A new research paper proposes a layered architecture for agentic AI using OpenClaw and Ollama. The system separates inference, orchestration, and execution to move beyond reactive LLM interfaces. It introduces a full-stack approach to memory and planning. This provides a structured blueprint for developers building persistent, goal-driven autonomous agents.