agentic AI, defining it as an autonomous problem-solving system capable of breaking down complex goals and utilizing tools independently. They explore multi-agent systems, emphasizing the collaborative nature of specialized AI agents working together through various frameworks like CrewAI, LangGraph, AutoGen, and BeeAI, each employing distinct design philosophies for agent interaction. The sources further detail fundamental AI workflow patterns, including sequential processing (prompt chaining), intelligent task distribution (routing), and concurrent task execution (parallelization). Additionally, they describe advanced design patterns such as the Orchestrator for dynamic task management and the Evaluator-Optimizer for iterative improvement through feedback loops, while also outlining best practices for building production-ready multi-agent systems with features like tools and structured outputs.

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