sage-agent-execution

You can orchestrate AI subagents in Rust by using a UnifiedExecutor engine that coordinates LLM calls, tool execution, and subagent coordination with lifecycle management. It provides a modular design for scalable integrations without relying on nonstandard runtimes.

Managing the lifecycle of AI agents during codebase exploration requires a state machine that handles interruptions and error recovery. A unified execution engine provides robust automation by coordinating specialized subagents like Explore and Plan with inherited working directories.

Setting up task planning and automated execution workflows involves initializing a UnifiedExecutor with default settings to coordinate subagents. The engine supports Explore, Plan, Execute, and GeneralPurpose subagents to handle complex code tasks across large projects.

Yes, a unified execution engine coordinates LLM calls and enforces explicit tool access controls for software engineering workflows. It establishes clear integration boundaries for automated planning and codebase exploration without depending on nonstandard runtimes.

The Rust subagent system supports error recovery and interruption handling through lifecycle management with a state machine. This ensures robust automation by maintaining execution state and enabling recovery during complex multi-agent task execution.