Why the race to AGI is BS - with Ian P. Cook, PhD
Ian P. Cook delivers a scathing critique of the AI industry's AGI narrative, arguing that companies like OpenAI are peddling marketing BS to raise investor dollars without clear definitions of what AGI actually means. His contrarian take cuts through the hype to examine AI's real impact on coding workflows, the US-China AI arms race, and why current AI systems fundamentally lack the taste and judgment that comes with human experience.
Key takeaways
- •AGI claims are primarily fundraising rhetoric designed to attract investor dollars rather than meaningful technical roadmaps.
- •Startups that insist on handwriting every line of code instead of leveraging AI tools will lose competitive advantage.
- •AI excels at junior-level coding tasks but struggles with senior development work because it lacks the 'taste' that comes from experience.
- •The US must massively scale data center infrastructure to maintain AI superiority over China as a national security imperative.
- •Current AI systems can generate code but cannot make the nuanced judgment calls that define experienced developers.
The essay
The most successful fundraising pitch in Silicon Valley history might also be the most meaningless. Ian P. Cook argues that Artificial General Intelligence , the holy grail every AI company claims to be chasing , is nothing more than "total BS" designed to extract money from investors who don't know better.
Cook, a tech founder and PhD, makes the case that companies like OpenAI and Anthropic are peddling undefined promises to fuel a speculative bubble. "You can say something and not care about whether it's true or false. That's literally the definition of the BS," Cook explains. "And my view is OpenAI, even Anthropic, all these other companies who are talking about AGI, don't have a definition for it. They just say it because their investors want to hear it. It's a great way to drum up money."
This matters because the AGI narrative isn't just moving money around venture capital firms. It's reshaping entire industries and national security strategies based on promises that may be fundamentally hollow.
The Real AI Revolution Is Already Here
While executives chase phantom AGI metrics, Cook argues the actual transformation is happening in plain sight among developers. Current AI tools have already fundamentally changed how code gets written, but not in the way most people expect. The impact follows a clear hierarchy: AI demolishes junior-level work while leaving senior developers largely untouched.
The reason cuts to the heart of what makes human expertise valuable. "I think one of the reasons that AI has had such an impact on junior level coding instead of the higher level coding is because what we get with experience and repetition is taste. And AI has no taste," Cook observes. This "taste" , the accumulated judgment about what works, what doesn't, and why , represents the irreducible human element that current AI cannot replicate.
For startups and tech companies, this creates an immediate strategic choice. Teams that resist AI tools in favor of "bespoke" hand-written code are making a catastrophic mistake. Cook is unambiguous: "If people are thinking, well, what I really need to do is be bespoke and be specific and just focus on the code and it's better when I handwrite every line, they are missing the opportunity and they're gonna be outpaced very, very quickly." The companies that win will be those that augment human taste with AI's computational power, not those that treat the two as competing forces.
The Geopolitical Stakes Are Real, Even If AGI Isn't
The disconnect between AI marketing and AI reality becomes dangerous when it shapes national policy. Cook acknowledges that despite the definitional problems with AGI, the competition with China over AI capabilities represents a genuine national security priority. "AI is a national security issue. Having AI that, by some measure, beats China is something that is imperative to the future of safety of The United States," he argues.
But winning this race requires massive infrastructure investments that dwarf current commitments. Cook envisions a future where "we need to build data centers the size of Manhattan, maybe the size of Rhode Island. Maybe we need to pave all of Nevada with" computing infrastructure. The scale suggests that even if AGI remains undefined, the resources required to maintain AI leadership are very real and very expensive.
This creates a policy paradox: the United States needs to invest heavily in AI capabilities to maintain strategic advantage, but the private sector driving this investment is motivated by potentially meaningless promises about AGI. The national security imperative becomes entangled with venture capital theater.
What Actually Changes
For anyone building or investing in technology, Cook's analysis suggests three immediate implications. First, ignore AGI timelines and focus on current AI capabilities. The tools available today already create competitive advantages for teams that use them effectively. Second, the value lies in combining AI automation with human judgment, not in replacing one with the other. Third, the infrastructure buildout required for AI leadership will create massive opportunities in data centers, energy, and computing hardware regardless of whether AGI ever materializes.
The companies and investors who recognize that the AI revolution is happening now , not in some undefined AGI future , will capture the actual value being created. Those still chasing the marketing mirage will find themselves funding science fiction instead of building competitive advantages.
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