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- code I don’t need to model in my head (low risk, follows established conventions, predictable, easy to verify), and
- code I can’t help modelling in my head (business-critical, novel, experimental, or introduces new patterns).
I feel like there’s actually one or two more shades in between.
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Sometimes I think something belongs in the second category, but then it turns out it’s really more like the first.
And sometimes something is second-category, but for the sake of getting things done, it makes more sense to treat it like the first.
If vibe coding keeps evolving, this is probably the path it needs to explore.
I just wonder what we’ll end up discovering along the way.
I think this is exactly the kind of example I wanted to see, so thank you for sharing.
I was thinking about it yesterday and realized that it might actually be worth trying to switch my current project entirely to “vibe development.” That said, I still worry a bit that AI might change the structure or expand the code when all I really want is to tweak a single line or a few expressions—but I’m sure there’s a way to handle that.
I feel the same way. AI coding skills seem to sit somewhere between intermediate and advanced. Unless you’re working in a space where you’ve thought very deeply and developed your own solutions—those “gotcha, you didn’t know this” kinds of problems—it doesn’t really feel like AI falls short.
So far, I’ve been reading through almost 100% of the code AI writes because of the traps and edge cases it can introduce. But now, it feels less like “AI code is full of pitfalls” and more like we need to focus on how to use AI properly.
Until recently, I thought that complex, multi-domain platforms were still relatively safe. But today, I’m seriously reconsidering and thinking about whether I should switch to a “vibe coding” approach.
I should also consider isolating the custom logic in the existing codebase as much as possible, converting it into general logic, and then testing the “vibe” approach directly.
For me, this isn’t just a curiosity—it’s a question of whether I need to completely change the way I work. Given the same conditions, I’d rather revisit the domain knowledge and get better at instructing AI than write everything by hand.
Outside the areas AI struggles with or really deep domain expertise, I feel like comparing productivity just doesn’t make sense anymore.