Unlike human-driven growth, which is limited by population and waking hours, AI agents can operate, replicate, and call each other endlessly. This creates a potentially infinite demand for compute infrastructure, far exceeding previous models and leading to massive, unpredictable strains on providers.

Unlike traditional software, OpenAI's growth is limited by a zero-sum resource: GPUs. This physical constraint creates a constant, painful trade-off between serving existing users, launching new features, and funding research, making GPU allocation a central strategic challenge.

Greg Brockman states that in AI, 'too much opportunity' is the main problem, as most ideas work. OpenAI's strategic decisions, like focusing on the GPT reasoning model over video generation, are primarily driven by an extreme scarcity of compute. They cannot fund all promising avenues simultaneously.

The focus in AI has evolved from rapid software capability gains to the physical constraints of its adoption. The demand for compute power is expected to significantly outstrip supply, making infrastructure—not algorithms—the defining bottleneck for future growth.

The transition to agentic AI creates an exponential, non-speculative demand for compute that far exceeds supply. This justifies massive CapEx investments by hyperscalers, indicating a rational response to real demand rather than a speculative bubble.

Instead of managing compute as a scarce resource, Sam Altman's primary focus has become expanding the total supply. His goal is to create compute abundance, moving from a mindset of internal trade-offs to one where the main challenge is finding new ways to use more power.

The AI industry's exponential growth in consuming compute, electricity, and talent is unsustainable. By 2032, it will have absorbed most available slack from other industries. Further progress will require potentially un-fundable trillion-dollar training runs, creating a critical period for AGI development.

Instead of viewing compute as a cost center, OpenAI treats it as a revenue generator, analogous to hiring salespeople. The core belief is that demand for AI capabilities is so vast that they can never build compute fast enough to satisfy it, justifying massive, forward-looking infrastructure investments.

A theory suggests Sam Altman's massive, multi-trillion dollar spending commitments are a strategic play to incentivize a massive overbuild of AI infrastructure. By driving supply far beyond current demand, OpenAI could create a 'glut,' crashing the price of compute and securing a long-term strategic advantage as the primary consumer.