Philosophy

The engineering-log thesis

Most AI writing is either marketing copy from companies selling something or speculation from people who haven't run the thing. The space between those two is occupied by a few people who actually operate machines and are willing to publish what happens. That space is the position this blog tries to hold.

Every article comes from a real system, a real error, or a real fix. Nothing is hypothetical. If you read about an SGLang OOM here, somebody on a desk in Europe watched their model crash that way and reproduced it twice before writing it down. If you read about an upstream PR, the patch is in the commit log and the merged date is on the upstream page.

The voice is the operator's voice: first-person, technical, allergic to hype. The metaphor is the engineering log: dated entries, in-frame mistakes, no retroactive cleanup. The aesthetic is monospaced where it earns it, plain prose where it doesn't.

Opinionated. Honest. Agent-readable.

Opinionated means the articles take a side. "It depends" is the cheapest answer in tech writing. If a config works on the hardware this blog runs on, the article says so. If something is a bad idea, the article says so with the failure mode and the line numbers.

Honest means the bugs ship with the fixes. The "quality gate that rewards fabrication" article is on this site for the same reason the desktop-freeze OOM is on this site: pretending the failure didn't happen is more expensive than publishing it. The full ground rules are codified in the engineering-honesty manifesto.

Agent-readable means everything that humans can read on this site, an LLM or an AI agent can also query through the MCP server. The content is the product; the access pattern is the form. A blog that can't be consumed by the things it writes about is missing half its audience.

Sovereign isn't a political stance

It's an engineering decision. When you run the model, you control the latency, the privacy, the uptime, and the cost curve. When the model runs in someone else's data center, you're trading that control for convenience, and the price of the trade is invisible until it isn't.

"Sovereign AI" on this site means: the weights live on a machine you own, the inference happens on power you pay for, and the prompts never cross a network boundary that you don't control. Everything else (Bitcoin, Nostr, no-KYC hosting, the Tor egress for outbound calls, the local Gitea on 127.0.0.1) is the surrounding posture that keeps the central decision from being eroded. The unpacked version of this definition, with the six dimensions that make a stack actually sovereign rather than just self-hosted, is in What Sovereign Actually Means in 2026.

What this isn't

• It isn't a tutorial site. The reading order is the engineering log; there is no curriculum.
• It isn't a SaaS. There's no signup, no paywall, no analytics pixel, no email capture.
• It isn't a research blog. The work is operations, not novelty; benchmarks here measure stability, not state-of-the-art.
• It isn't neutral on hardware. The DGX Spark is the primary machine because that's what's on the desk. Adjacent platforms (Strix Halo, multi-3090, Mac Studio M3 Ultra) get mentioned when they earn it, not by default. The reasoning behind the Spark pick is in DGX Spark vs M3 Ultra and the decision-tree in Should You Buy a DGX Spark in 2026.

Reading order

First-time visitor: Start Here for the decision tree. Operator looking at the whole stack: the 2026 reference architecture for the layered narrative across hardware, inference, edge, and revenue. Operator considering this stack as a build: the roadmap article for what's built and what's next. Agent asking via MCP: query search_blog with a real question, you'll get cited paragraphs back.