Google Antigravity. This item is unavailable.
Language: English
Published by Amazon Digital Services LLC - Kdp, 2025
- Softcover
- New
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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Softcover
Condition: New
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Item description from seller
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Seller Inventory # L0-9798279201822
- Title
- Google Antigravity
- Author
- Leo Hartmann
- Publisher
- Amazon Digital Services LLC - Kdp
- Publication year
- 2025
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 13
- 9798279201822
- Item weight
- 213 grams
- Series
- Book 1 of 2: Google Antigravity Blueprints Series
Manual coding is no longer the primary constraint in software development—coordination is.
In Google Antigravity: The Agentic Development Blueprint, you will learn how to replace syntax-driven workflows with agent-orchestrated development, using Google Antigravity as a command center for autonomous AI systems.
This book focuses on the foundations of agentic engineering. You will learn how to design specialized agents, structure high-leverage missions, and engineer context that enables consistent, high-quality output. Most importantly, it introduces verification and trust mechanisms—including artifact reviews, execution replays, and code diffs—so you can confidently audit AI-generated work before it reaches production.
Rather than treating AI as a code-completion tool, this book teaches you how to think like a software architect, directing parallel agents to execute complex tasks while you focus on system design and decision-making.
By the end of Book I, you will have a clear, repeatable framework for building software through autonomous collaboration, without surrendering control, quality, or accountability.
In Google Antigravity: The Agentic Development Blueprint, you will learn how to replace syntax-driven workflows with agent-orchestrated development, using Google Antigravity as a command center for autonomous AI systems.
This book focuses on the foundations of agentic engineering. You will learn how to design specialized agents, structure high-leverage missions, and engineer context that enables consistent, high-quality output. Most importantly, it introduces verification and trust mechanisms—including artifact reviews, execution replays, and code diffs—so you can confidently audit AI-generated work before it reaches production.
Rather than treating AI as a code-completion tool, this book teaches you how to think like a software architect, directing parallel agents to execute complex tasks while you focus on system design and decision-making.
By the end of Book I, you will have a clear, repeatable framework for building software through autonomous collaboration, without surrendering control, quality, or accountability.
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