Notes from the field.
Long-form writing on private AI deployment, on-premises infrastructure, compliance, and the engineering decisions behind every system I ship.
Apple Silicon as an inference node: M4 Max & M3 Ultra, honest digits
Benchmarks for 70B models on M4 Max and M3 Ultra. Why Apple is betting on local inference - and what the token economics tell us about the future.
Public AI assistants in higher education: the GDPR exposure most institutions have not assessed
When staff paste student work into a public AI assistant - ChatGPT, Claude, Gemini, whichever - the institution becomes the controller for a processor it never contracted. A walk through GDPR Articles 5, 28, 32 and 35, the rulings already issued, and the architectural fix that does not require banning AI.
A private LLM for a research lab: notes from a 14-day rollout
Field notes from a 14-day on-premises private LLM deployment for a 28-person genomics lab: Mac Studio M3 Ultra running Llama 3.3 70B via Ollama, AnythingLLM RAG over 2,400 unpublished documents, pfSense deny-by-default egress, and zero outbound bytes after handover - with the hardware trade-offs, GDPR and grant-compliance framing, and the three things that broke.
Private RAG for contract review: a law firm case study (Dubai/London)
How a Dubai/London law firm cut contract review time by 73% with a private Llama 3.1 70B RAG running on-prem over 12k binding documents - audit-grade citations, NDA-safe, no cloud.
Hand-written referrals to structured EHR records: a clinic NER case study (UAE)
A UAE clinic group turned hand-written referral letters into structured EHR records in 4 seconds with 99.2% NER precision - on a single on-prem A6000, never touching the public internet.
Why 40% of AI Projects Get Canceled - And the Five Decisions That Separate the Rest
Gartner says more than 40% of AI agent projects will be canceled by the end of 2027. The reason is almost never the technology. Here is what actually goes wrong - and a practical framework for not ending up in that pile.
How I Built an Autonomous AI Content Engine for a Crypto Media Company
A crypto media company needed to cover a 24/7 market with a finite editorial team. Here is how I built an autonomous pipeline that went from detecting events to publishing finished articles - and why the hardest part had nothing to do with AI generation.
Shadow AI: Your Staff Are Leaking Data Into ChatGPT
You'd never let a stranger read your contracts and medical records. Yet employees paste them into ChatGPT daily. The GDPR risk, and how private AI stops it.
One Creator. One Workstation. No More Subscription Roulette.
A creator was paying for five separate AI tools, uploading unfinished work to platforms they didn't fully trust, and spending more time managing accounts than making things. Here's what changed when we built one private workstation instead.
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