PostHole
Compose
Login
From Michigan to Silicon Valley: A Conversation With Mohamad Yassine
Lessons on humility, careers, the automotive sector, “cowboy coding” and disrupting with AI from a lifelong innovator.
From Michigan to Silicon Valley: A Conversation With Mohamad Yassine
Lessons on humility, careers, the automotive sector, “cowboy coding” and disrupting with AI from a lifelong innovator.
March 01, 2026 •
[A car steering wheel, dashboard and display with graphics representing autonomous driving.]
Adobe Stock/metamorworks
Back in the year 2000, just after we completed our state of Michigan Y2K remediation, all eyes in the government technology world turned to new Internet opportunities, building websites and web applications, and moving government services like driver’s license renewals and campground reservations online.
In the Michigan Department of Management and Budget (DMB) at that time, we built a “rapid web development team” to bolster our new Internet efforts, which eventually got rolled into our e-Michigan team. Over time, we launched michigan.gov, which was the first state (or local) government “dot-gov” portal.
Fortunately, Ric Tombelli, who was our outstanding webmaster at the time and who worked for me when I was the Michigan DMB CIO, hired Moe Yassine straight out of Michigan State University. Moe was — and is — an energetic entrepreneur, who went on to start his own company before joining Ford Motor Company managing next-generation diagnostics. From there, Moe became the engineering manager over diagnostics for Tesla before moving to Google to become their head of North America OEM engagements for the Android Automotive Partner Engineering and later the head of systems engineering for that same Google organizational unit.
And in January 2024, he became the co-founder and CEO of a new AI company called Predictive Horizons. The firm is now doing groundbreaking AI work that has been highlighted by Inc. Magazine and many others.
I reached out to Moe and asked him for an interview, and he agreed. What follows is that conversation.
Dan Lohrmann (DL): What excites you about applying AI to the auto sector?
Mohamad Yassine (MY): The most exciting thing is really helping the industry as a whole thrive by giving the people on the front lines the tools they need to remove their biggest roadblocks. I grew up only a few blocks away from Ford World Headquarters, and I often tell people that these companies, whether in the United States or overseas, are the lifeblood of so many communities. And one of the most gratifying aspects of this industry is in service engineering and operations. You get to touch a part of the auto sector where you deal directly with real people, whether that be a service engineer, a service technician, a service adviser or the customer themselves. It’s a very humbling experience to be able to contribute to the part of the industry that’s not only underserved but has a massive impact on the overall health of the industry and its ability to innovate.
DL: Where did the idea for Predictive Horizons come from? Why is this company needed now?
MY: Our ultimate goal is to develop a “minority report” for cars that essentially can know what’s wrong with a vehicle before the customer even experiences the symptoms. Between myself, Jason and Dave (my co-founders), we all had different experiences within the auto industry. Jason was one of the early pioneers of using data science to solve these vehicle problems. I remember once he presented a neural network he trained over a weekend to diagnose issues at Tesla, and we all just sat there amazed as he was showing us the accuracy compared to what the technicians were doing, just dumbfounded that he could do something like that over the weekend. Dave is our resident “car guy” who grew up loving cars all his life and built out the service organizations of both Tesla and Rivian. If he’s not with us or his kids, you’ll probably find him under one of his nine cars or figuring something out for a family member’s car. And for me it was really the software engineering and problem solving that I loved about this, the sheer scale of the systems and how best to present information to users, the closeness to the customer experience that just made me love this space. And we all felt like we had unfinished work, and for whatever reason the stars seemed to align when we decided to do this.
In any industry, as innovation accelerates you tend to see quality take the biggest hit; it’s sort of the natural order that this will happen. The auto industry specifically has been going through a lot of innovation lately, but we even see it in other industries. And we see many companies out there who are on the other side of the quality equation, building products and services that ultimately serve product development with the philosophy that if you catch problems earlier in the design process it costs you much less to handle it. This philosophy, however, misses some really important factors: First, that when you are moving to innovate as fast as you can, you will ultimately break things. Second, if you are constantly moving fast, and aren’t able to contain these problems early or effectively, your post-sale costs skyrocket not only hitting your bottom line but also severely impacting your brand loyalty and the customers’ experience with your product. And we see that only accelerating as competition heats up, we only see that automakers will need to “step on the gas” even more.
DL: How is AI risky or overblown in 2026? Are companies overpromising?
MY: I believe AI presents us with an unbelievable opportunity, one that could change the course of history on par with the Industrial Revolution. But I do think we need to also move with caution. To me it’s clear we’re operating in an AI bubble where companies are overpromising near-term capabilities to keep up with the hype. And while everyone is eager to discuss the immediate impacts of AI, there isn’t nearly enough talk about the risks it poses when used irresponsibly even in its current iteration.
[...]