The path to Artificial General Intelligence (AGI), long the ultimate prize in the field of AI, may not culminate in the creation of a single, all-powerful model as many believe.
This is the viewpoint of Logan Kilpatrick, who leads product at Google AI Studio and has become a prominent voice for Google’s AI initiatives. In a landscape where the race to AGI is often measured by the parameter counts and benchmark scores of foundational models, Kilpatrick offers a nuanced, product-centric perspective. He suggests that the true “AGI moment” for the public will be less about the raw capability of a model and more about a masterfully crafted user experience that makes intelligence feel truly general and useful in our daily lives.
Kilpatrick hypothesizes that the breakthrough won’t be as clear-cut as a new model release that definitively crosses the AGI threshold. “I think AGI is going to end up being much more of a product experience,” he states. “My assumption right now is that someone’s going to release a model that ends up being really good, but it’s not going to be this thing where everyone agrees, ‘We’ve clearly built AGI.'”
Instead, he argues, the magic will happen at the product level. “I think someone’s going to weave together the right components at the product level with a model that’s really smart,” Kilpatrick explains. He believes that even incremental improvements in core model capabilities, such as in context understanding and reasoning, could be the key, provided they are integrated thoughtfully. “It could be that long context is 50% better and reasoning is 50% better, and then you somehow figure out how memory should work.”
He emphasizes that creating a functional memory is not just a modeling problem. “The memory piece is actually a completely different engineering, neuroscience, and human psychology problem of how you surface the right things at the right time,” he says. “I think someone’s going to build that experience, and the feeling will be that this thing is like AGI. Again, it’s really a product experience enabled by a model, but the model itself isn’t able to do all those things. It’s what happens when you take the model and you build everything around it in a really thoughtful way that people are going to say is the AGI moment.”
Kilpatrick’s perspective reframes the AGI race from a pure arms race of model scale to a more complex challenge of product innovation. This view aligns with a broader trend in the tech industry where the focus is shifting from demonstrating raw technical power to delivering tangible, intuitive, and valuable user applications — Google, Anthropic and Meta had created chatbots around the same time as OpenAI, but ChatGPT got the lead because its product was much superior than others. Kilpatrick’s argument suggests that the company that finally cracks the AGI code won’t just be the one with the most intelligent model, but the one that masterfully solves the human-computer interaction puzzle, making that intelligence feel less artificial and more genuinely helpful.