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The Kind of AI Work I Want to Build Over the Next Decade

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AIMachine LearningTechnical LeadershipRoboticsApplied AIInnovation

Illustration: a person walks a long winding path across a landscape, past a stack of papers, a robot arm, gears, and a workshop, toward a teal sun rising on the horizon.

The kind of AI work I’m most interested in building over the next decade sits at the intersection of research depth, systems discipline, and real-world usefulness.

I’m interested in AI that does more than generate impressive outputs. I’m interested in systems that can interpret, decide, and act more responsibly under real constraints.

That is why I keep coming back to grounded language understanding, multimodal learning, robotics, data infrastructure, applied AI systems, and product design.

But it is also why my perspective on AI has been shaped by more than research alone. Working across embedded systems, software delivery at scale, technical leadership, hiring, team development, and company building has made me care deeply about whether a system is not only capable, but dependable.

To me, the future of strong AI work is not just bigger models. It is better systems. Better data. Better judgment. Better engineering. And better translation from capability into something people and organizations can actually rely on.

That is the kind of work I want to keep building, leading, and helping bring into the world.

Originally posted on LinkedIn.