An AI coding agent with a real codebase to read is a different animal from one spinning in an empty sandbox. Same model, same prompt — totally different output. The agent that wakes up to a tested component library, a config file declaring how things are structured, and a test suite that catches it when it drifts — that agent ships code you don't have to rewrite on Friday.
That's the actual enable. The context layer is the reason.
But every agent session in an ephemeral sandbox wakes up blank. No repo. No conventions. No history of how you wrote the last 50 components. So it improvises — and improvisation at scale is just entropy dressed up as velocity.
Here's the part that took me a while to internalize: "context" for a coding agent isn't chat history. It's not the previous turn. It's not memory across sessions. It's the files on disk that the agent can read. Every prompt is a fresh boot, and the only thing carried across turns is what the agent pulled into its window — which means the only thing carried across sessions is what the model can re-read when it starts.
What context actually is for an agent
