Adam Gonnerman

In a few blog posts here recently I've attempted to share what we can expect with the coming burst of the AI bubble . I think it's a matter of "when," not "if." The clip below explains the consequences of the end of the AI bubble in simple and direct terms. What bothers me about it, besides its inevitability, is that I can't think of what to do to protect myself from the aftermath.   

The most interesting concept I’ve learned about in the past month is “enshittification,” a term coined by Cory Doctorow . He uses it to describe the predictable decline of digital platforms: first they are great to users, then they shift to favor business customers and advertisers, and finally they extract maximum value for shareholders, often degrading the experience for everyone else in the process. The term is blunt, but the framework is sharp. It gave language to something I’ve observed repeatedly in media and technology organizations: product decisions that begin as user-centered gradually become revenue-optimized, and eventually erode trust, quality, and long-term viability. Related to that, I’ve been following Doctorow’s arguments about a potential AI bubble, his view that massive capital is flowing into AI in ways that may not be sustainable relative to real, durable value creation. That perspective helped me separate two things that are often conflated: genuine technological...

Behind the headlines celebrating the AI revolution lies a financial story that isn't nearly as clean as the press releases suggest. Trillions of dollars in debt, underwhelming adoption numbers, and a revenue loop that may be more circular than it first appears — this video takes a hard look at whether the AI boom is built on solid ground or something far more precarious. If you think the biggest risk to your portfolio is missing out on AI, you might want to watch this first.

The AI boom hasn't just captured investor imagination. It has quietly become one of the biggest concentrations of financial risk in modern history. In this video, we dig into the economic mechanics that most coverage glosses over: a business model that may actually lose more money as it scales, a web of capital flows that can look like growth while cycling through the same handful of players, and a market so top-heavy that a single crack could become a systemic fracture. The technology may be real, but the economics deserve a much harder look.

The AI hype cycle is loud, but the numbers behind it tell a quieter and more troubling story. In this video, we look at the growing gap between what the industry is promising and what it is actually delivering, from the economics that get worse as they scale to the valuations that depend on growth that may never arrive. It's not a reason to give up on technology, but it might be a reason to stop taking the headlines at face value.