Anthropic recently published fascinating research describing evidence of a “global workspace” inside Claude—an internal space where information appears to come together before language is produced.

Like many AI researchers, they’re trying to answer a difficult question:

What did this enormous neural network teach itself?

At Punkworx, we’ve accidentally been approaching the same mountain from the opposite side.

We aren’t trying to peer inside a trillion-parameter model.

We’re asking a different question:

If you started with the observable characteristics of human thought, could you deliberately engineer a cognitive operating system that remains understandable by its owner?

Instead of discovering hidden representations, we’re asking:

• What is a memory?

• What makes one memory relevant?

• How do experiences become knowledge?

• How does rumination differ from reflection?

• What separates conversation from reasoning?

• How should an AI explain why it surfaced a memory?

One path begins with a giant neural network and asks, “What emerged?”

The other begins with cognition itself and asks, “What architecture would reproduce these behaviors transparently?”

Perhaps both paths eventually meet in the middle.

If they do…

…that would be interesting.