Abstract
This survey paper explores the design patterns essential for constructing generative autonomous agents, a significant advancement over traditional LLM-based applications. These agents can independently plan, execute, and refine tasks, enabling them to overcome limitations such as the need for continuous human input and rules-based reasoning. I review four design patterns: reflection, planning, tool use, and multi-agent collaboration for building more efficient agents. Each is illustrated through a detailed, holistic analysis of a specific implementation technique.
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