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Description
Summary
This issue proposes a design approach for the AgenticLoop project: separating the Plan and Executor components, inspired by the architectural principles used in OpenCode.
Motivation
Decoupling planning from execution can enhance system scalability, maintainability, and modularity. It enables flexible agent behavior adaptations, easier experimentation, and clearer debugging processes.
Proposed Design
- Plan Component: Responsible for generating tasks, strategies, or action sequences based on goals and context. The planner should accept high-level objectives and return structured plans (e.g., step/task lists).
- Executor Component: Interprets and carries out the plan. The executor manages progress, handles errors, and interfaces with lower-level system capabilities. It should report status and feedback to the planner for dynamic adjustments.
Reference: OpenCode Design
Refer to OpenCode’s mechanism of separating planning logic from executors for robust AI agent workflows. Their implementation and documentation may be helpful references for details on task structure, error handling, and module communication.
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