Matt leads AI strategy at Point of Rental Software, where he's transforming how thousands of equipment rental businesses operate globally through mobile, fintech, and AI platforms. He's also built one of the first AI-first development workflow engines in the industry, a systematic approach to context engineering that's turning skeptics into power users and compressing months of work into weeks.

Starting his career at 14 building software to pay for school, Matt has consistently worked at technology's bleeding edge: from building one of the first cloud-based web applications in the early 2000s to pioneering mobile-first enterprise solutions. Now he's implementing generative AI not just as a development tool, but as the interface that fundamentally changes how rental businesses interact with their software and how development teams build software in the first place.

What sets Matt apart is simple: he builds AI for people who don't care about AI. His customers care about equipment uptime, not algorithms. They need faster invoicing, not chatbots. This reality check drives everything from killing features that demo well but fail in the field, to building solutions that work on muddy job sites with spotty internet. He's not interested in what's possible with AI; he's interested in what's useful.

His Developer Handbook methodology teaches teams the difference between "vibe coding" (hoping AI figures it out) and context engineering (systematically giving AI what it needs to succeed). The results speak for themselves: converted skeptics, compressed timelines, and teams shipping work they didn't think was possible.

Matt speaks on practical AI implementation, including:

"From Stuck to Started: Your Practical Guide to AI" Battle-tested strategies that work whether you're on day one or year three of AI adoption.

"Beyond the Band-Aid: Stop Treating AI Like a Feature" Why stopping at AI assistants is denial, not innovation, and what happens when you rebuild for this new reality.

"Stop Prompting, Start Engineering" The difference between developers who gave up on AI and those getting breakthrough results isn't talent, it's discipline. Learn the systematic approaches (context engineering, agent orchestration, AI-first workflows) that treat AI like the engineering challenge it is, not a magic box you hope figures it out.

His sessions blend technical depth with business strategy, delivered with the candor of someone who's shipped products that both flopped spectacularly and scaled globally.

His current focus: building software that acts as a business's central nervous system, anticipating needs rather than waiting for commands. Think less "AI assistant" and more "AI that knows to order parts before equipment breaks."