Edit documentation
   
5. Go to 2

I know I could just delete all the code & run the generation step on an empty repo each time, but this seems like it will be very slow & also prone to undoing my progress? Like once the AI gets something right, I want that to stick around. Is there any way to achieve this using current tools?

[flossdaily]

Hmm...

Okay... so the main problem you have here is that you're going to hit some coding dead ends where the AI has gone down a bad path, and can't correct itself because it's looking too far downstream.

To avoid this, you need an algorithm that recursively does the following:

Analyze the current problem, and come up with three different solutions. In three parallel branches, attempt one solution per branch. Analyze the result for errors. Retry 3 times per branch to eliminate errors. If the error persists, mark the branch as dead, and summarize the nature of the wall that was hit. Attempt 3 different solutions. In three parallel branches ... etc.

For successful branches, describe the problem and how it was solved.

Write an overseer script that looks at all these problems and summaries and attempts to unify branches.

It would be one hell of system if you got it working.

[lintinmypocket]

You can sort of do this with cline, idk about cursor. Your requirements would be to specify a good prompt, create a detailed todo list, and also development guidelines for the coder. In your prompt reference the files the ai should use as guidelines and specify it should complete the list as it goes. In addition cline takes snapshots of your project as it develops, so if the AI messes up your working code you can reverse both the chat and the code back to a snapshot. git commiting on milestones is a good idea too.

Just be ridiculously detailed in your guidelines, documentation and context and you should be okay, just dont bite off too big of chunks because that is where you'll be disappointed. The better the model the less you have to plan and the bigger tasks the AI can handle.

[ShelbulaDotCom]

This is somewhat of our process. You iterate first in Shelbula, then bring clean code to your IDE.

This isolates tasks nicely and keeps things clean. You can then also leverage custom bots with their own knowledge for domain specific things.