Insights
Ideas behind the private inference cloud.
The servescale.ai thesis in three essays: don’t scale up infrastructure blindly, don’t use giant models for every task, and prepare for AI to move from developer playground to CIO-managed platform.
Infrastructure economics
Don’t Scale Up TL;DR
The core argument: the room is the architecture. Power, topology, cache locality, and utilization matter more than simply buying bigger GPUs.
Model economics
Don’t Scale Up Part 2: The Model Edition
Production AI should use right-sized models, tools, retrieval, validators, and selective escalation - not one giant model for every job.
Enterprise platformization
The Inevitable Path of AI
AI is following the pattern of virtualization, cloud, and Kubernetes: developer-led experimentation becomes CIO-managed infrastructure.