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AIMA's management and after-sales layers are done, but the inference engine is missing: Ollama, llama.cpp, and vLLM all fall short, so I'm building one.

Mac permissions are for humans, Linux for programs. Agents are infrastructure, not apps. Running one on a Mac is like forcing a server into a laptop: it works, but feels wrong.

I covered cost and control before; this post adds law. Cloud is rented, edge is sold, and that distinction matters once AI agents decide on their own.

Edge devices shouldn't chase cloud LLMs. A Mac mini-class box with helper models—TTS, ASR, OCR, VLM—should sit in a corner like a router: boring is right.

Compute is directly becoming productivity, bypassing labor. Edge AI devices aren't just cost savers—they're a counterweight to centralized AI power.

As AI shifts from chat to agents, compute demand surges 100×. The real edge problem isn't buying hardware but using it—TCO traps eat cheap devices' value.