Nathaniel Whittemore

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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.