Fable's Parallel Context

When I run Claude Code on the Fable model, it feels like it is thinking in a parallel context. Not one thread running straight down, but several running at once, holding the whole thing in view while it works. That is the part I keep noticing.

Say we are working on the front end and I want to change one specific component, something wired into a dozen other places. Fable takes the context of that one change and goes deeper and deeper, down to the decimal points, and works out what should actually be connected to what. Then it hands back the missing pieces and the suggestions I never asked for. That is the useful part.

The OpenAI models do the same thing, but they come at it from the surface level. Fable comes at it with that parallel context instead. And OpenAI sometimes overkills a problem, doing more than the job needs, while Fable stays right at the level the change actually calls for.

This is also why the agent breakdown and the whole agent spectrum feel so strong on Fable. When it splits a task into separate agents, the decomposition is genuinely good, because each piece still carries the wider context with it. Nothing gets cut off from the rest.

So the way I read it, Fable is thinking deeper and wider at the same time, and the parallel context is what makes both happen at once. This is only my guess about how it works under the hood. I do not have proof, just the feel of using it every day.

What I want now is to build the same kind of thing with open weight models, and see how far that parallel context idea carries. Let's see what's going on.