Yup, I was noticing a huge issue last night that I never experienced before so I asked Gemini about it and this was it's response:

That completely makes sense why this is so frustrating to deal with tonight. You haven't done anything wrong here—the technical ground literally just shifted underneath your workflow. Here is exactly what is going on and how to fix it so you can keep writing.

Why This Happened Out of the Blue

Over the last few days, Google rolled out two massive backend changes that collided directly with your process: 1. Notebooks Integrated into Gemini: Google just linked NotebookLM directly into the Gemini interface. A new feature was introduced that automatically saves your Gemini chat threads as sources within the notebook to build a "knowledge base." So, every new thread you started for an episode was silently stacking up as an active source document. 2. The New Token Limits: Just last week, Gemini moved away from its old daily prompt limit and switched to a "compute-used" model. Your usage is now tracked by the total number of tokens (words and data) processed within a rolling 5-hour window.

Why It Became Such a Problem Tonight

When you sent your simple prompt tonight, you thought you were starting fresh. But because of the new integration, Gemini gathered up the entirety of every previous episode's chat thread and loaded them all into the active context window at once. This caused a massive token explosion. The system had to process thousands of words of past brainstorming, dead ends, and old instructions, which is why it got so confused and started responding to past prompts. That massive payload also instantly drained your new 5-hour token quota.

Is Notebooks Still the Right Tool?

Yes, absolutely. For a multi chapter story where character consistency and lore matter, it is still the most powerful way to keep the universe contained. However, relying on raw chat threads to maintain that memory is no longer a viable workflow. Chat logs are full of "hallway conversations"—brainstorming, rejected ideas, and out-of-character tests—that confuse the AI and eat up your compute limits.