In this issue: The fight for the user interface. $10 million for AI journalism. Tech policy expert Frederike Kaltheuner on how to escape a captured ecosystem. Plus: Watching Tom Vaillant’s local research tool is like watching magic.

If you’re attending the NPA Summit in Chicago next week: I somehow got talked into giving a masterclass on what comes after the article. Come say hi and help me figure it out.

What we’re talking about: The fight for the user interface. Take this example: someone wears a Garmin watch to track workouts. Garmin lets some of that data sync with other services, and launched its own paid subscription tier last year, while freezing new developer access to its API. For now, there is no official way to pipe extensive workout data into a chatbot automatically. Garmin has its own app and ecosystem. Why give that up to enrich someone else’s AI?

But you can ask a chatbot to get the data out anyway. It will happily help you build a script that logs into Garmin, grabs your temporary authentication token, and pipes the data into the model of your choice.

I’ve used this method myself. Not with Garmin, but with an internal system at work. If a service doesn’t offer an API or an MCP connection, you can just ask AI to build a bridge. It might violate the terms of service, and things might break, but the barrier to building your own connector has dropped to near zero.

That is a problem for platforms like Amazon or Booking.com. Their business models depend on controlling the interface so they can serve ads and upsell you along the way. Amazon sued Perplexity over its “Comet” shopping agent. At least one court sided with Perplexity, ruling that when a local agent acts on a user’s orders, it is the user knocking on the door.

Media companies already block AI crawlers. But what happens when our own paying subscribers use personal AI agents, logged in with their own credentials and session tokens, to read our journalism without ever seeing our homepage, our ads, or our related stories? And while publishers try to stop AI agents from bypassing their frontends, journalists are using the same AI tricks to pull data out of clunky tools and public databases.

What I’m reading:

And now: Like many European companies, we give SPIEGEL employees access to the latest AI models, as long as they are hosted on European infrastructure. That includes Mistral 4. We don’t build everything on one app. Instead, we use a model-agnostic approach. Frederike Kaltheuner looks at questions like these and how to avoid a captured ecosystem from a policy perspective.

Four Questions with Frederike Kaltheuner

Frederike Kaltheuner

Frederike Kaltheuner is a Berlin-based technology policy expert and adviser.

What's the most important question right now?

How can we avoid a future in which much of our economy runs on the proprietary models of two companies? I don’t think that’s the most likely outcome, but it’s roughly the kind of dominance Anthropic and OpenAI would need to justify their valuations and the debt-financed buildout behind them.

Last year, Anthropic had to spend (!) $2.75 to make a single dollar. (For reference, OpenAI was at -$2.60 per dollar of revenue in 2025.) Anthropic also has $518bn in compute commitments, most of which cannot be cancelled. Again, that’s for a loss-making company.

I strongly recommend Ed Zitron’s take on the entire market. He’s obviously a well-known critic, but he has also taken a really close look at the numbers, which are simply mind-boggling.

Where are we taking AI too seriously, and where not seriously enough?

Let’s start with the latter. Despite all this, we’re still not taking AI seriously enough. We’re focussing on an incredibly narrow set of problems, “rogue models” and speculative extinction risk, when we should be talking about the much more existential transformations currently underway. What will happen to the web as we know it? Will we still have websites when people read the news and go shopping via agents? Will software firms still exist when you can build custom solutions for everything yourself? We’ve spent a decade studying the effects of social media on democracy, mental health, and children. Are we ready for what’s next?

These are serious questions that need a much wider societal debate. Yet we’re increasingly treating AI as an exceptional technology around which all other politics (labor, sustainability, democracy) must bend.

What we’re taking way too seriously are the narratives and predictions coming out of the dominant AI firms, which make us believe that AI is on a single trajectory.

Two things can be true at once: the AI market is heavily concentrated, and it is also in flux. No technological shift or market correction will, on its own, make Europe a global leader in AI or limit the power of Nvidia and the hyperscalers. But which layer of the stack (applications, models, infrastructure) captures value in the long run is a different question, and one the market has not yet answered (remember, OpenAI and Anthropic are losing money on every client!).

Even the underlying technology is anything but fixed: we simply don’t know if the dominant approach to building AI will continue to be based on ever-larger models trained on ever more data and compute, and run on the cloud. What if open-weight models reach durable parity and models commoditize? What if leading labs respond by moving up the stack into enterprise products and agents? What if inference cost, not training cost, determines where value accumulates? What if the market corrects, and corrects sharply?

These are just some of the questions pointing to radically different futures that each need a solid policy response. Yet, as I have argued with my colleague Leevi Saari, Europe’s policy response has been deeply flawed.

If we accept the idea that AI’s future is much more open, we also need to accept that it is shapeable. We need to shape this market in our interest. That’s no easy task, but it’s our only hope. Simply said, regardless of how AI develops, a concentrated market leaves economies and democracies worse off than an open one. That’s why keeping the market open and contestable is a necessary condition for AI that serves us.

There’s much more that Europe can do, and I’ve written about this in greater depth in a new report: How to escape a captured ecosystem.

What future are you looking forward to?

As an avid hater of life admin, I am looking forward to a future where I can automate this part of life. We experimented with a locally run model to take care of the mental load at home (it half-worked). I am also looking forward to the disappearance of screens. A few weeks ago, OpenAI ran a bizarre ad in which people sat in a €10,000 Eames Lounge Chair in front of a gigantic screen, already holding their tennis rackets, casually instructing AI to do their presentation. I want the robots to work for me! But can we have this without destroying the planet or handing over our deepest thoughts, desires, and ideas to a Silicon Valley oligopoly, while keeping everything that’s genuinely human and joyful (poetry! music! art!) for ourselves?

What's a good website?

Net art by Constant Dullaart from 2010. I miss the internet we had back then.

Hands on: I’ve mentioned it before: watching journalist and technologist Tom Vaillant use his own AI research tool, Mycroft, is like watching magic. It’s just a chatbot, some skills, and text files. You could build this with Codex or Claude Code, but he chooses to run it locally on his computer with Goose and Obsidian.

And he’s doing a free webinar to wow and teach us all! It’s on October 28th, 10 am ET/4 pm CET, hosted by Indicator’s Craig Silverman.

One more thing: There is a way to get paid by AI companies for content, and it’s making advertorials on TikTok. Eugene Healey does short essays on culture and marketing, and he’s done at least two paid partnerships for Claude.

The AI chatbot gets to be the pure, ad-free space to think, while cultural critics on social become the ad-supported wrapper. Quite the inversion.

This is THEFUTURE.