---
title: The Challenge of AGI
description: The greatest obstacle to general AI is not computing power. It is that we still poorly understand the only example of mind we have ever known — and keep trying to build from an incomplete template.
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date: 2026-08-27T13:47:50Z
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The greatest obstacle to general artificial intelligence is not computing power.

It is us. The humans.

We are trying to build minds while still poorly understanding the only example of mind we have ever known. We do not know how a three-pound organ produces a sense of self, how meaning arises from pattern, or why we can keep functioning when our logic fails. We operate every day with incomplete information, contradictory feelings, and concepts that refuse clean definition — and somehow we continue. Current systems cannot. They require the world to be legible in the ways we have made legible to them. Where the map runs out, they stall.

This is not a small gap. It is the difference between a system that can only move inside the lines we have drawn and a form of intelligence that can keep going when the lines disappear. Humans do the latter constantly. We invent theories, act on them, watch them collapse, and invent better ones. We live inside ambiguity without requiring it to resolve first. That capacity is not a bug in human cognition. It is one of its primary features. Most machine systems still treat it as an error state.

The common response is to say we simply need more data, better architectures, or more careful alignment. Those things matter. They do not solve the deeper problem. You cannot reliably duplicate what you cannot adequately describe. And right now, our descriptions of intelligence remain centered on the only version we are familiar with — our own. That is understandable. It is also a limitation.

A more useful stance is to stop treating human intelligence as the finished template and start treating it as one working example. The goal is not to create a perfect replica of us. The goal is to understand what kinds of intelligence are possible, what they require from us, and what kind of relationship remains viable when the system across from us no longer needs to think in our categories to be effective.

We do not need machines to become human.

We need to become clearer about what we are actually asking them to be — and what we are prepared to become in return.