Computer science alone will not build the next generation of AI-capable engineers. The future belongs to mechanical, electrical, and civil engineers who understand both their domain and AI fundamentals. Universities are catching on, launching hybrid programs that combine traditional engineering excellence with practical machine learning skills.
Most companies build AI skills matrices backwards - focusing on tool expertise that expires in months. The real framework tracks learning velocity and adaptation speed. What actually matters is how fast people adapt to new tools, not what they know today.
Most AI training fails because it starts with theory. The curriculum that works starts with outputs, then inputs, then process. Reverse everything you think you know about teaching AI to understand what actually sticks with learners and drives real behavioral change.