I recently put out a video arguing that frontend development is changing. I don't think the work is going away. The frontend developer title is wha...
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I don't think so as well. Although it is easier to do front-end with AI, it's easy to miss some important aspects of what makes a good front-end. One is accessibility, optimization, etc.
If you prompt the front-end generally, you tend to miss these since it's not really there for you to see. You have to make sure you test the front-end design to see if it's accessible, which can vary depending on who your audience is. You also have to take care of optimization, which is difficult since it depends on browser and one's computer specs.
Even when done with detail prompts, it's a similar experience since you are focus on the looks and not about if it's a good design in general.
Overall, AI makes it easier to create front-end designs, but it's important to catch as many edge cases as you can which is part of the human aspect. Sure, AI can take care of those edge cases, but you never know until you try it yourself.
Great writeup Erik!!
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Hi, interesting and maybe quite controversial topic.
I want to say, i hope we are not cooked! yet the way we develop is certainly changing. I liked the comments you mentioned above.
AI makes things easier, and can certainly extend one's skills-set a lot. But i love them best for i can learn much faster and quicker.
My thought is very much inline with the intent of your post (with a few exceptions on some specifics) 🥰
There are so many things I have to say on this topic, that I often just don't say much 🤣
This is my prediction: AI has the potential to replace all knowledge base workers, with the only exception of really good Software Engineers and Programming Ninjas (I'm separating SWE and Programmers for very good reasons too).
Of course, the exception part is exaggerated to prove a point. But in reality, I too think that AI will NOT replace anyone with deep foundational human knowledge. So, becoming very good at a few things, and having decent amount of knowledge on many other things will be extremely beneficial.
I have a post in my draft that somewhat explains why I think that.
I'll add the link to that post once I publish it.
We need more of these sort of posts to prevent AI CEOs misguiding new generations for their own financial gains. While AI is useful, it can never be replacement for human knowledge and creativity. It can only augment human capabilities.
BTW, before I complete that post, here's a short one: 😁
We Don't Need to Learn or Use Basic Math / Arithmetic Anymore 😜
Really enjoyed this one. The ErikAmp example makes the point pretty clearly: AI is getting surprisingly good at producing the visible part of frontend work.
But frontend isn’t just a collection of screens. It’s a system of states, interactions, constraints, and user decisions.
Take a checkout page. An AI can generate a polished payment form very quickly, but what happens when the payment request times out after the user clicks Pay? Do we show “Payment failed” when the bank actually received it? What happens if they refresh and submit again? Does the UI preserve the correct order state? Can they recover without creating a duplicate payment?
The same thing happens with something much simpler like a search box. The happy path is easy. The interesting part starts when the API is slow, returns nothing, returns 500, the user changes the query while the previous request is still running, or the result arrives out of order.
That’s where I think frontend engineering becomes more than implementation. AI can produce the screen, but someone still has to understand the state machine behind the screen and decide what should happen when reality stops following the happy path.
AI is making frontend implementation cheaper. It also makes good judgment more visible.
The title change matches what I see. Vue on the front with Laravel behind it is what I write every day, and the work never cared which half I was in that week.
If AI takes anything first, I'd bet on the glue between the two halves: forms wired to endpoints, validation written twice. Deciding what the endpoint should do at all stays with us.
Great read! I think frontend development is changing, but not disappearing. AI can generate components and layouts surprisingly well, yet translating business requirements into a reliable, accessible, and maintainable product still requires human judgment.
In my experience with open-source projects, the hardest part is rarely writing the initial code. It's understanding trade-offs, edge cases, and long-term maintenance. AI helps with implementation, but ownership and decision-making remain human responsibilities.
I've been shipping frontend with AI agents for about 18 months and the "generic Tailwind look" gap is closing faster than people think. Last month I had a designer friend review two landing pages — one I hand-coded, one Claude generated — and he picked the AI one as more polished. Taste still matters but it's becoming a steering skill, not a pixel-pushing skill. The real moat isn't design, it's knowing the stack well enough to debug when the agent confidently breaks something subtle.
The ErikAmp and 5K coach examples make a useful distinction: matching an existing interface and designing a new workflow are different tests. I would separate visual fidelity from interaction fidelity in the player: pause midway, seek, change the playlist, then use only the keyboard and check what keeps its state. For the coach, the equivalent question is whether someone can understand and complete today’s session without interpreting the whole weekly plan. That gives the agent a concrete user task to improve, rather than another theme to generate.
Take a look at this!. It ushers in the end of web frameworks. It is fully A.I. Compatible has been tested over 10,000 times, fully async, all native JavaScript and semantic html, no bundler, no build required.
the 62 year old developer's framing is the part that holds. agents are good at CRUD, not at knowing when the task is wrong. someone who catches that is still in the loop because the model cannot fire itself.
the UI observation tracks for now. the generic Tailwind look has gotten harder to spot. but give it a layout that needs to respect an existing design system with real constraints and it gets conservative in the wrong direction.
what's the use case where a newer model actually solved a real design constraint, not just a visual one?
Frontend is the closest the user is to a working software. Frontend developers are what makes the design not only usable but "human-friendly". AI without context would be having a hard time in that scenario.
The bit about older models having a spottable generic Tailwind look is a good tell, and it points at the harder problem: the taste you describe, catching an accessibility issue or sensing a flow will bog users down, is exactly what no quick check catches, so an AI-built UI passes a glance and still feels off in use. Did rebuilding Winamp with Kiro move where you draw the line on what the agent decides versus what you review?
What did the generated test suite miss in ErikAmp that you caught through manual UI review?
I think there are professionals here so I think it's a good place to ask my question
How did you learn each frontend library and become a professional at it?
Not in my min it is right. Thanks