The Enterprise AI Operating Manual
A practical blueprint for operating AI systems in the real world
The Enterprise AI Operating Manual is a foundational reference for organizations that are already running AI in production and are now dealing with its long-term implications.
It documents what it takes to design, operate, and govern AI systems that must remain defensible over time, across teams, and under real organizational pressure. The manual is built from lived enterprise experience; where systems are live, assumptions are tested, and decisions need to be explained, defended, or corrected.
Rather than treating AI as a sequence of projects, the manual uses a puzzle model to describe how enterprise AI systems truly operate. Each chapter corresponds to one essential piece of that puzzle, addressing a capability that must be in place for the system to function under real-world conditions.
What this helps you do
This collectible series is written for leaders who are accountable for AI once it is live and relied upon.
It is designed to help them:
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Identify where AI systems quietly degrade after deployment
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Understand why operational costs rise even when models appear to perform well
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Put structures in place before failures turn into escalations or compliance issues
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Reduce manual workarounds created by systems teams no longer fully trust
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Build governance and operating models that scale without accumulating hidden debt
All Chapters
Chapter 1: Reliability
How AI systems behave over time, and what breaks when reliability is treated as an afterthought.
Chapter 2: Explainability
How to ensure AI decisions can be understood, reviewed, and defended when challenged.
Chapter 3: Security & Compliance
How to ensure AI remains under organizational control as it scales across data, teams, and external services.