alt Hacker News> the workflow I’ve settled into is radically different from what most people do with AI coding tools
This looks exactly like what anthropic recommends as the best practice for using Claude Code. Textbook.
It also exposes a major downside of this approach: if you don't plan perfectly, you'll have to start over from scratch if anything goes wrong.
I've found a much better approach in doing a design -> plan -> execute in batches, where the plan is no more than 1,500 lines, used as a proxy for complexity.
My 30,000 LOC app has about 100,000 lines of plan behind it. Can't build something that big as a one-shot.
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This is actually embarrassing. His "radically different" workflow is... using the built-in Plan mode that they recommend you use? What?
> design -> plan -> execute in batches
This is the way for me as well. Have a high-level master design and plan, but break it apart into phases that are manageable. One-shotting anything beyond a todo list and expecting decent quality is still a pipe dream.
> if you don't plan perfectly, you'll have to start over from scratch if anything goes wrong.
You just revert what the AI agent changed and revise/iterate on the previous step - no need to start over. This can of course involve restricting the work to a smaller change so that the agent isn't overwhelmed by complexity.
100,000 lines is approx. one million words. The average person reads at 250wpm. The entire thing would take 66 hours just to read, assuming you were approaching it like a fiction book, not thinking anything over
How can you know that 100k lines plan is not just slop?
Just because plan is elaborate doesn’t mean it makes sense.
wtf, why would you write 100k lines of plan to produce 30k loc.. JUST WRITE THE CODE!!!
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Dunno. My 80k+ LOC personal life planner, with a native android app, eink display view still one shots most features/bugs I encounter. I just open a new instance let it know what I want and 5min later it's done.
if you don't plan perfectly, you'll have to start over from scratch if anything goes wrong
This is my experience too, but it's pushed me to make much smaller plans and to commit things to a feature branch far more atomically so I can revert a step to the previous commit, or bin the entire feature by going back to main. I do this far more now than I ever did when I was writing the code by hand.
This is how developers should work regardless of how the code is being developed. I think this is a small but very real way AI has actually made me a better developer (unless I stop doing it when I don't use AI... not tried that yet.)