71–80 of 133 posts
Congrats on the 1.0 milestone! I had a Show HN that built with Instant: https://news.ycombinator.com/item?id=44247029 The common request from that thread was to add guest auth, and few months later Instant had it baked in, so it was really easy to add that feature. Great dev experience :)
An honest question - why would we need any frameworks at all for vibe coded apps? I can just tell the coding agent to use pure HTML5/Vanilla JS/CSS on the frontend and pure whatever on the backend and it would do it. No need for hundreds/thousands dependencies. For deployment I can ask the coding agent to do the same.
More code in the context window doesn't just increase the cost, it also degrades the overall performance of the LLM. It will start making more mistakes, cause more bugs, add more unnecessary abstractions, and write less efficient code overall.
You'll end up having to spend a significant amount of time guiding the AI to write a good framework to build on top of, and at that point you would have been better off picking an existing framework that was included in the training set.
Maybe future LLMs will do better here, but I wouldn't recommend doing this for anything larger than a landing page with current models.
An honest question - why would we need any frameworks at all for vibe coded apps? I can just tell the coding agent to use pure HTML5/Vanilla JS/CSS on the frontend and pure whatever on the backend and it would do it. No need for hundreds/thousands dependencies. For deployment I can ask the coding agent to do the same.
An honest question - why would we need any frameworks at all for vibe coded apps? I can just tell the coding agent to use pure HTML5/Vanilla JS/CSS on the frontend and pure whatever on the backend and it would do it. No need for hundreds/thousands dependencies. For deployment I can ask the coding agent to do the same.
I kid but any reason you can think of applies to app development too.
1. Good abstractions decrease verbosity and improve comprehension
2. Raw HTML/CSS/JS are out of distribution just like assembly (no one builds apps like this)
3. Humans need to understand and audit it
4. You'll waste time and tokens reinventing wheels
This inuitively makes sense. LLMs mimic human behavior and thought, so for all the reasons you'd get lost in a pile of web spaghetti or x86, so would an LLM.
Earlier quoted context omitted.
You don't necessarily, but each token costs money for the AI to spit out. And probably more money when that output is used as input later. Delegating to a library makes sense financially.
With local inference on pretty decent local models we have nowadays (Qwen-3.5 and better) it's not much of a concern anymore.
What's the difference between Instant and Convex?
Sending you guys lots of love and best of luck!