OpenAI's Greg Brockman: Why Human Attention Is the New BottleneckOpenAI's
In a Nutshell
OpenAI, led by co-founder Greg Brockman, thrives by aggressively scaling compute amid shortages, leveraging scaling laws and innovations like Transformers to push toward AGI, with models now 80% there—excelling at software engineering, overnight optimizations, and agentic coding that shifts 80% of work from humans. Human attention emerges as the new bottleneck, demanding robust primitives for security, governance, and EQ in agentic workflows, while organizations flatten into solopreneurs and small teams commanding vast AI agents. OpenAI prioritizes enterprise sales, consumer productivity via proactive AGI assistants, and frontier science breakthroughs in physics and biology, envisioning a future where coding evolves into natural, vision-driven oversight rather than typing drudgery.
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Greg Brockman was employee number four and first CTO at Stripe, which processes 1.6% of global GDP. OpenAI has almost a billion or more weekly active users. He is co-founder, president, and chief builder at OpenAI.
OpenAI's business: buy, rent, build compute, and resell at a margin. Scale as long as margin is positive because demand for intelligence is unlimited. Current AIs handle any problem. They do not have enough compute and are constantly hunting for more. Matt Garman says GPU compute availability in 2026 rounds to zero. When launching ChatGPT, Brockman told team to buy all compute; demand has outpaced supply ever since.
Scaling laws feel like a fundamental scientific truth, empirical like Newton's laws. Neural networks designed in the 1940s, now scaled with massive compute, continuously improving capabilities with no wall. Constant innovations: micro tweaks like data formatting, larger shifts like LSTM to Transformer (not yet surpassed from 2018 paper). OpenAI leads in long-term research on architectures, algorithms, and paradigm shifts, with fruit on the horizon.
OpenAI has a formal definition of AGI, but intuitions vary. Models are 80% of the way there: smart, very capable. Smarter than Brockman at writing software with context. No one feels better at writing software than GPT-5.4, even writing kernels. Internal results show massive gains on low-level tasks with right setup.
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