Experiment: Using NotebookLM as a cynical code reviewer (via custom prompts) I've been experimenting with using NotebookLM not just for summarization, but for "Red Teaming" my own automation workflows. I fed it a video demo of an n8n research agent I built and used Custom Instructions to force the Audio Overview hosts into a specific persona: "Jaded, cynical tech reviewers." My goal was to see if the model could pick up on specific node logic and architectural choices (like manual Server-Sent Events handling and JSON output forcing) from the video feed alone, rather than just summarizing the "gist" of the project. The Prompt I used: "Act as two jaded, cynical tech reviewers... Focus ONLY on the single most impressive feature... Notice the 'Server-Sent Events' (SSE) configuration... Admit that the 4-Layer Architecture is legitimate engineering." The Result: The model successfully identified the specific timeout handling logic I implemented in n8n, which a standard summarization usually misses. It seems like a viable way to get a "synthetic second opinion" on architectural flows if you prompt for hostility rather than agreement. Video of the output (4 min): https://youtu.be/oof9JB3OFO4 Has anyone else had success forcing specific technical personas in NotebookLM? |