A new research paper proposes a layered architecture separating inference, orchestration, and execution for autonomous systems. It utilizes Ollama for the LLM inference layer and OpenClaw to handle goal-driven execution. This framework moves beyond reactive interfaces toward persistent agents with memory. Practitioners can now better evaluate full-stack agentic systems through these distinct architectural layers.