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The $2 Trillion Question About Anthropic

Anthropic at $2 Trillion: Right About AI, Wrong About the Price?

The technology is real. The question is who captures the value — and Buffett answered this one about cars and planes a century ago.

Anthropic is heading for a public listing at a reported $2 trillion.

I want to start with what I actually believe, because it matters.

This technology is real, and it will unlock an enormous amount of economic value. Anthropic went from $386m of revenue in 2024 to $4.59bn in 2025 — twelve-fold growth. Q2 2026 revenue hit $11.5bn, with two consecutive profitable quarters and 300,000+ business customers.

Anyone calling AI “all hype” isn’t paying attention.

So the interesting question isn’t whether AI creates value. It’s who captures it — and whether the price leaves anything for you.

The most under-discussed fact in this debate is Anthropic itself

Anthropic was founded in 2021. Within roughly four years it went from nothing to overtaking OpenAI — the company that invented this market, with the multi-year head start, the Microsoft partnership, and the ChatGPT brand.

On enterprise LLM API spend, Anthropic now leads with about 40% share. OpenAI has slipped to the high-20s.

Impressive. But read it again as an investor:

If a newcomer can reach parity with the leader in five years, the leader did not have a moat.

That is what a moat is supposed to mean — protection against exactly this. We have instead watched model leadership change hands repeatedly between OpenAI, Anthropic, Google, DeepSeek and xAI, with benchmark leads lasting months, not years.

The cost structure says the same thing. Anthropic spent $7.33bn on compute in 2025 — 1.6× its entire revenue — and has committed roughly $518bn to infrastructure over the next decade, about 80% reportedly non-cancelable.

That is usually described as a moat. I’d call it the opposite: the price of staying in the game, which every serious competitor is also paying. Capital intensity that everyone must match doesn’t protect returns — it raises the stakes and converts flexible costs into fixed ones owed even if pricing collapses.

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Articles

I hired a (personal) AI employee.

I hired a (personal) AI employee. It works for me in the background, and it’s now a permanent part of my “staff”.

For over a month I’ve run Hermes Agent — an autonomous AI that lives on my hardware, has its own memory, and does things. Not a chatbot. A worker.

What it actually does for me:

🎬 1,500+ videos & articles → downloaded, transcribed, summarized, and filed into a searchable learning library. I just drop a link; it does the rest. And it structures the whole process — turning a chaotic stream of random finds into a clear curriculum and learning plan I can actually work through. A very different outcome from what the social media algorithm will feed you.

🔎 A research assistant that knows my standards. I throw topics at it and it scours various sources — with references, context, and analysis. It’s learned what matters to me in research, so the output comes back the way I’d want it, not generic.

📚 5 Anki (language learning) collections (66,901 media files) synced to my phone via a self-hosted server it deployed — and debugged when the SQLite schema broke.

🔐 My VPN — added a TCP fallback, managed the firewall, and diagnosed a carrier-NAT issue that was blocking me on mobile.

🧠 A private digital coach — its own persona, memory, and Telegram chat, checking in on my career and health. Runs on local models on my own hardware. My conversations never leave my infrastructure.

📝 A notes repository it maintains and cross-references automatically.

What I learned about managing it:

  1. Autonomy is the unlock. I brief it, it executes end-to-end, and reports back. I don’t babysit it.
  2. It fails — and self-corrects. Crashed containers, locked databases, retries. Resilience beats perfection.
  3. Memory compounds. It remembers my personal targets and goals, my health habits, my taste in music. Every interaction gets smarter.
  4. Privacy is a feature. My most personal conversations — with my coach — run on local models. No cloud, no training on my data.
  5. You still need judgment. It’s a tool, not a replacement for thinking. I review the important stuff.

The honest take: I’m a realist — I know what technology can and can’t do, and I don’t chase hype. But AI is maturing, and the potential is very significant. After weeks of real use, Hermes Agent has earned its place as permanent infrastructure, not a novelty. It’s the difference between having an assistant and having a staff.

Curious about hiring your own agent — and your own private coach — on your own hardware? Happy to share what I’ve learned.

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Videos

Humans Need Not Apply

I would like to share with you this awesomely concise  video created by CGP Grey on the subject of automatisation, and on some aspects of fourth industrial revolution driven by AI:

World is constantly changing and evolving, one of the transformational changes heralded for society is AI (Artificial Intelligence).

In many areas where automatisation brings highest returns,computers and machines are already considerably outperforming people. This tendency of incremental substitution of human labor was most evident in industry and manufacturing, but besides this incremental advancement of machines in industry, a new wave of transformational changes can be expected from AI.