Founder & CEO
Throughout my life, I've found myself standing in the spaces between worlds - translating perspectives across the divides of people’s understanding and experiences. My journey to founding Composabl begins with understanding that these translation skills are essential to creating a bridge between the excitement of AI concepts and their practical application in the industrial and manufacturing industries.
The Bridge Builder
Growing up in New England, I was constantly translating between worlds. As one of very few African Americans in my community, I certainly didn’t feel like I belonged in the Caucasian group, but I didn’t feel that I quite belonged in the African American group either.
My father – born in 1916 – was quite a bit older and I often felt more comfortable around his peers than my own. My father was also a uniquely gifted teacher, and I can see his influence in how I communicate and think about the world.
After studying mechanical engineering, I began my career at IBM. I then moved into startups where I found myself in a familiar position of being between worlds and translating. I was too technical for the marketing team but also often told I was too sales-oriented for the engineers.
It took me a while to realize that this was actually a superpower: the ability to sit in one place, understand both perspectives, and translate between them.
This realization, combined with the teaching sensibilities I inherited from my father, revealed a significant opportunity to bring together the worlds of AI and engineering.
From Code to Teaching
In 2017 I learned about a concept called “machine teaching” while working at a startup called Bonsai. This concept was revolutionary, yet intuitive: If machines can learn, we should probably teach them something.
In that moment, it all clicked. Machine teaching was the bridge between AI and engineering, and my life’s work would be to build that bridge.
I’m going to switch into teacher mode with a quick history lesson in AI. The first incarnation of artificial intelligence was physically embedded in machines, think PID controllers. Then came software, where programming became an interface to leverage various capabilities of the machines they controlled. More recently the conversation has shifted to machine learning, but machine learning is still heavily dependent on coding and data.
Machine teaching is the next logical step in AI evolution. Teaching – at its core – doesn’t require advanced coding skills or a PhD in machine learning. You just need to properly leverage the expertise the teacher already possesses. It's how humans have always transferred knowledge, and it removes the barriers for participation in the AI revolution – if only we could effectively bridge the gap.
I knew that this approach would not only engage industrial subject matter experts but create an opportunity for AI to be practically applied in industrial automation spaces to do things never done before.
What Industry Taught Me
I have traveled to factories, mines, warehouses, and steel mills all over the world. I’ve spoken with both executives and operators to watch their manufacturing and logistics processes and understand how to build AI that was useful to improving their operations.
By interviewing these leaders with decades of valuable experience in making things – products we use every day like Cheetos, soap, and steel – I began to understand how engineering expertise could be “taught” to an autonomous AI system. And as I watched them teach each other, the method to teach a machine became clearer than ever.
These experts didn't teach each other to read manuals or understand procedures. Instead, they taught each other strategies: "When the situation is like this, you should use this strategy. When the situation is like that, you should use that strategy." It reminded me of chess masters exchanging gambits.
Like a chess gambit, their skills were modular – they broke things down to base components and used those components to build. All these engineering experts lacked was the appropriate tool that would allow them to translate their expertise to a machine.
Building Composabl
Mimicking the skills transfer of these engineers became the foundation for Composabl. By translating between an engineer’s real-world expertise and advanced machine learning, we've created a tool that empowers engineers to build intelligent systems the same way they build everything else – on a teachable, modular AI framework.
When a multi-agent AI system is built this way, it’s easier to test, validate, and explain. Engineers can create exploded-view diagrams to understand exactly how each part of the system contributes to the whole. AI doesn't have to be a black box.
Technology That Empowers Engineers
This is why I don’t believe in the whole “AI is going to replace people” argument. The internet didn't replace people. Databases didn't replace people. The cloud didn't replace people.
Each technology translated complex capabilities into accessible tools that amplified what people could accomplish. This isn't about replacing engineers - it's about empowering them.
Working first at Bonsai, then Microsoft, and now Composabl, I've seen firsthand how this translation approach truly empowers engineers of industry. I’ve come alongside these engineers to design over 200 modular autonomous AI systems that make high-value decisions in industrial settings, always with the engineers themselves playing the central role.
I've watched these engineers receive multiple promotions because of the AI systems they built - using an interface designed specifically to capture their expertise.
Now our goal is for millions of engineers who make and move things in our economy to leverage machine teaching methodology to build intelligent systems that automate, augment, and extend their capabilities. We want to help preserve and amplify high-value technical skills at a time when manufacturing is experiencing a renaissance in the United States.
By translating between industrial expertise and artificial intelligence, we're ensuring that the next revolution in AI will serve the engineers who build, make and move things in our physical world. This is the bridge that needs building, and it's where having the right tools in your toolbelt makes all the difference.
