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.
I don’t think it’s controversial to suggest that LLMs haven’t measured up to any of the lofty promises made by their vendors. But in more concrete terms, consumers dislike “AI” when it shows up in products, and it makes them actively mistrust the brands that employ it. In other words, we’re some three years into the hype cycle, and LLMs haven’t met any markers of success we’d apply to, well, literally any other technology.
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.
We trained people to care deeply and then funnelled them into environments that reward detachment. And the longer you stick around, the more disorienting the gap becomes – especially as you rise in seniority. You start doing less actual design and more yapping: pitching to stakeholders, writing brand strategy decks, performing taste. Less craft, more optics; less idealism, more cynicism.
This is a really thoughtful piece by Rich, who’s got conflicted feelings about large language models in the design process. I suspect a lot of people can relate to this.
What I do know is that I find LLMs useful on occasion, but every time I use one I die a little inside.
The web is open, apps are closed. The majority of web users have installed an ad blocker (which is also a privacy blocker). But no one installs an ad blocker for an app, because it’s a felony to distribute that tool, because you have to reverse-engineer the app to make it. An app is just a website wrapped in enough IP so that the company that made it can send you to prison if you dare to modify it so that it serves your interests rather than theirs.
I Feel Like I’m Going Insane
Everywhere you look, the media is telling you that OpenAI and their ilk are the future, that they’re building “advanced artificial intelligence” that can take “human-like actions,” but when you look at any of this shit for more than two seconds it’s abundantly clear that it absolutely isn’t and absolutely can’t.
Despite the hype, the marketing, the tens of thousands of media articles, the trillions of dollars in market capitalization, none of this feels real, or at least real enough to sustain this miserable, specious bubble.
We are in the midst of a group delusion — a consequence of an economy ruled by people that do not participate in labor of any kind outside of sending and receiving emails and going to lunches that last several hours — where the people with the money do not understand or care about human beings.
Their narrative is built on a mixture of hysteria, hype, and deeply cynical hope in the hearts of men that dream of automating away jobs that they would never, ever do themselves.
Generative AI is a financial, ecological and social time bomb, and I believe that it’s fundamentally damaging the relationship between the tech industry and society, while also shining a glaring, blinding light on the disconnection between the powerful and regular people. The fact that Sam Altman can ship such mediocre software and get more coverage and attention than every meaningful scientific breakthrough of the last five years combined is a sign that our society is sick, our media is broken, and that the tech industry thinks we’re all fucking morons.
In which Rich nails Clearleft’s superpower:
“Clearleft is a relatively small team, but we can achieve big results because we are nimble and extremely experienced. As strategic design partners, we have a privileged position where we can work around a large company’s politics,” Rutter said. “We need to understand those politics — and help the client staff navigate them — but we don’t need to be bound by them. We bring a thoroughly user-centered approach to our design partnership, and that can be something novel to companies. By showing them what good design looks like (not so much the interface, as the actual process of getting to really well-designed products and services), we can be disruptive within the organization and leave them in a much better place.”
AI has the same problem that I saw ten year ago at IBM. And remember that IBM has been at this AI game for a very long time. Much longer than OpenAI or any of the new kids on the block. All of the shit we’re seeing today? Anyone who worked on or near Watson saw or experienced the same problems long ago.
I miss A Book Apart, and I really miss An Event Apart—I made so many friends and memories through that conference. I admire Jeffrey’s honest account of how much it sucks when something so good comes to an end.
The story of Lore Harp McGovern is like something from Halt And Catch Fire.
Here’s a nice interview with Rich all about how things work at Clearleft.
This observation seems intuitively obvious in Europe and pearl-clutchingly shocking in America:
What’s perfectly acceptable behaviour when you are a relatively small company becomes outright illegal (and rightly so) when you become dominant in an industry.
Your teams should be working closer to the web platform with a lot less complex abstractions. We need to relearn what the web is capable of and go back to that.
Let’s be clear, I’m not suggesting this is strictly better and the answer to all of your problems. I’m suggesting this as an intentional business tradeoff that I think provides more value and is less costly in the long run.
The whole point of the web is that we’re not supposed to be dependent on any one company or person or community to make it all work and the only reason why we trusted Google is because the analytics money flowed in our direction. Now that it doesn’t, the whole internet feels unstable. As if all these websites and publishers had set up shop perilously on the edge of an active volcano.
But that instability was always there.
This is the transcript of a fantastic talk called “The Tools We Still Need to Build with AI.”
Absorb every word!
The rise of dot-com companies was pitched as a no consequences gold rush. We were on the precipice of a fictional future where everyone would be cashing in on the web. The reality was quite a bit more slow, and boring. Business on the web consolidated, as we now know, and left most people holding the bag. There’s no knowing exactly what will happen with AI technologies, but it wouldn’t be unreasonable to expect something far more boring and centralized than what’s being promised.
Primer was a film about a start-up …and time travel. This is a short story about big tech …and time travel.
I find my feelings about AI are actually pretty similar to my feelings about blockchains: they do a poor job of much of what people try to do with them, they can’t do the things their creators claim they one day might, and many of the things they are well suited to do may not be altogether that beneficial. And while I do think that AI tools are more broadly useful than blockchains, they also come with similarly monstrous costs.
A very even-handed take.
I’m glad that I took the time to experiment with AI tools, both because I understand them better and because I have found them to be useful in my day-to-day life. But even as someone who has used them and found them helpful, it’s remarkable to see the gap between what they can do and what their promoters promise they will someday be able to do. The benefits, though extant, seem to pale in comparison to the costs.
Powerful metaphors in this piece by Maria Farrell and Robin Berjon on the Waldsterben of the internet:
Our online spaces are not ecosystems, though tech firms love that word. They’re plantations; highly concentrated and controlled environments, closer kin to the industrial farming of the cattle feedlot or battery chicken farms that madden the creatures trapped within.
We all know this. We see it each time we reach for our phones. But what most people have missed is how this concentration reaches deep into the internet’s infrastructure — the pipes and protocols, cables and networks, search engines and browsers. These structures determine how we build and use the internet, now and in the future.