# The Architecture of Agentic Workflows
Agentic workflows represent the shift from static LLM prompts to dynamic, self-correcting systems. In this course, we explore the structural foundations required to build reliable autonomous agents for Enterprise AI.
## 1. The Reasoning Loop
Modern agents operate on a cycle of Perception, Reasoning, and Action (ReAct). Unlike simple chatbots, agents maintain state and evaluate the outcomes of their own actions against predefined goals.
## 2. Tool Integration & Orchestration
Teaching LLMs to interact with external APIs is the "limbic system" of agentic architecture. We discuss the security implications of executable code and the necessity of sandbox environments in B2B SaaS.
## 3. Resilience in Autonomy
How to handle non-deterministic outputs and infinite loops in production-grade AI agents.
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