How should developers decompose tasks when building with system one models?

Break everything down into its smallest semantic unit. Never ask one big question when you can ask ten small ones. For each piece of state you want to reason about, ask a separate, explicit, very structured question. This way every single call is evaluable, every failure is diagnosable, and every fix is durable because it lives in the structure of your code, not hidden in some context-rotting system prompt. If you find a situation where the model got something wrong, you add a new question to handle that case. The bug is now solved forever. It is like machine learning without the machine learning. And yes, it is more calls, but with a model like Jev the cost is not a barrier and the reliability gain is enormous.