Written from mid-climb.
Not the polished retrospective. The actual experience of building a company with AI—including the parts that didn’t work.
What this book is about
Infinite Leverage is the memoir of building a company with AI agents—honest, from mid-climb, about what works, what broke, and what differed from the plan. The jump from “AI that answers questions” to “AI that executes tasks” is the distance between a calculator and an employee. Most people haven’t adjusted to that yet.
After 30+ years in enterprise integration, Dave Lawler walked away from the corporate track and started building. The first project was Velocity Point, stood up in a weekend. Then came Second Ring, a real business where AI agents do the code, the ops, the marketing, and the customer service. This book is the story of that build as it happened.
Most books on AI are written either by people who haven’t shipped anything with it, or by people who already sold the company and are writing the hero narrative. This book is neither. It’s written while the thing is still being built—so the lessons are raw, and the mistakes are still visible.
If you’re trying to decide whether to build with AI (not just use it), this book is a field report from someone who made that jump.
Who this book is for
Solo Founders
You’re one person with an idea. You need to know whether “one person with AI” actually builds what it promises, or whether you still need a team of ten.
Builders, Not Just Users
You’re done using AI as a chat toy. You want to give it work—real work, with real stakes—and you want to know what that actually feels like day to day.
People on the Edge
You’re the engineer or operator quietly asking: should I quit my job and try this? This book won’t make the decision for you, but it will show you the actual view from the other side.
Skeptics Who Want Detail
You’ve heard the hype and you’re tired of it. You want to know what AI actually did, what it failed at, and what a human still had to do by hand. No evangelism—just the logs.
Concrete takeaways, not vague promises
- How to pick the right first project. The projects that work with AI look nothing like the ones that get written up in blog posts.
- When to trust AI output and when not to. A practical calibration from thousands of real agent sessions, not a vendor slide deck.
- The unglamorous plumbing that makes it work. Context files, prompt discipline, pull-request hygiene, test harnesses—the boring stuff that turns demos into companies.
- How to run multi-agent teams. What to parallelize, what to serialize, and how to keep the whole thing from collapsing into a pile of half-merged branches.
- What AI still can’t do for you. The judgment calls, the taste, the customer conversations. The parts that are still yours and always will be.
- What compounding actually looks like. Why the leverage is called “infinite”—and where the real ceiling is.
Ready to see the full arc?
Twelve chapters, four parts, one company going from notebook to launch.