Field Notes
Human-written pieces on ownership, the economics, and what most people building with AI get wrong. Read before you decide anything.
A dull mind in the user and a lying machine trace back to one root: abdicating the operator’s role. When you stop thinking, it starts making things up. Same problem, same fix.
The coming wave of “privacy” AI tools looks genuinely good. But if you don’t own the machine, your data still lives in someone else’s box, no matter how good the company.
The word “sovereign” is being misused across the AI space. The simple rule of thumb for knowing whether your data actually stays in your room.
How the bubble actually formed, why the technology doesn’t vanish when it pops, and where that leaves the people paying attention.
The justified, and unjustified, backlash against LLMs, where it comes from, and what the real problems actually are.
What running AI on hardware you own actually means for the energy-and-infrastructure question everyone argues about.
The distinction that decides how much of your AI you actually control, and why the words keep getting blurred on purpose.
Why where your intelligence runs, and who has legal reach over it, is quietly becoming a question of sovereignty.
What growing government entanglement with the largest AI companies signals for the people who depend on them.
Anthropic can now require a government ID and a live selfie to keep using Claude. The plain version of what changed, who it hits, and why it matters.
What truly private AI is, why most “local” solutions fall short, and how to own a machine that answers only to you, no ID required.
Not a vague “it depends.” The actual floor is about $2,400, with the honest range and exactly what changes the price in 2026.
The manuals take you from an idea to a running, private machine you own outright.
See the manuals