The Planner Made the Same 3 Mistakes Every Time. A Bigger Model Didn't Fix It.

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Directly relevant to LLM agent orchestration with technical depth and actionable insights on multi-agent critique systems.

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Why It Matters

For engineers building agentic or multi-LLM systems, this confirms that scaling model size alone won't fix planning failures—you need deterministic dependency and sequencing validation in your orchestration layer.

Key Takeaways

Add a deterministic dependency graph checker and sequencing validator to your planner agent before relying on revision loops or model upgrades.

The Planner Made the Same 3 Mistakes Every Time. A Bigger Model Didn't Fix It.

Summary

An open-source planning engine, PlannerCritic, revealed three recurring defect families across 132 blockers in a 63-goal field test: unverified dependencies (57 blockers), unsafe sequencing (46 blockers), and weak rollback (18 blockers). Upgrading from a smaller model to GPT-4o for the planner role did not eliminate these structural failures—the same patterns persisted with better prose. The revision loop converges after a median of 2 iterations, but the planner cannot fix dependency graph or ordering issues by rewriting text; the fix requires deterministic validation, not larger models.

Author

Debashish Ghosal