u/zonayedahmed

I’ll be honest, after trying different AI agents and all kinds of workflows, frontend feels like the easiest part to hand over to AI, but also the hardest part to actually perfect.

AI agents can usually build the UI, wire things up, follow instructions, and get something working pretty quickly. But there are almost always small to medium imperfections: spacing issues, inconsistent states, weird responsive behavior, slightly off interactions, unnecessary complexity, or code that technically works but doesn’t feel clean.

And then you either have to keep prompting again and again, or manually adjust the codebase yourself.

The frustrating part is that when these small issues pile up, fixing them can take almost as much time as just doing the work by hand from the beginning.

Maybe this is more true for frontend because “done” is not just about the code working. It also has to feel right visually, behave well across states, and match the product taste.

Are you guys feeling the same? How are you handling frontend work with AI agents right now?

A pattern I keep running into in frontend-heavy Next.js projects:

You don’t always need a full backend, but you still need some public API-like data for the frontend.

Things like:

pricing/config data

changelog feeds

docs metadata

directory/listing data

public content APIs

cached output from external APIs

For small-to-medium read-heavy data, the options usually become raw JSON files, Route Handlers, serverless functions, CMS APIs, object storage/CDN, or a small backend.

All of them work, but sometimes they feel either too manual or too much infrastructure for the problem, especially when the data still needs predictable updates after a source data change, on an interval, or after some event.

Curious how other Next.js builders handle this:

Do you usually keep these as JSON files?

Use Route Handlers/serverless functions?

Use a CMS or external API?

Push generated JSON to object storage/CDN?

Or something else?

Also, where do you draw the line between “just use a JSON file” and “this needs a real backend”?

So, what does full-stack web development even mean with AI around these days? I mean, if I say I'm a full-stack web developer, I should probably be handling the frontend, backend, database, deployments, and all that jazz. But now, with AI advancing so much, what skills are a must for someone who wants to call themselves a full-stack web developer? Should we also be thinking about product engineering, like what architecture to pick for our projects? And should we even start thinking about shipping, the business side of things, and working with distributions? What do you all think, where should this full-stack development process begin and end now?

I've been thinking about this a lot lately, and I bet the people who've built their careers in this field are too. On one hand, AI has really sped up development and made us way more efficient in different parts of a project. But at the same time, it's also turned a five-person job into something one or two people can handle, which is a bit scary to think about, right? What do you guys make of all this, and what do you see for the future of a web developer?

Earlier I asked what’s hardest about building side projects now that AI makes implementation easier.

Most people said: distribution.

It was hard before, but now it feels even harder because everyone can ship faster.

I know different projects need different strategies, but I don’t want to stay ignorant about distribution.

Where should a builder start?

AI seems pretty good at frontend stuff, except when it comes to custom designs, UI, or UX requirements. And making a UI perfect is a huge deal in frontend, which AI can't quite nail yet unless it's using existing UI libraries. So I'm torn: part of me thinks maybe customers don't care how the frontend is made, as long as it works for them. But then, from a product's UI and UX perspective, it's super important for it to have its own unique design language, which existing UI libraries can't provide. And AI can't handle that part properly yet. So, is frontend the biggest victim of AI, or is this just the MVP phase that AI has covered?

Since AI has made it fairly easy to make a project now, what is the hardest struggle do you people face now?

Thanks in Advance