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Agentic Prompt Stack

The Agentic Prompt Stack is a 6-layer model for designing prompts that run AI agents: Goals, Tool permissions, Planning scaffold, Memory access, Output validation, and Error recovery. Unlike one-shot prompt structures, the Stack organizes agent prompts by the layers where they typically fail — which makes debugging tractable, because each symptom maps to a specific layer to inspect and fix.

Example

A research agent's prompt split by Stack layer: Layer 1 Goals define what "done" means; Layer 2 Tool permissions list which APIs the agent may call; Layer 3 Planning scaffold enforces a plan-execute-reflect loop; Layer 4 Memory access scopes recall to the last 3 steps plus a running summary; Layer 5 Output validation checks a JSON schema; Layer 6 Error recovery defines retry behavior on tool failures.

Related Terms

Agentic AIAutonomous AgentTool Use (Function Calling)ReAct PromptingFunction Calling

Related Resources

Blog Post

The Agentic Prompt Stack: 6 Layers for Designing Prompts That Run Agents

The Agentic Prompt Stack organizes agent prompts into 6 layers — Goals, Tool permissions, Planning scaffold, Memory access, Output validation, Error recovery — so failures map to a specific layer to fix.

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