You won't be building courses end-to-end so much as making them right — evaluating curricula for technical accuracy from a working developer's perspective, filling content gaps, surfacing the real-world context that turns generic AI material into training engineers trust, and implementing better processes to speed up the design and development phases. Fill Content Gaps: When a missing or thin area is identified, develop the technical content to close it — written guides, video tutorials, hands-on labs, technical demos, code examples, and reference material — grounded in real engineering use and delivered for both self-paced and instructor-led formats.