Builder Mindset: Jeff Butler on Systems, AI, and Why Most Projects Break | Hatch Podcast

What separates systems that scale from systems that fall apart?

For Jeff Butler, it starts with understanding the problem before writing a single line of code.

In this episode of The Hatch Podcast, Jeff shares how a self-taught path from building simple websites in the ‘90s turned into a 30-year career working with large-scale systems, infrastructure, machine learning, and AI.

Along the way, the conversation covers everything from early web development and massive business data sets to weather satellites, usability, infrastructure, and the hidden problems most companies don’t realize they have.

Jeff also explains why many businesses rushing into AI are building on top of messy, disconnected data—and why that creates bigger problems down the line.

This episode is a look at how a longtime builder thinks about systems, problem solving, and creating technology that actually works in the real world.

💡 In this episode:

• How Jeff taught himself web development in the early days of the internet
• Why “data is data” across industries and systems
• The satellite project that started with watching the ISS with his son
• Why usability and infrastructure matter more than most people think
• The danger of relying too heavily on third-party tools
• What businesses are getting wrong about AI and dirty data
• Lessons learned from 30 years of building systems

About the Guest

Jeff Butler is a senior DevOps and systems engineer with more than 25 years of experience building cloud infrastructure, large-scale data systems, automation workflows, and AI-powered applications.

His work spans industries including e-commerce, aerospace, biotech, machine learning, and real-time satellite data systems.

Jeff Butler: https://jeffbutler.dev/