The slower notes behind the run.
Articles preserve the setup decisions, tradeoffs, and operator judgment that do not fit cleanly into a benchmark row or a short video segment.
Latest writing
Alex Karp Just Described Your Home Lab, at a Thousand Times the Scale
Palantir's Alex Karp went on CNBC this week and tore into the frontier labs, calling their token-metered business model "effing insane" and saying enterprises are "livid" about paying for tokens that create no value while handing their data and "alpha" to third parties. The crux of his argument (that renting all your intelligence from a black box you don't control is a strategic liability) is exactly what the local AI community has been saying and building for the last two to three years. Karp is describing the home lab ethos at a thousand times the scale. Same argument, same architecture, defense budget instead of a spare bedroom.
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In Defense of the DGX Spark: A Reality-Grounded Take
NVIDIA marketed the DGX Spark as a "supercomputer on your desk," and taken literally that sets you up to be let down: its 273 GB/s memory bandwidth means slow token generation on dense models, which is why a wave of early buyers returned or resold theirs. But that critique measures the machine against the wrong job. The Spark is a large-memory device, not a fast-dense-model device. It comes alive on Mixture of Experts models, on clustering multiple units over ConnectX-7 to run near-frontier-scale open weights like Qwen3.5-397B at home, and on prefill-heavy agentic workloads where its Blackwell compute chews through long prompts far faster than a Mac Studio.
Kevin Harnischfeger · Jul 1, 2026 · 10 min read -
You Are Bidding Against a Datacenter
Local AI enthusiasts are being quickly displaced from the market due to the monumental nature of price increases we've experienced over the last year. What's expensive to us is nothing but capital expenditure to the big players, and with supply not catching up to current and projected demand, it's clear that the issue of more staggered price increases is only going to get worse. With Apple raising prices on their hardware by as much as 30%+ this last week, it's clear that the market has all but abandoned consumers and tech-enthusiasts.
Kevin Harnischfeger · Jun 29, 2026 · 8 min read -
The Intern that Doesn't Leave the Building
AI security is about where the AI lives, what it can access, and who controls its actions. This article argues that private and local AI offer a more practical path for serious organizations by keeping sensitive data inside trusted boundaries. The result is not weaker or less ambitious AI, but AI that can safely work with the information that matters most. Private AI makes powerful systems more governable, auditable, and useful.
Daniel Lopez · Jun 29, 2026 -
The Bull Case for Sovereign Intelligence
This month the US government took two frontier AI models offline and forced a third into a gated release. If that does not concern you, it should, because it proves the intelligence most of us rely on can be revoked by people we do not answer to. This piece is about why that matters, and what owning your own compute actually protects you from.
Kevin Harnischfeger · Jun 28, 2026 · 9 min read -
Private AI Is Not Just About Privacy: It’s About Cost, Consistency, and Control
Private AI is not just about keeping data private. For serious AI users, local LLMs matter because of cost, consistency, control, open-weight models, and the limits of hosted AI subscriptions.
Mark Chang · Jun 27, 2026
