Every so often, a term bursts out of the labs and into the mainstream, getting twisted and diluted along the way. Right now, that term is “AGI.” If you search for it, you’re just as likely to find articles about your adjusted gross income for the IRS as you are to find discussions about the future of intelligence. It’s a perfect, almost poetic, confusion. We’re all trying to calculate our place in the world, whether it’s on a tax return or in the face of a technological dawn.
The debate raging in Silicon Valley right now feels just as muddled. Is the quest for Artificial General Intelligence—a true thinking machine—a fool’s errand? Or is it the only prize that matters? We hear from pragmatists like Replit CEO Amjad Masad, who argues that The economy doesn't need true AGI, says Replit CEO. Then we hear from visionaries like OpenAI’s Sam Altman, who speaks of a true AGI that will “go whooshing by” within five years, reshaping society before we’re even ready.
Listening to the back-and-forth, it’s easy to feel a sense of whiplash. Are we on the verge of a breakthrough or stuck in a trap of diminishing returns? I think the answer is both. And I believe this tension isn’t a sign of failure; it’s the sound of the engine turning over.
The Power of “Good Enough”
Let’s start with the pragmatists, because what they’re building is already changing your world. Amjad Masad’s concept of “functional AGI” is incredibly powerful. He’s talking about systems that don't need consciousness or human-like reasoning; they just need to learn from data and complete complex, verifiable tasks. In simpler terms, we’re building the most capable, versatile, and scalable workforce in human history.
Masad worries the industry is caught in a “local maximum trap,” chasing profitable tweaks to current models instead of swinging for the fences. I see it differently. This isn't a trap; it's a basecamp. Think of the Industrial Revolution. Before we could even dream of building skyscrapers and microchips, we first had to master the steam engine. The steam engine was a messy, inefficient, and profoundly “functional” piece of technology. It wasn’t elegant, but it laid the tracks, powered the factories, and built the economic and logistical foundation for everything that came after.
That’s where we are now. The “functional AGI” that can automate vast sectors of the economy is our steam engine. When I first saw the latest models autonomously writing and debugging complex code, I honestly just sat back in my chair, speechless. This is the kind of breakthrough that reminds me why I got into this field in the first place. It’s not the final destination, but it’s the vehicle that gets us there. So the question isn't whether this is the "real" AGI. The more thrilling question is: If we can automate the known, what new, unknown territories does that free the human mind to explore?
Building a New Kind of Mind
This brings us to the grand vision—the quest for a true, general intelligence. This is the moonshot. Skeptics like Gary Marcus and Yann LeCun correctly point out that simply scaling up today’s large language models—making them bigger with more data—probably won’t get us there. They argue that we’re missing a fundamental spark, the leap from pattern recognition to genuine understanding.
And you know what? They’re right. But that shouldn't be a source of pessimism. It should be a source of absolute, unadulterated excitement! It means there is still a profound scientific mystery at the heart of intelligence, one that we get to solve. The current models are like a perfect parrot; they can recite Shakespeare flawlessly, but they don’t feel the tragedy of Hamlet. The next step isn’t just about knowing more words; it’s about understanding the story. What does it take to build a system that doesn't just process information, but synthesizes it into wisdom? How do we create not just an answer machine, but a question machine?
This is where Sam Altman’s perspective becomes so fascinating. Altman predicts AGI will reshape society before we’re ready — and that’s okay? Scary moments, sudden shifts, and late-stage adaptation await. He predicts it will whoosh by and we’ll learn as we go, because people and societies are just so much more adaptable than we give ourselves credit for. The speed of this is just staggering—it means the gap between today and tomorrow is closing faster than we can even comprehend, and we’re essentially building the airplane while we’re already in mid-air.
This is, of course, where our responsibility comes in. Altman acknowledges that “bad stuff” will happen. This isn’t a utopian fantasy. With any technology this powerful—from the printing press to nuclear fission—comes immense risk. Building the ethical guardrails, the societal shock absorbers, isn’t a secondary task for policymakers to figure out later. It is a core part of the engineering challenge, as fundamental as the algorithms themselves. We are not just building a tool; we are building a partner in our future.
This Is How Revolutions Begin
So, what is AGI in AI? It’s not one thing. It’s a spectrum, a journey. The functional, practical AI of today is not a detour from the path to true AGI; it is the path. Each incremental improvement, each new capability, is another paving stone laid on the road to a destination we can’t fully see yet.
The debate between the pragmatists and the visionaries isn't a conflict; it's a collaboration. One side is building the engine, piece by piece, making it stronger and more efficient every day. The other is looking at the horizon, drawing the map, and dreaming of where that engine could take us. Both are essential. This is how all great leaps in history have been made—with one foot planted firmly in the practical reality of the present, and the other stepping boldly into the possibility of the future. We are living through one of those moments right now. Don't let the noise distract you from the signal.