Anthropic is projecting $10.9 billion in Q2 2026 revenue, up from $4.7 billion in Q1, and reporting its first operating profit. The AI press is treating this as a validation story. I want to offer a different read. This isn't primarily a story about Anthropic. It&
We've seen this movie before. In the mid-1990s, AOL had 30 million subscribers and a stranglehold on how America experienced the internet. It was fast, polished, and carefully curated, a walled garden that felt like the future. Then the open internet arrived and ate it alive. Today,
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The US government just suspended access to Anthropic's most capable models overnight. Here's what that actually means if you're building in AI — and what founders need to do about it.
A recent CNBC report revealed that 220 former unicorns built before ChatGPT have slipped below one billion dollar valuations. At the same time, AI is capturing 80% of Q1 2026 venture capital. These two facts are not unrelated. We are living through a startup extinction event. Not a crash. A
Yann LeCun raised $1.03 billion for AMI Labs, Europe's largest seed round ever. The headlines are fixating on the number. That's the wrong thing to pay attention to. The real story is where this happened and why it matters for every founder thinking about where
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Prometheus is a $41B bet that AI can automate the work of physical engineers. For founders whose defensibility rests on domain expertise, this is the clearest signal yet that expertise alone is not a moat.
Gartner is projecting that 40% of enterprise applications will include AI agents by the end of 2026. Adoption curves like that don't happen by accident, and they don't stall by accident either. Here's what's actually happening in enterprise AI right now: the
Over $250 billion has flowed into OpenAI and Anthropic ahead of their expected IPOs this year. The headline story is what this did to the startups that came before. The real story is what it is about to do to the ones building on top of them right now.
Forbes named 20 new agentic AI jobs. Most won't survive the next model release cycle. Here's what the list actually tells you about where the real opportunities are.
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The most powerful AI infrastructure company on the planet decided its supplier relationship was too risky. If they're worried, you should be too.
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AI model vendor lock-in is no longer just a procurement risk. As frontier labs move up the stack, it's an existential margin risk — and the founders who understand this are already building differently.
The CNBC story about stranded startups got the diagnosis wrong. Timing did not kill those companies. The wrong business model did. And most founders reading that story today are making the identical bet.