Most developers still treat large language models as one-shot responders. The systems that deliver real value today are agents. Python programs that can reason through multi-step goals, call tools, maintain memory, recover from errors, and collaborate with other agents.
AI Agents in Python is a practical guide to building these systems with the frameworks that matter: LangChain, CrewAI, AutoGen, and related tools. It moves from core agent concepts and Python foundations through tool integration, advanced reasoning patterns, multi-agent coordination, production deployment, and the ethical considerations required for reliable use.
The emphasis is on working code, clear architectural patterns, and the decisions that turn experimental prototypes into systems that can handle real tasks. Written for Python developers, data scientists, and engineers ready to move beyond chat interfaces into autonomous, tool-using AI.
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