Combining NotebookLM Research with Gemini Context

gemini 3.1 pro dropped and nobody's talking about the real play here... it's not the benchmarks or the reasoning scores but what happens when you pair it with NotebookLM here's how i use it for literally everything i work on: 1. open NotebookLM, run Deep Research on your topic 2. it pulls hundreds of sources from across the web automatically 3. review everything, cut the garbage, keep only what's good 4. now you have a curated knowledge base grounded in real sources this is where it gets interesting... > import that notebook directly into Gemini > build a Gem with your notebook as context > now every prompt you write is backed by YOUR research, YOUR sources this thing was built to process massive context... 1M tokens, entire codebases, hundreds of documents at once if you're prompting it with zero context you're wasting the most powerful part of the model notebooks are the knowledge layer and gemini is the reasoning engine stack them together and you have the best system to process large context files