So instead of asking yourself, “How can I write code that does what I want?” Consider asking yourself, “Can I write code that ties together things the browser already does to accomplish what I want (or close enough to it)?”
Every engineer eventually overbuilds something. You think you’re being smart. You’re thinking ahead, building for growth and before you know it, you’ve created a system ten times heavier than your actual problem. That’s the trap. We keep designing for imaginary futures for scale that may never come and call it engineering. But it’s not engineering. It’s over-engineering.
The industry rewards it too. Nobody gets promoted for keeping things small and sane. You get promoted for complexity.
I prefer my tools to help me with repetitive tasks (and there are many of those in programming), understanding codebases, and authoring correct programs. I take offense at products that are designed to think for me. To remove the agency of my own understanding of the software I produce, and to cut connections with my coworkers. Even if LLMs lived up to the hype, we would still stand to lose all of that and our craft.
A microwave isn’t going to take your job; a chef who knows how to use a microwave is going to take your job.
When you vibe code, you are incurring tech debt as fast as the LLM can spit it out. Which is why vibe coding is perfect for prototypes and throwaway projects: It’s only legacy code if you have to maintain it!
The worst possible situation is to have a non-programmer vibe code a large project that they intend to maintain. This would be the equivalent of giving a credit card to a child without first explaining the concept of debt.
If you don’t understand the code, your only recourse is to ask AI to fix it for you, which is like paying off credit card debt with another credit card.
The short version of what I want to say is: vibe coding seems to live very squarely in the land of prototypes and toys. Promoting software that’s been built entirely using this method would be akin to sending a hacked weekend prototype to production and expecting it to be stable.
Remy is taking a very sensible approach here:
I’ve used it myself to solve really bespoke problems where the user count is one.
Would I put this out to production: absolutely not.
Here’s what the “AI will replace developers” crowd fundamentally misunderstands: code is not an asset—it’s a liability. Every line must be maintained, debugged, secured, and eventually replaced. The real asset is the business capability that code enables.
If AI makes writing code faster and cheaper, it’s really making it easier to create liability. When you can generate liability at unprecedented speed, the ability to manage and minimize that liability strategically becomes exponentially more valuable.
This is particularly true because AI excels at local optimization but fails at global design. It can optimize individual functions but can’t determine whether a service should exist in the first place, or how it should interact with the broader system. When implementation speed increases dramatically, architectural mistakes get baked in before you realize they’re mistakes.
Frankly, I’d rather quit my career than live in the future they’re selling. It’s the sheer dystopian drabness of it. Mediocrity as a service.
I tried the tab-completion slot machines; not my cup of tea. I tried image generation and was overcome with literal depression. I don’t want a future as a “prompt artist”.
I’m mostly linking this for what it says, but oh boy, do I love the way it says it with this wonderful HTML web compenent.
I heard you like divs…
Instead of that deep immersion where I’d craft each function, I’m now more like a curator? I describe what I want, evaluate what the AI gives me, tweak the prompts, and iterate. It’s efficient, yes. Revolutionary, even. But something essential feels missing — that state of flow where time vanishes and you’re completely absorbed in creation. If this becomes the dominant workflow across teams, do we risk an industry full of highly productive yet strangely detached developers?
Here’s the main problem I’ve found with generative AI, and with “vibe coding” in general: it completely sucks out the joy of software development for me.
I hate the way they’ve taken over the software industry, I hate how they make me feel while I’m using them, and I hate the human-intelligence-insulting postulation that a glorified Excel spreadsheet can do what I can but better.
We’re at a point in the most ecosystems where pulling in libraries is not just the default action, it’s seen positively: “Look how modular and composable my code is!” Actually, it might just be a symptom of never wanting to type out more than a few lines.
It always amazes me when people don’t view dependencies as liabilities. To me it feels like the coding equivalent of going to a loan shark. You are asking for technical debt.
There are entire companies who are making a living of supplying you with the tools needed to deal with your dependency mess. In the name of security, we’re pushed to having dependencies and keeping them up to date, despite most of those dependencies being the primary source of security problems.
But there is a simpler path. You write code yourself. Sure, it’s more work up front, but once it’s written, it’s done.
The moment you run LLM generated code, any hallucinated methods will be instantly obvious: you’ll get an error. You can fix that yourself or you can feed the error back into the LLM and watch it correct itself.
Compare this to hallucinations in regular prose, where you need a critical eye, strong intuitions and well developed fact checking skills to avoid sharing information that’s incorrect and directly harmful to your reputation.
With code you get a powerful form of fact checking for free. Run the code, see if it works.
Working on this project is great but ten minutes into it and I already miss the resilience of the web. I miss how you have to really fuck things up to make a browser yell at you or implode.
Want to use all those great features that have been in landing in browsers over the past year or two? View transitions! Scroll-driven animations! So much more!
Well, your coding co-pilot is not going to going to be of any help.
Large language models, especially those on the scale of many of the most accessible, popular hosted options, take humongous datasets and long periods to train. By the time everything has been scraped and a dataset has been built, the set is on some level already obsolete. Then, before a model can reach the hands of consumers, time must be taken to train and evaluate it, and then even more to finally deploy it.
Once it has finally released, it usually remains stagnant in terms of having its knowledge updated. This creates an AI knowledge gap. A period between the present and AI’s training cutoff. This gap creates a time between when a new technology emerges and when AI systems can effectively support user needs regarding its adoption, meaning that models will not be able to service users requesting assistance with new technologies, thus disincentivising their use.
So we get this instead:
I’ve anecdotally noticed that many AI tools have a ‘preference’ for React and Tailwind when asked to tackle a web-based task, or even to create any app involving an interface at all.
Detective stories and tales of bughunting in software and hardware.
Sometimes bugs have symptoms beyond belief. This is a collection of such stories from around the web.
Many interactions are not possible without JavaScript, but that doesn’t mean we should look to write more than we have to. The server doing something useful is a requirement for building an interesting business. The client doing something is often a nice-to-have.
There’s also this:
It’s really fast
One of the arguments for a SPA is that it provides a more reactive customer experience. I think that’s mostly debunked at this point, due to the performance creep and complexity that comes in with a more complicated client-server relationship.
When haters deny HTML’s status as a programming language, they’re showing they don’t understand what a language really is. Language is not instructing an interlocutor what to do in a way that leaves no room for other interpretations; it is better and richer than that. Like human language, HTML is conversational. It is remarkably adept at adapting to context. It can take a different shape on any machine, from a desktop browser or an e-reader screen to a mobile app or a screen reader for the blind (so long as that device is built to present hypertext).
Hell, yeah!
Ultimately, even as HTML has become the province of professionals, it cannot be gatekept. This is what makes so many programmers so anxious about the web, and sometimes pathetically desperate to maintain the all-too-real walls they’ve erected between software engineers and web developers.
Hell, yeeeeaaaaahhh!!!
What other programmers might say dismissively is something HTML lovers embrace: Anyone can do it. Whether we’re using complex frameworks or very simple tools, HTML’s promise is that we can build, make, code, and do anything we want.
Tabloid is a turing-complete programming language for writing programs in the style of clickbait news headlines.
React is a non-transferable skill.
React proponents might claim that React will teach you modern UI, but from what I’ve seen it barely copes with modern UI.
autofocus is broken, custom elements don’t work in all but the experimental version, using any “modern” features likedialogor popovers requiresuseEffect, and the synthetic event system teaches you so little about how DOM actually works. This isn’t modern UI, it’s UI from 2013 at its inception. I don’t have the time left in my career to pick up UI paradigms that haven’t evolved much beyond from when Barack Obama was in office.When I mentor early career developers and they ask me what they should learn, I can’t say React, they don’t have time. I mean sure, pick up enough React to land you the inevitable job doing it, but it’s not going to level up your career.