Innovation without solving problems

Is AI an attempt to take the Rot Economy to its illogical conclusion? Can you maximise profit without solving a problem and without a quality product or user experience?

Ed Zitron has been on a tear over the last year. His newsletter and podcast Better Offline make a sustained and uncomfortable argument about what has gone wrong inside the world's largest technology companies. Ed has spent a lot of time recently on AI, but I really vibed with his earlier critique. The Rot Economy: a philosophy – or perhaps an ideology – where the pursuit of endless growth has been prioritised over product quality, user experience, and the original purpose that made these companies worth using in the first place. Loyal users have been left behind. Products have gotten worse. And the people running these companies have gotten richer.

I think he's right. And I think it connects to something I've been turning over for a while about what innovation actually means.

Real innovation requires two things: change and a problem worth solving. Not a manufactured problem, not a financial problem, not a problem that exists only because venture capital needs a 10x return – a real problem, felt by real people. When you strip that requirement away, what you're left with isn't innovation. It's solutionism. The answer that goes looking for a question.

That's where I land on generative AI. I genuinely struggle to identify the problem it solves. What is the problem that it actually solves? What it has identified is a gap in the investment landscape – a place to park capital in search of returns that have become harder to find as big tech has consolidated its dominance. Rather than address the structural conditions that make those returns scarce, the money has moved sideways into the next technical novelty. Generative AI is not a response to a need.

The pattern isn't new, though. We've watched it play out already – just more slowly.

Facebook, in its early years, had genuine value. It solved a real problem: staying connected with people across distance. Before the ads, before the algorithm, before the growth imperative took hold, there was something real happening – a sense of everyday connection, of living vicariously through the small moments of people you cared about. That was worth something.

Then the model changed. Growth became the only metric that mattered. Ads appeared, then multiplied. The algorithm began promoting engagement over connection, which in practice meant conflict, outrage, and sensation over the quiet updates that made the thing useful in the first place. The ratio of ads to genuine posts inverted until the product became effectively unusable. For every post from a friend, fifteen ads. And because there are fifteen ads, there are fewer posts from friends. So it fills the gap with recommended posts from strangers or ads pretending to be strangers.

Twitter followed the same arc. When it was less focused on profit, it was a genuinely useful place – democratic in a way that felt new, allowing anyone to reach anyone. As commercial pressure intensified, moderation loosened, algorithms promoted the most inflammatory content, and the platform became a place where discourse goes to die rather than happen.

This is what the Rot Economy looks like in practice. It's not a sudden collapse. It's a slow hollowing out – the original value gradually replaced by the mechanisms of extraction, until the host has nothing left to give. Which, as Zitron puts it, is parasitic behaviour. And a parasite that kills its host has nowhere left to go.

AI is the Rot Economy taken to its logical conclusion. It doesn't just hollow out an existing product — it attempts to bypass the problem/product paradigm altogether. In the context of global climate change, the investment in data centres to run AI far exceeds that of installing renewable energy and electrifying everything, which seems absolutely insane. Yet here we are.

And while we're doing that, the climate crisis continues. The world's most significant and most tractable problem – the one that stands to affect every person, every system, every economy on the planet – sits underfunded and under-prioritised. Instead, we're building infrastructure that consumes more energy, water, and other resources to automate the generation of content that doesn't need to exist. It is hard to think of a more complete misdirection of talent and capital. What if the hundreds of billions of dollars pledged to build data centres were spent electrifying the nation with renewables?

The problem is that "number go up" has become so synonymous with success that we've stopped asking what the number is actually measuring. Growth is a metric, not a purpose. You can have billions of users engaging with something less, because it works better and asks less of them. That's a different business model, yes – but so much of the current model is so fundamentally broken that rewriting it isn't a threat, it's an opportunity.

What we actually need is less. Simpler. More federated, more cooperative, more focused on doing fewer things well. Technology that reduces its footprint rather than expanding it. Innovation that starts with the problem rather than the return. The tools exist. The knowledge exists. What's missing is the will to point them at something that matters. Number go up, until it doesn't. The question is what we've built by the time it stops.

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