OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems
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arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural understanding of Agentic AI, particularly in separating inference, orchestration, and execution layers for autonomous AI agents. Despite recent advances, unified frameworks for designing and evaluating full-stack agentic systems remain limited. This paper presents a comprehensive, layered architecture…
1Key Takeaways
- Despite recent advances, unified frameworks for designing and evaluating full-stack agentic systems remain limited.
- This paper presents a comprehensive, layered architecture….
2AIWedia Score
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3Why it matters
Research breakthroughs often arrive in products months later—early signals matter for strategy. arXiv cs.AI reports that despite recent advances, unified frameworks for designing and evaluating full-stack agentic systems remain limited.
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