Pineau emphasizes that meaningful AI advancement requires patience, as breakthroughs often emerge after years of iterative work, contrary to the perception of overnight success. She highlights the limitations of reinforcement learning for general intelligence and stresses the growing importance of capital efficiency in enterprise AI adoption. Security risks with autonomous agents, especially around impersonation and deployment safety, remain underappreciated. The rising cost and complexity of data—particularly synthetic data—pose new challenges, including model degradation without careful diversity management. Pineau advocates for balanced investment in talent, infrastructure, and algorithmic innovation over sheer scale. She sees transformative potential in healthcare and science but warns of societal risks, particularly in digital well-being and child safety. Ultimately, she champions open collaboration, smaller efficient models, and human-AI co-development as keys to responsible and sustainable progress.