Layered Architecture of Agentic AI
Roger_M_Taylor · x · 2026-07-19
This diagram breaks down Agentic AI into four layers:
- LLMs: The foundation, comprising tokenization, reasoning, prompt engineering, context engineering, and fine-tuning.
- AI Agents: Introduces ReAct, Chain-of-Thought, state management, long-term memory, task planning, multi-step tool usage, safe interrupts, and fail-safe designs.
- Agentic Systems: Connects multiple agents and external tools via protocols like MCP and A2A, covering routing, scheduling, collaboration, agentic RAG, and error handling.
- Agentic Infra: The underlying layer for governance, security, privacy, access control, observability, monitoring and logging, and bias/fairness controls.
This is an engineering-focused layered diagram, perfect for understanding the full capabilities needed to build a "running agent system" beyond just the model itself.
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