How we think. What we make.
Build logs, system breakdowns, and essays on private AI, local-first architecture, autonomous agent systems, and the philosophy behind sovereign intelligence.
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Generating code is easy. Generating code that compiles, doesn't break existing tests, and actually solves the problem — that's where the real engineering live...
Most agent failures aren't execution failures. They're planning failures — good work on the wrong task, in the wrong order, at the wrong level of detail. The ...
Before an agent can reason, plan, or generate, it has to see what it's working with. Most agents still read code the way a text editor does. That's the root of ...
A series announcement. After months of building and running autonomous AI systems, we've identified six layers that every serious coding agent needs. Each one g...
We built a research system that runs around the clock on local infrastructure. Here's what changed when we gave it a real embedding model and a vector database ...
What happens when you rebuild the AI inference stack from scratch in Go — no Python, no ONNX, no C dependencies. A look at a novel approach to model compilati...
Autonomous agents need more than instructions — they need governance. Here's how we built a declarative rules engine to keep our AI systems trustworthy.
Why we run our own stack — and what it actually costs. A look inside the sovereign AI infrastructure powering a small creative studio.
The case for local-first AI: sovereignty over your data, independence from platforms, and systems that compound instead of expire.
How we're using ChatGPT for stills, Grok for animation, and Codex for production management to build a full animated series — with a team of zero animators.
How we built a 10-process autonomous AI system with cost breakers, structural code analysis, and self-correcting code generation — running locally on a Mac Mi...