It's a new skill that takes time to learn. When I started on gpt3.5 it took me easily 6 months of daily use before I was making real progress with it.
I regularly generate and run in the 600-1000LOC range.
Not sure you would call it "vibe coding" though as the details and info you provide it and how you provide it is not simple.
I'd say realistically it speeds me up 10x on fresh greenfield projects and maybe 2x on mature systems.
You should be reading the code coming out. The real way to prevent errors is read the resoning and logic. The moment you see a mistep go back and try the prompt again. If that fails try a new session entirely.
Test time compute models like o1-pro or the older o1-preview are massively better at not putting errors in your code.
Not sure about the new claude method but true, slow test time models are MASSIVELY better at coding.
The “go back and try the prompt again” is the workflow I’d like to see a UX improvement on. Outside of the vibe coding “accept all” path, reverse traversing is a fairly manual process.
Having full control over inputs and if something goes wrong starting a new chat with either narrower scope or clearer instructions is basically AGI level work.
There is nobody but a human for now that can determine how bad an LLM actually screwed up its logic train.
But maybe you mean pure UI?
I could forsee something like a new context creation button that gives a nice UI of what to bring over and what to ditch from the UI as pretty nice.
Maybe like a git diff looking method? Drop this paragraph bring this function by just simple clicks would be pretty slick!
I deffinetly see a future of better cross chat context connections and information being powerful. Basically git but for every conversation and cpde generated for a project.
Would be crazy hard but also crazy powerful.
If my startups blows up I might try something like that!
I regularly generate and run in the 600-1000LOC range.
Not sure you would call it "vibe coding" though as the details and info you provide it and how you provide it is not simple.
I'd say realistically it speeds me up 10x on fresh greenfield projects and maybe 2x on mature systems.
You should be reading the code coming out. The real way to prevent errors is read the resoning and logic. The moment you see a mistep go back and try the prompt again. If that fails try a new session entirely.
Test time compute models like o1-pro or the older o1-preview are massively better at not putting errors in your code.
Not sure about the new claude method but true, slow test time models are MASSIVELY better at coding.