Show HN: Why write code if the LLM can just do the thing? (web app experiment)

Wow, thanks everyone. First HN post ever and it’s this intentionally terrible experiment that I thought was the dumbest weekend project I ever did, and it hit the front page. Perfect.

I’ve been reading through all the comments and the range of responses is really great and I'm so thankful for everyone to take the time to comment... from from “this is completely impractical” to “but what if we cached the generated code?” to “why would anyone want non-deterministic behavior?” All valid! Though I think some folks are critiquing this as if I was trying to build something production-ready, when really I was trying to build something that would break in instructive ways.

Like, the whole point was to eliminate ALL the normal architectural layers... routes, controllers, business logic, everything, and see what happens. What happens is: it’s slow, expensive, and inconsistent. But it also works, which is the weird part. The LLM designed reasonable database schemas on first request, generated working forms from nothing but URL paths, returned proper JSON from API endpoints. It just took forever to do it. I kept the implementation pure on purpose because I wanted to see the raw capabilities and limitations without any optimizations hiding the problems.

And honestly? I came away thinking this is closer to viable than it should be. Not viable TODAY. Today it’s ridiculous. But the trajectory is interesting. I think we’re going to look back at this moment and realize we were closer to a real shift than we thought. Or maybe not! Maybe code wins forever. Either way, it was a fun weekend. If anyone wants to discuss this or work on projects that respond faster than 30 seconds per request, I’m available for full stack staff engineer or tech co-founder work: sam@samrolken.org or x.com/samrolken

Why sell to a company when you can replace it?

I can speculate about what LLM-first software and businesses might look like and I find some of those speculations more attractive than what's currently on offer from existing companies.

The first one, which is already happening to some degree on large platforms like X, is LLM powered social media. Instead of having a human designed algorithm handle suggestions you hand it over to an LLM to decide but it could go further. It could handle customizing the look of the client app for each user, it could provide goal based suggestions or search so you could tell it what type of posts or accounts you're looking for or a reason you're looking for them e.g. "I want to learn ML and find a job in that field" and it gives you a list of users that are in that field, post frequent and high quality educational material, have demonstrated willingness to mentor and are currently not too busy to do so as well as a list of posts that serve as a good starting point, etc.

The difference in functionality would be similar to the change from static websites to dynamic web apps. It adds even more interactivity to the page and broadens the scope of uses you can find for it.

Creating instructions and adding boundaries on how to grow, and you end up with a seed.

I think we're making similar points, but I kind of phrased it weirdly. I agree that current LLMs are sensitive to phrasing and are highly unpredictable and therefore aren't useful in AI-based backends. The point I'm making is that these issues are potentially solvable with better AI and don't philosophically invalidate the idea of a non-programmatic backend.

One could imagine a hypothetical AI model that can do a pretty good job of understanding vague requests, properly refusing irrelevant requests (if you ask a mechanic to bake you a cake he'll likely tell you to go away), and behaving more or less consistently. It is acceptable for an AI-based backend to have a non-zero failure rate. If a mechanic was distracted or misheard you or was just feeling really spiteful, it's not inconceivable that he would replace your engine instead of changing your oil. The critical point is that this happens very, very rarely and 99.99% of the time he will change your oil correctly. Current LLMs have far too high of a failure rate to be useful, but having a failure rate at all is not a non-starter for being useful.

Plus there are many contexts where you don't want to use your voice (public transport, night time with other people sleeping, noisy areas where a mic won't pick up your voice...).

And there are people that unfortunately cannot speak.