Here’s a question worth more than most of the AI hype takes clogging your feed: what happens to your velocity the day your frontier provider changes the deal? Raises the price. Deprecates the model you tuned your whole workflow around. Throttles you at the worst possible moment. Or just decides your use case, your industry, or your country isn’t one they want to serve anymore. If your honest answer is “I’d be dead in the water,” then you don’t have a strategy — you have a dependency. And it’s time to look hard at running some inference on your own metal.
I have two 128 GB unified-memory machines on my desk. Day job gear, not mine. One is an ASUS Ascent GX10 — an NVIDIA GB10 Grace Blackwell appliance half the size of a hardback book. The other is an HP ZBook Ultra G1a, a 14" mobile workstation running AMD’s Ryzen AI MAX+ PRO 395 (“Strix Halo”). Both hold an 80B coding model entirely in memory. How do they compare for agentic coding?
Right now, as an industry, we are running almost entirely on COGS and calling it innovation. Kelsey Hightower gave a talk at PlatformCon called Zero Token Architecture, and the whole thing compresses down to one sentence: infer once, export, run without inference. He’s right. I want to give you the vocabulary that makes it land in a budget meeting, because I work at a company that ships hardware, and we already have words for this.