How to Build Autonomous AI Agents in Python Using Orchestration Patterns

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Autonomous AI agents are software systems that can plan multi-step workflows, use external tools, self-correct, and retain memory without constant human intervention. At their core, these agents require a reasoning engine such as an LLM, tool access, memory systems, and a planning loop following an observe-think-act cycle. A developer guide published on DEV Community demonstrates how to implement a minimal working agent in Python using the ReAct pattern with OpenAI's GPT-4 API. The guide recommends starting with three to five well-defined tools and a narrow task before incrementally adding complexity. It also outlines practical use cases including code review bots, research assistants, and customer support agents, each with varying tool requirements and complexity levels.

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