Intelligence for the people building the AI infrastructure stack.
The AI infrastructure space is noisy. Every week brings new model releases, funding announcements, and hot takes. But if you're actually building and operating AI systems in production — managing GPU fleets, monitoring hallucination rates, optimizing token costs, keeping systems reliable — you don't need more news. You need intelligence you can act on.
What Stack Monitor covers
Stack Monitor is a technical intelligence publication focused on the intersection of AI systems and infrastructure operations. We write for the engineers, SREs, and platform leads who are actually shipping these systems — not the executives reading about them secondhand.
Editorial principles
Cost is a first-class concern
Most AI coverage ignores the economics. We put cost engineering at the center — because in production, the difference between a profitable system and a money pit is often 10% better infrastructure choices.
Depth over breadth
We'd rather publish one deeply researched brief that saves you a week of investigation than five shallow posts that add nothing to your understanding.
Production > prototypes
LLM demos are easy. Shipping reliable, cost-effective AI systems at scale is hard. We focus on the second problem — the one that actually matters to practitioners.
Opinionated, not neutral
Information without interpretation is just noise. We take positions, make arguments, and aren't afraid to say when something is overhyped or a genuine breakthrough.
The name
"Stack Monitor" comes from the observation that modern software teams are increasingly operating AI systems as part of their core infrastructure stack — but the monitoring, observability, and cost management practices haven't caught up. The stack is changing. The monitoring has to change with it.