Code AGI is Functional AGI (And It's Here)
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The AI Daily Brief: Artificial Intelligence News and Analysis
24 min
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4 chapters
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Today on the AI Daily Brief, why Code AGI is functional AGI and why functional AGI is here. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Zencoder, Robots and Pencils, Section, and Superintelligent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief. And if you are interested in sponsoring the show, send us a note at sponsors at ai-dailybrief.ai. So we are back now with another long read slash big think episode. And this week, we're getting into a topic that I have been kind of obsessing about for the last several weeks.
It feels to me quite clear that something dramatic has shifted. Obviously, I don't mean some new model that changes everything, but more, it feels as though we've digested what the latest round of models is actually capable of. We've had enough time with them for them to start to shift our behaviors. And the implication of all of that is, fundamentally speaking, some different new era in the story of AI and more broadly in the story of work. It is a shift which I am still trying to figure out how to put words around, but one that I am convinced has profound implications for how companies do what they do. To some extent, the shift is starting to come home to roost in a concerted conversation around whether we are finally at AGI.
I will argue that we are with some nuance. But what I'm going to do first is read some excerpts from a recent piece by Sequoia's Pat Grady called 2026, This is AGI, follow it up with a more skeptical piece by Every's Dan Shipper called Toward a Definition of AGI, and then I'm going to add my own thoughts, steelmanning both perspectives and trying to end with where I think is the most useful place to be. Let's start with Pat's piece. It's actually by Pat Grady and Sonya Huang, and begins, Years ago, some leading researchers told us that their objective was AGI. Eager to hear a coherent definition, we naively asked, How do you define AGI? They paused, looked at each other tentatively, and then offered up what's become something of a mantra in the field of AI.
Well, we each kind of have our own definitions, but we'll know it when we see it. The vignette typifies our quest for a concrete definition of AGI. It has proven elusive. While the definition is elusive, the reality is not. AGI is here now. Coding agents are the first example. There are more on the way. Long horizon agents are functionally AGI, and 2026 will be their year. Now in the next section, Pat and Sonja make sure to qualify that they do not have any sort of scientific authority to propose this definition. And yet, with that said, they offer what they call a functional definition of AGI. AGI, they write, is the ability to figure things out. That's it. A human who can figure things out has some baseline knowledge, the ability to reason over that knowledge, and the ability to iterate their way to the answer.
An AI that can figure things out has some baseline knowledge, pre-training, the ability to reason over that knowledge, inference time compute, and the ability to iterate its way to the answer, long horizon agents. The first ingredient, knowledge and pre-training, is what fueled the original ChatGPT moment in 2022. The second, reasoning and inference time compute, came with the release of O1 in late 2024. The third, iteration and long horizon agents, came in the last few weeks with cloud code and other coding agents crossing a capability threshold. Generally intelligent people can work autonomously for hours at a time, making and fixing their mistakes and figuring out what to do next without being told.
Generally intelligent agents can do the same thing. This is new.
How have recent AI models changed our understanding of AGI?
So what's an example of this new capability that they're talking about? They provide an example of a founder telling his agent that he needs a developer relations lead. He gives a set of qualifications, including the fact that this person needs to enjoy being on Twitter.
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