Grinberg predicts AI will boost GDP growth above the historical 2% average, but businesses need time to adapt. He foresees a bifurcation in engineering, with a few 'load-bearing' individuals gaining immense leverage from AI tools. Executives must learn to allocate tokens like capital, focusing on output metrics rather than intermediate ones. He criticizes Kirkland's $500M AI build as outside its core competency and argues that open-source models can already replace 80-90% of frontier model work, with the remaining 'decision-making tokens' being the most critical. Grinberg believes the role of a great engineer is shifting from coding speed to owning end-to-end business outcomes, predicting a new 'general manager' role. He is not worried about long-term job displacement, arguing that short-term shocks are real but long-term fears are overblown, and that the primary bottleneck is human behavior change. He also changed his mind on AI concentration, now believing at least four frontier companies will emerge, which is a win for humanity.