Forget building a god-tier superintelligence. Replit CEO Amjad Masad said we don’t need that to change the economy and society — we just need “functional AGI.”
The CEO of the vibe coding startup said on an episode of the “a16z” podcast published Thursday that while Silicon Valley obsesses over true AGI, the practical version is already within reach, and it’s good enough to automate massive chunks of the economy.
“We can get to like functional AGI,” Masad said. He defines functional AGI as AI that doesn’t need human-like consciousness or reasoning, just systems capable of learning from real-world data and completing verifiable tasks on their own.
“We’ll target every sector economy and you can automate a big part of labour that way,” he said. “We’re on that track for sure.”
Masad said he’s not convinced that we’ll ever reach true AGI, the kind of artificial intelligence that can learn and adapt across knowledge fields like a human mind.
While true AGI could “propel us to the next level of human civilization,” Masad said he’s “bearish on true AGI breakthrough because what we built is so useful and economically valuable.”
Masad also said the industry might be stuck in a “local maximum trap,” which means AI companies are optimizing what already works instead of reinventing the field. By chasing small, profitable improvements to today’s large models, they could be missing the path to a true breakthrough.
“Maybe the general problem is actually not within our lifetimes,” Masad said, referring to solving the problem of general intelligence itself. “Who knows?”
Masad did not respond to a request for comment from Business Insider.
The AGI dream is losing its shine
Masad’s comments come amid renewed debate over whether AGI is even a meaningful goal.
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Major AI labs still consider AGI the ultimate prize. OpenAI, Google, Meta, and Microsoft have devoted their top researchers to the same goal.
However, some experts have questioned whether LLMs can ever evolve into true general intelligence.
“Nobody with intellectual integrity should still believe that pure scaling will get us to AGI,” Gary Marcus, an AI leader and best-selling author, wrote in a blog post in August. “Even some of the tech bros are waking up to the reality that ‘AGI in 2027’ was marketing, not reality.”
The release of OpenAI’s GPT-5 didn’t live up to the AGI hype, either.
“This is clearly a model that is generally intelligent, although I think in the way that most of us define AGI, we’re still missing something quite important, or many things quite important,” OpenAI CEO Sam Altman told reporters during a press call in August before the release of GPT-5.
Other industry veterans have echoed that caution. Meta’s chief AI scientist, Yann LeCun, said we may still be “decades” away from achieving AGI.
“Most interesting problems scale extremely badly,” LeCun said at the National University of Singapore in April. “You cannot just assume that more data and more compute means smarter AI.”
