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hellovai | 5 months ago

if you haven't tried the research -> plan -> implementation approach here, you are missing out on how good LLMs are. it completely changed my perspective.

the key part was really just explicitly thinking about different levels of abstraction at different levels of vibecoding. I was doing it before, but not explicitly in discrete steps and that was where i got into messes. The prior approach made check pointing / reverting very difficult.

When i think of everything in phases, i do similar stuff w/ my git commits at "phase" levels, which makes design decision easier to make.

I also do spend ~4-5 hours cleaning up the code at the very very end once everything works. But its still way faster than writing hard features myself.

discuss

order

0xblacklight|5 months ago

tbh I think the thing that's making this new approach so hard to adopt for many people is the word "vibecoding"

Like yes vibecoding in the lovable-esque "give me an app that does XYZ" manner is obviously ridiculous and wrong, and will result in slop. Building any serious app based on "vibes" is stupid.

But if you're doing this right, you are not "coding" in any traditional sense of the word, and you are *definitely* not relying on vibes

Maybe we need a new word

simonw|5 months ago

I'm sticking to the original definition of "vibe coding", which is AI-generated code that you don't review.

If you're properly reviewing the code, you're programming.

The challenge is finding a good term for code that's responsibly written with AI assistance. I've been calling it "AI-assisted programming" but that's WAY too long.

dhorthy|5 months ago

alex reibman proposed hyperengineering

i've also heard "aura coding", "spec-driven development" and a bunch of others I don't love.

but we def need a new word cause vibe coding aint it

chickensong|5 months ago

AI is the new pAIr programming.

giancarlostoro|5 months ago

> but not explicitly in discrete steps and that was where i got into messes.

I've said this repeatedly, I mostly use it for boilerplate code, or when I'm having a brain fart of sorts, I still love to solve things for myself, but AI can take me from "I know I want x, y, z" to "oh look I got to x, y, z in under 30 minutes, which could have taken hours. For side projects this is fine.

I think if you do it piecemeal it should almost always be fine. When you try to tell it to do two much, you and the model both don't consider edge cases (Ask it for those too!) and are more prone for a rude awakening eventually.