dailyai.report

A new research paper proposes a layered architecture separating inference, orchestration, and execution for autonomous agents. It utilizes Ollama for the inference layer and OpenClaw to handle persistent, goal-driven execution. This framework aims to bridge the gap between reactive LLMs and full-stack agentic systems. Practitioners can now better evaluate scalable, action-capable AI workflows.