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.

OpenAI initially experimented broadly with 'side quests' like a hyperscaler (e.g., Google), launching many initiatives. Facing intense competition and the need to scale compute, it's now consolidating its focus on the 'main quest' of core productivity for business and coding users, marking a significant strategic shift.

Brad Lightcap joined OpenAI because he saw the potential of scaling laws. The realization that bigger models predictably improve transformed the AI challenge from a conceptual puzzle into a matter of scaling compute, which became the company's core early conviction.

OpenAI shelved its Sora video platform not because of poor user reception, but as a strategic choice. Sora is built on a different technological foundation ("world models") than their core GPT models. The company is focusing all compute resources on the GPT "tech tree," viewing it as the most promising path to powerful AI.

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.

OpenAI is shuttering its popular Sora video products not due to failure, but to reallocate immense compute costs. Resources are being strategically redirected from the consumer-facing tool to "world models" that better mimic real-world physics, a crucial investment for the company's long-term robotics ambitions.

For entire countries or industries, aggregate compute power is the primary constraint on AI progress. However, for individual organizations, success hinges not on having the most capital for compute, but on the strategic wisdom to select the right research bets and build a culture that sustains them.

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.

OpenAI is likely closing its computationally expensive Sora video project to focus capital and compute resources on ventures with higher ROI. This is a classic business strategy to strengthen financials and the company narrative ahead of a public offering, not an admission of defeat in video AI.