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An AI Book for People Who Hate AI Books

A business-first guide to using AI in a way that supports real workflows, clear ownership, and outcomes you can measure. Built to be finished, referenced, and applied, without the slog.

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The writing is intentionally readable and human. You will find quick, laugh-out-loud moments that keep the pace moving, while still getting concrete frameworks you can apply the same week. It is funny, insightful, and actionable by design.

What this book is, and what it is not

This is not a tour of AI features or a collection of motivational case studies. It is a practical guide to building AI into business systems where adoption, reliability, and accountability matter. The tone stays sharp and readable, with enough humor to keep it moving without losing the point.

How to choose the right AI use cases based on workflow impact, risk, and readiness
How to design AI outputs that support decision-making instead of creating noise
How to establish ownership, evaluation, and feedback loops that prevent drift
How to move from scattered experiments to durable capability across teams

AI is not a strategy. It is a capability.

The value comes from the system around that capability. Workflow fit, adoption, evaluation, governance, and operating cadence are what turn AI access into operating leverage.

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Who this is for

This book is written for leaders and teams who have AI access, but want a clear, credible approach to applying it inside real work. If you care about repeatability, adoption, and operational clarity, you will get value quickly. The tone stays engaging throughout, so it reads fast and sticks.

Operating leaders

For leaders responsible for execution, delivery quality, and adoption across teams and workflows.

Product and engineering

For teams building AI into products or internal systems, where evaluation and reliability determine success.

Customer and revenue teams

For teams using AI to improve throughput, enablement, and decision support without compromising trust.

What you will take away

The goal is practical. You should be able to make better decisions, build a stronger operating model, and move faster without creating chaos. The humor is there to keep you reading, not to dilute the substance.

Use case selection

A way to prioritize opportunities based on readiness, risk, and workflow value.

Reliability and evaluation

A framework for output quality, measurement, and iteration that fits your environment.

Adoption and ownership

How to define roles, operating cadence, and support pathways so AI stays useful over time.

Want the short version first

Start with the 15-minute AI Bottleneck Audit. You will walk away with a clear view of what is blocking reliable AI adoption and what to do next.

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FAQ

Answers to the most common questions, with a practical focus.

Is this a technical book

It is technical enough to be useful, but written for business and operating leaders. The focus is on systems, decision-making, workflow fit, and execution.

Is it actually enjoyable to read

Yes. The writing is intentionally readable, with sharp examples and laugh-out-loud moments that keep the pace moving. The humor supports the learning and keeps it from feeling like homework.

Does it cover AI tools and vendors

It addresses how to evaluate capabilities and fit, but it is not a vendor guide. The goal is to help you design the operating model that makes any tool perform.

Can I use this with my team

Yes. The frameworks are designed to be shared, discussed, and used to align leadership and delivery teams.

What is the best next step if we are stuck

Book the 15-minute AI Bottleneck Audit. It is the fastest way to diagnose the real constraint and identify the right next move without over-scoping.