Vivek Trivedy's "The Anatomy of an Agent Harness" is one of the better-written article on AI agent infrastructure this year. It defines the harness clearly — "Agent = Model + Harness; if you're not the model, you're the harness" — and systematically derives each component: filesystem for durable storage, bash for general-purpose tool use, sandboxes for safe execution, memory for continual learning, compaction for context management, the Ralph Loop for long-horizon work.
The infrastructure engineering is real and useful. The derivation from model limitations to harness features is clear. If you're building an agent, you need most of what the article describes.
The problem isn't what the article covers. It's the frame the article thinks in, and it's worth naming precisely because it's the same frame the entire industry uses.
The engine is not the car
"Agent = Model + Harness" is "Car = Engine + Harness." That equation tells you what the builder thinks is the system and what's just support infrastructure.
