Sample Chapter

Let me tell you about the worst deployment advice I ever gave.

A founder reached out to me in 2023. She'd used Claude to build a beautiful SaaS app in three weeks. The product worked. Users wanted it. She just needed to deploy it.

"Should I use Docker?" she asked.

And I—with 15 years of experience and the smug confidence of someone who's deployed hundreds of applications—said yes. Of course she should use Docker. Everyone uses Docker. Best practices, right?

Three weeks later, she still hadn't deployed. She was stuck in Docker hell, fighting with container orchestration, environment variables, and networking configs. Her users were waiting. Her momentum was gone.

That's when I realized: all my experience was making me a worse advisor for AI-coded apps.

The Problem with "Best Practices"

Here's what happens when you ask experienced engineers about deployment:

• • They'll recommend Docker (because isolation)
• • They'll suggest Kubernetes (because scaling)
• • They'll mention microservices (because modularity)
• • They'll talk about CI/CD pipelines with 12 stages

And all of this advice is technically correct. For the wrong problem.

These "best practices" assume you have:

1. A team of engineers who understand deployment
2. Thousands of users requiring serious scaling
3. A codebase you'll maintain for years
4. Budget for DevOps tools and infrastructure

But if you're a founder who used AI to build an MVP in Replit, you have:

1. Zero users (yet)
2. No DevOps experience
3. Code you might throw away next month
4. Limited budget and time

Same words. Completely different problems.

The Three Pillars of Sustainable Deployment

After helping dozens of founders deploy AI-coded apps, I've distilled deployment down to three non-negotiable principles:

These principles might sound obvious. But I've watched hundreds of founders violate them because someone with "experience" told them to use Kubernetes.

Why This Matters More for AI-Coded Apps

AI coding tools changed the deployment game in ways most people haven't recognized yet:

You ship faster. What used to take months now takes weeks. But if deployment takes days to figure out, you've eliminated all the gains from AI coding.

You iterate more. AI lets you try 5 different approaches in the time it used to take to build one. But only if you can deploy each iteration quickly to test with real users.