Swap the model. The project stays coherent

The project hasn’t noticed this yet but…
I’ve been switching AI models mid-project for months.

Claude. Codex. Whatever Cursor decides to load today.
Different weights. Different training. Different personality out of the box.

And yet, the project stays coherent, stays itself, and sounds like it’s been on the job for months.

Because it has.

Not the model.
The project.

Here’s what I’ve realised: most people think they’re working with Claude. They’re not.

They’re working with their project - through Claude.
The model is just the mouth.
The index is the soul.

Swap the mouth. The soul stays intact. Or at least, that should be the case.

This breaks something the AI industry has quietly been betting on: model loyalty. The assumption that you’ll stay with a platform because your work lives there, and because switching means starting over.

SR-SI as a methodology makes that bet worthless.

The identity of your project doesn’t live in the model.
It lives in the index: your decisions, your architecture, your accumulated scar tissue from every bad call and every good pivot.

And because it lives in the index, it means all of it is portable.
And all of it is model-agnostic.

A new model reads the index, steps into the role, and gets up to speed in seconds because the project already knows who it is.

Think of it like this: the model is a contractor. The index is the institutional memory no contractor can take with them when they leave.

You don’t need model loyalty when your project has its own soul.

If you want the deeper mechanics of context continuity and self-orienting workflows, I’ve written a full paper on the broader “AI Memory Prosthesis” idea and how to prevent coherence drift across long-running projects.