“Make money, save money, change the world.” It’s a simple framework but in generative AI engineering, those outcomes are built through code, not strategy decks. In this session, Gregory Johnson breaks down what ROI looks like from the inside out: how model optimization, infrastructure efficiency, and scalable deployment translate into tangible business and social impact. Drawing from real production rollouts, he shows how teams are driving revenue through AI-powered features, cutting cost per inference, and embedding responsible design into high-impact systems. Key takeaways: → How engineering decisions directly map to the three pillars of ROI — performance (make money), efficiency (save money), and impact (change the world). → Techniques for improving throughput, latency, and cost without sacrificing quality. → Real examples of how optimized infrastructure and ethical design create measurable value.