Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
The Execution Age: Building, Deploying, and Governing Autonomous AI Systems in the Agentic Era

The Execution Age: Building, Deploying, and Governing Autonomous AI Systems in the Agentic Era

Royce, Taylor

Paperback

Series: Books on Tech, Book 113

Business General

ISBN13: 9798258955920
Publisher: Independently Published
Published: Apr 26 2026
Pages: 128
Weight: 0.40
Height: 0.27 Width: 6.00 Depth: 9.00
Language: English
A new stage of artificial intelligence has begun. Formerly text-generating and question-answering systems may now plan tasks, carry out workflows, use tools, and make decisions that have an influence on the actual world. The era of AI that acts has replaced the era of AI that speaks.

A useful, highly influential manual for comprehending and developing this new kind of autonomous AI systems is the Agentic AI Playbook. This book goes beyond theory to demonstrate how agentic systems are created, implemented, and managed in practical settings. It is written for developers, engineers, product leaders, and forward-thinking professionals.

You'll learn how AI agents truly operate within, from memory systems and multi-agent cooperation to reasoning loops and tool usage. You'll discover how to create agents that can deconstruct complicated objectives, carry out tasks gradually, and adjust in response to immediate input. In order to help you create systems that function in practice rather than merely in demonstrations, the book also guides you through the realities of production deployment, including dependability issues, cost control, security threats, and system failures.

You will get lucid, useful understanding of:

  • Creating self-sufficient AI entities that organize and carry out activities
  • Linking models to data systems, APIs, and real-world tools
  • Creating multi-agent processes for tackling challenging problems
  • Controlling production's performance, expenses, and dependability
  • Protecting systems from threats like abuse and rapid injection
  • Using agentic AI in enterprise, business, and software use cases

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