Planner
A classic component in multi-agent systems in which a dedicated LLM instance takes responsibility for task decomposition, breaking a high-level problem into subtasks, dispatching them to execution agents, and aggregating the results.
Timeline (last 90 days)
TinyFish's deep research system abandoned the standalone planner and per-query subagents.
TinyFish's engineering team found that the hierarchical structure of a standalone planner plus per-query subagents brings coordination overhead and information loss in deep research scenarios.
The planner is a classic component in multi-agent systems, typically a dedicated LLM instance responsible for task decomposition, breaking the user's high-level problem into subproblems or subtasks, dispatching them to execution agents, and finally aggregating the results.
Most AI agent frameworks lack an explicit mechanism for checking plan validity, and planners are typically designed for one-shot planning rather than continuous replanning.
LLM-based planners do not rely on formal state-space search but instead use the commonsense and reasoning abilities of language models to generate plans, and therefore lack explicit modeling of plan preconditions.
All Facts (5)
TinyFish's deep research system abandoned the standalone planner and per-query subagents.
50%UnverifiedTinyFish's engineering team found that the hierarchical structure of a standalone planner plus per-query subagents brings coordination overhead and information loss in deep research scenarios.
50%UnverifiedThe planner is a classic component in multi-agent systems, typically a dedicated LLM instance responsible for task decomposition, breaking the user's high-level problem into subproblems or subtasks, dispatching them to execution agents, and finally aggregating the results.
50%UnverifiedMost AI agent frameworks lack an explicit mechanism for checking plan validity, and planners are typically designed for one-shot planning rather than continuous replanning.
50%UnverifiedLLM-based planners do not rely on formal state-space search but instead use the commonsense and reasoning abilities of language models to generate plans, and therefore lack explicit modeling of plan preconditions.
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