I love the small web, the clean web. I hate tech bloat.
And LLMs are the ultimate bloat.
So much truth in one story:
They built a machine to gentrify the English language.
They have built a machine that weaponizes mediocrity and sells it as perfection.
They are strip-mining your confidence to sell you back a synthetic version of it.
Great minds think alike! I have a very similar HTML web component on the front page of The Session called input-autosuggest.
But perhaps the death of search is good for the future of the web. Perhaps websites can be free of dumb rankings and junky ads that are designed to make fractions of a penny at a time. Perhaps the web needs to be released from the burden of this business model. Perhaps mass readership isn’t possible for the vast majority of websites and was never really sustainable in the first place.
Progressive enhancement is about building something robust, that works everywhere, and then making it better where possible.
You might not need (much) JavaScript for these common interface patterns.
While we all love the power and flexibility JS provides, we should also respect it, and our users, by limiting its use to only what it needs to do.
Yes! Client-side JavaScript should do what only client-side JavaScript can do.
See, I’ve always compared that building pressure of need-to-blog to being constipated (which makes the resultant blog post like having a very satisfying bowel movement), but maybe Brad’s analogy is better. Maybe.
I suppose it’s not clear to me what a ‘good’ window into unreliable, systemically toxic systems accomplishes, or how it changes anything that matters for the better, or what that idea even means at all. I don’t understand how “ethical AI” isn’t just “clean coal” or “natural gas.” The power of normalization as four generations are raised breathing low doses of aerosolized neurotoxins; the alternative was called “unleaded”, but the poison was called “regular gas”.
There’s a real technology here, somewhere. Stochastic pattern recognition seems like a powerful tool for solving some problems. But solving a problem starts at the problem, not working backwards from the tools.
Delivering total nonsense, with complete confidence.
The promise of AI – the promise AI companies make to investors – is that there will be AIs that can do your job, and when your boss fires you and replaces you with AI, he will keep half of your salary for himself, and give the other half to the AI company.
That’s it.
That’s the $13T growth story that MorganStanley is telling. It’s why big investors and institutionals are giving AI companies hundreds of billions of dollars. And because they are piling in, normies are also getting sucked in, risking their retirement savings and their family’s financial security.
Now, if AI could do your job, this would still be a problem. We’d have to figure out what to do with all these technologically unemployed people.
But AI can’t do your job. It can help you do your job, but that doesn’t mean it’s going to save anyone money.
AI has the Jeopardy Phenomenon too.
If you use it to generate code that is outside your expertise, you are likely to think it’s all well and good, especially if it seems to work at first pop. But if you’re intimately familiar with the technology or the code around the code it’s generating, there is a good chance you’ll be like hey! that’s not quite right!
Not just code. I’m astounded by the cognitive dissonance displayed by people who say “I asked an LLM about {topic I’m familiar with}, and here’s all the things it got wrong” who then proceed to say “It was really useful when I asked an LLM for advice on {topic I’m not familiar with, hence why I’m asking an LLM for advice}.”
Like, if you know that the results are super dodgy for your own area of expertise, why would you think they’d be any better for, I don’t know, restaurant recommendations in a city you’ve never been to?
Spot-on observations from Terence linking the fundamental nature of parsing in web browsers with the completely wrong-headed takes of some technologists who have built on top of the web.
The core idea of the event is to get you up to speed on the most powerful web platform features that you can use right now. I love that because it aligns perfectly with what I’ve been working on over the last couple of years: finding ways to break old habits to get the most out of CSS.
My mind boggles at the thought of using a generative tool based on a large language model to do any kind of qualatitive user research, so every single thing that Gregg says here makes complete sense to me.
Eric Meyer and Brian Kardell chat with Jay Hoffmann and Jeremy Keith about Shadow DOM’s backstory and long origins
I enjoyed this chat, and it wasn’t just about Shadow DOM; it was about the history of chasing the dream of encapsulation on the web.
Whenever anyone states that “AI is the future, so…” or “many people are using AI anyway, so…” they are not only expressing an opinion — they‘re shaping that future.
Here’s a little snippet of CSS that solves a problem I’ve never considered:
The problem is that Live Text, “Select text in images to copy or take action,” is enabled by default on iOS devices (Settings → General → Language & Region), which can interfere with the contextual menu in Safari. Pressing down on the above link may select the text inside the image instead of selecting the link URL.
A short piece of speculative fiction.
This is a spot-on analysis of how CSS-in-JS failed to deliver on any of its promises:
CSS-in-JS was born out of good intentions — modularity, predictability and componentization. But what we got was complexity disguised as progress.
Belfast TradFest have republished this blog post of mine and I must say, I really like the photo they’ve used—doesn’t my mandolin look lovely!
