AI safety organizations struggle to hire despite funding because their bar is exceptionally high. They need candidates who can quickly become research leads or managers, not just possess technical skills. This creates a bottleneck where many interested applicants with moderate experience can't make the cut.

The primary constraint to solving major AI safety challenges is the lack of experienced founders and leaders who can build and scale organizations. Ideas are plentiful, and funding follows great talent, making the 'founder bottleneck' the key problem to solve.

Ajeya Cotra suggests a radical shift for philanthropies like Open Philanthropy. Their best strategic play during the critical AI 'crunch time' may be to deploy billions of dollars not on human salaries, but on buying massive amounts of compute to direct AI labor towards solving safety and defense challenges.

Unlike specialized non-profits, Far.AI covers the entire AI safety value chain from research to policy. This structure is designed to prevent promising safety ideas from being "dropped" between the research and deployment phases, a common failure point where specialized organizations struggle to hand off work.

Unlike prior tech waves where founders aimed to build companies, many top AI founders are singularly focused on achieving AGI. This unified "North Star" creates a unique tension between long-term research and near-term product goals, leading to unconventional founder and company dynamics.

It seems counterintuitive to start new organizations if AGI is near. However, the alternative is inaction. The second-best time to start an AI safety company is today, as these entities are needed to build the solutions we'll rely on if we manage to slow down progress.

Anthropic's resource allocation is guided by one principle: expecting rapid, transformative AI progress. This leads them to concentrate bets on areas with the highest leverage in such a future: software engineering to accelerate their own development, and AI safety, which becomes paramount as models become more powerful and autonomous.

Even if the market would eventually build decision-making tools, their impact is time-sensitive. Waiting for commercial rollout might mean they arrive after AGI, too late to help navigate the riskiest period. Therefore, philanthropic or impact-driven acceleration, even by a few months, is highly valuable.

Sequoia's proclamation that AGI has arrived is a strategic move to energize founders. The firm argues that today's AI, particularly long-horizon agents, is already capable enough to solve major problems, urging entrepreneurs to stop waiting for a future breakthrough and start building now.