We talk a lot about the AI revolution in terms of models, chips, and software. But to make it a reality, there needs to be a huge buildout of physical infrastructure like data centers and semiconductor fabs. And that's where we have a problem. While we're focused on the race for AI talent, we also have a shortage of skilled tradespeople—the electricians, the HVAC technicians, the welders—who are essential to building this physical infrastructure. The government's new AI Action plan creates a forcing function to solve this. There's a big emphasis on a "worker-first" agenda, and directions to the Departments of Labor and Commerce to fund new rapid retraining programs for exactly these kinds of physical labor jobs. This creates opportunities for startups. We want to fund startups building a new kind of vocational school for the AI economy to train people for these jobs. We think you could use AI to create personalized training programs to get people job-ready in months, not years. The challenge is, how do you teach someone to weld or fix pipes via AI? Unlike coding, you can't learn these skills by typing on a keyboard — you need to learn by practicing them in the real world. This is where multimodal AI could create opportunities — for example, maybe a voice AI could coach someone through these tasks. Or perhaps some combination of AR/VR could let people practice the work in simulation with an AI tutor using vision models to watch them and give feedback. It's clear how you'd make money from this business — employers would pay to hire your well-trained workers. In the past, these types of training businesses — like coding bootcamps — have struggled to expand because it's hard to scale the quality of human tutors, but AI might solve this problem too. If you can make one effective AI teacher, it'll scale infinitely. This is a chance to build a huge business that lets everyone benefit from and participate in the new AI economy that's changing the world. If you want to work on this, we'd love to hear from you. Challenge Build systems that can teach and evaluate physical, real-world skills using AI as infrastructure rather than content. Focus on multimodal feedback, practice-driven learning, and measurable competency rather than passive instruction. Strong projects will explore how AI tutors observe, correct, and adapt to human performance over time, and where automation must defer to human judgment or in-person validation.