Under the hood, Muse Code pairs a simple agent loop with persistent, async…
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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.
Context
Meta describes two mechanisms intended to keep Muse Code productive during long sessions. In its runtime post, background agents remain active throughout the session, allowing them to carry work forward without repeatedly gathering the same information.
A local log also appends each model call, tool execution, approval and edit. Meta says that record lets the runtime replay its history and recover after a restart. These mechanisms address different interruptions: repeated information gathering during normal work and lost continuity when the runtime stops. The post presents the design without an independent recovery test.
- 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.
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