It's the right trade-off, IMO. Most projects won't succeed and the ones that do can be refactored - by real engineers if needed.
An unsuccessful project might be unsuccessful because it got eaten by costs before it became successful.
A wildly successful project is risky to migrate.
If not, then it’s poor price controls.
IIUC Pieter Levels talks a lot about not prematurely optimizing engineering solutions because most ideas will flop.
Most startups fail. Optimizing for getting revenue is more important than optimizing cost in the beginning.
If you get revenue you can solve the cost problem. If you don’t, it doesn’t matter.
Anything that gives you more shots at the goal is a win in a startup.
I've seen many colleagues bootstrap something - even if they're not themselves very technical - because they've leveraged these well integrated low cost platforms.
I think it’s rare that fails to show potential because of the underlying technology that’s chosen.
Sure, Vercel is relatively expensive. But I just don’t see how you’d throw in the towel because the costs are too high without first evaluating how to lower them.
If you’re saying that the evaluation is likely to show that you’re stuck - I have never seen that be the case personally.
All this is to say: even if all progress on AI halted today, it would remain the case that, after the Internet, LLMs are the most impactful thing to happen to software development in my career. It would be weird if companies like Supabase weren't thinking about them in their product plans.
I have two main issues, first the tooling is changing so rapidly that as I start to hone in on a process it changes out from under me. The second is verifying the output. I’m at like 90% success rate on getting code generated correctly (if not always faster than I could do it) but boy does that final 10% bite when I don’t notice.
An aside, I think the cloud ought to make your (perhaps especially your) list. At least for me that changed the whole economy of building new software enterprises.
https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
The Internet, LLMs, open source, high-level languages, the cloud --- that would be my top 5.
For “real work” done by a “real engineer”, I approach it almost exactly as you say.
For side projects/personal software that I most likely would have never started pre-llms? I’ll just go full vibe code and see how far I get. Sometimes I have to just delete it, but sometimes it works. That’s cool.