AI is Stifling Tech Adoption | Vale.Rocks

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.

AI is Stifling Tech Adoption | Vale.Rocks

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Progress Without Disruption - Christopher Butler

We’ve been taught that technological change must be chaotic, uncontrolled, and socially destructive — that anything less isn’t real innovation.

The conflation of progress with disruption serves specific interests. It benefits those who profit from rapid, uncontrolled deployment. “You can’t stop progress” is a very convenient argument when you’re the one profiting from the chaos, when your business model depends on moving fast and breaking things before anyone can evaluate whether those things should be broken.

We’ve internalized technological determinism so completely that choosing not to adopt something — or choosing to adopt it slowly, carefully, with conditions — feels like naive resistance to inevitable progress. But “inevitable” is doing a lot of work in that sentence. Inevitable for whom? Inevitable according to whom?

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The Main Thread Is Not Yours — Den Odell

Every millisecond you spend executing JavaScript is a millisecond the browser can’t spend responding to a click, updating a scroll position, or acknowledging that the user did just try to type something. When your code runs long, you’re not causing “jank” in some abstract technical sense; you’re ignoring someone who’s trying to talk to you.

This is a great way to think about client-side JavaScript!

Also:

Before your application code runs a single line, your framework has already spent some of the user’s main thread budget on initialization, hydration, and virtual DOM reconciliation.

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I’m more proud of these 128 kilobytes than anything I’ve built since | by Mike Hall | Jul, 2025 | Medium

I don’t normally link to articles on Medium—I respect you too much—and I do wish this were written on Mike Hall’s own site, but this is just too good not to share.

And don’t dismiss this as a nostalgiac case study from the past:

At no point did the constraints make the product feel compromised. Users on modern devices got a smooth experience and instant feedback, while those on older devices got fast, reliable functionality. Users on feature phones got the same core experience without the bells and whistles.

The constraints forced us to solve problems in ways we wouldn’t have considered otherwise. Without those constraints, we could have just thrown bytes at the problem, but with them every feature had to justify itself. Core functionality had to work everywhere, and without JavaScript crutches proper markup became essential.

This experience changed how I approach design problems. Constraints aren’t a straitjacket, keeping us from doing our best work; they are the foundation that makes innovation possible. When you have to work within severe limitations, you find elegant solutions that scale beyond those limitations.

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Keeping up appearances | deadSimpleTech

Looking at LLM usage and promotion as a cultural phenomenon, it has all of the markings of a status game. The material gains from the LLM (which are usually quite marginal) really aren’t why people are doing it: they’re doing it because in many spaces, using ChatGPT and being very optimistic about AI being the “future” raises their social status. It’s important not only to be using it, but to be seen using it and be seen supporting it and telling people who don’t use it that they’re stupid luddites who’ll inevitably be left behind by technology.

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In 2025, venture capital can’t pretend everything is fine any more – Pivot to AI

Here is the state of venture capital in early 2025:

  • Venture capital is moribund except AI.
  • AI is moribund except OpenAI.
  • OpenAI is a weird scam that wants to burn money so fast it summons AI God.
  • Nobody can cash out.

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