Under the hood, Muse Code pairs a simple agent loop with persistent, async background agents that stay active throughout each session to execute next steps, avoid redundant info gathering, and reduce steering on complex tasks.
An append-only local event log tracks every model call, tool run, approval, and edit, making the runtime replay-exact and restart-safe for long-running workflows.
agentic loop — The cycle an agent runs in: decide, call a tool, read the result, decide again — repeating until the goal is met or a stop condition fires.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Why it matters
Persistent background subagents plus an append-only event log is a directly borrowable pattern for anyone building long-horizon AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → harnesses, and it shows how a frontier lab is resolving context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → and steering costs.
