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Agentic AI Systems Automation With Python: Design autonomous workflows, tool integration, and structured task execution with language models
Paperback
Series: LLM Applications and Retrieval Systems, Book 1
Publisher: Independently Published
Published: May 9 2026
Pages: 200
Weight: 0.78
Height: 0.42 Width: 7.00 Depth: 10.00
Language: English
The material walks through how these workflows are designed, showing how tasks are structured, how decisions are made within the system, and how results are passed between steps. It also explains how to maintain state across interactions, allowing applications to remain consistent and context-aware even as tasks become more complex. Particular attention is given to how tools are integrated, enabling the system to retrieve information, transform data, and produce outputs that go beyond text generation.
In addition to building functionality, the book addresses the challenges that come with agentic systems, including reliability, control, and clarity of execution. Readers will learn how to structure their applications in a way that reduces unpredictable behavior and improves the overall stability of the system. This includes designing clear workflows, managing dependencies between steps, and ensuring that each part of the system contributes to a well-defined outcome.
By the end of the book, readers will have a clear understanding of how to build AI applications that can operate with direction and purpose. The focus remains on practical implementation using Python, making it possible to take the concepts presented and apply them directly to real projects involving LLM applications, automation workflows, and intelligent task execution.
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