What it means here Interleaved thinking describes how a model reasons in the middle of doing rather than before it: the model pauses to think between steps of a multi-step task — between tool calls, searches, or file edits — instead of front-loading all of its reasoning into a single block at the start. Why the channel discusses it In the captured material, interleaved thinking sits alongside the broader question of how much a model should reason per task. The team's vibe-check testing pays close attention to thinking modes because they affect reliability: on Opus 4.6, for example, the suspected source of its confabulations was that when the model decides not to think much, it sometimes goes off the rails. That's the same tradeoff interleaved thinking raises — reasoning distributed across a task can help the model course-correct mid-stream, but it can also leave room for under-thinking individual steps. What to take away - Interleaved thinking = reasoning woven between the steps of a task, not all before it.- It's one of the levers to explore when you tune reasoning effort per task during a vibe check.- More distributed thinking is not automatically better — the team's evidence shows models that under-think can confabulate, so testing how a model uses its thinking matters as much as whether it has the option.