AI · May 16, 2026

PHIPA-compliant AI for Ontario clinics: a build checklist

What it actually takes to deploy AI inside an Ontario healthcare practice without violating PHIPA. A practical checklist for clinic operators and the developers they hire.

AIPrivacyComplianceHealthcare
AI · May 14, 2026

The real total cost of running your own LLM in 2026

GPU sticker prices are only one line on the invoice. A breakdown of every cost center for self-hosted inference, with current 2026 numbers, so you can decide whether the math works for your use case.

AIInfrastructureCost OptimizationHardware
Security · May 8, 2026

Back-to-back Linux kernel CVEs, and why a small shop still needs a patch cadence

Copy Fail one week, Dirty Frag the next, the sudo flaws last year. The Linux kernel keeps leaking privilege-escalation bugs. Here's the honest read on what matters and the unglamorous routine that handles it.

SecurityInfrastructureLinux
AI · May 7, 2026

AI coding assistants, one year in

A studio that ships code every day takes an honest accounting of what AI coding tools changed, what they didn't, and what it means if you're paying for them, or paying a shop that uses them.

AIDevelopment
AI · March 20, 2026

Where AI development sits in 2026

An honest read on where AI development is in 2026: what's actually in production, what's still vaporware, and what it means for the kind of businesses we build software for.

AIDevelopmentTechnology Trends
AI · March 20, 2026

What it actually costs to run AI on your own hardware

A plain-English breakdown of the hardware, GPU, memory, and cloud costs involved in running AI inference, for operators who want a number, not a whitepaper.

AIHardwareInfrastructure
AI · March 20, 2026

The actual break-even point for running LLMs yourself

Cloud APIs are cheap at small volume and expensive at large volume. Here's the rough math on where self-hosting starts to pay off, what it actually costs, and the common mistakes.

AIInfrastructureCost Optimization
AI · January 20, 2025

When local AI deployment is the right answer

There are specific situations where sending data to a cloud AI provider isn't viable. Here's when local deployment is worth the extra work and when it isn't.

AIInfrastructurePrivacy
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