Check out the 8 Architectural Layers of Agentic AI, from infrastructure to decision-making and governance. 1️⃣ Infrastructure Layer: Foundational components that include APIs, cloud infrastructure, data storage, and orchestration systems that support reliable operations. 2️⃣ Agent Internet Layer: Enables communication and coordination between distributed components.It supports protocols, memory modules, and shared data networks. 3️⃣ Protocol Layer: This layer defines standard communication methods for agents, capabilities, and task execution across tools and platforms. 4️⃣ Tooling and Enrichment Layer: Provides access to external tools, retrieval systems, code execution environments, and other utility modules for task completion. 5️⃣ Cognition and Reasoning Layer: Manages decision-making, planning, error handling, and feedback. It enables systems to adapt and improve based on results. 6️⃣ Memory and Personalization Layer: Maintains short-term and long-term memory, user preferences, identities, and behavioral patterns to support contextual responses. 7️⃣ Application Layer: Interfaces that users interact with, including assistants, content generators, research tools, and collaborative agents. 8️⃣ Operations and Governance Layer: Focuses on system reliability, observability, compliance, and cost optimization. Provides governance frameworks and oversight tools. A structured approach is essential for building scalable, secure, and effective systems. This guide covers the core building blocks required for consistent performance and adaptability in real-world use cases. Save for future reference, and let me know your thoughts below! #genai #artificialintelligence | 64 comments on LinkedIn