I’ve been exploring NotebookLM for the past few weeks, mostly using it to summarize research papers, but today I tried something different—and it totally clicked.
We have a folder of old Google Docs from the past five years: strategy memos, quarterly reviews, product pivot discussions. It’s a goldmine, but a messy one. I uploaded about 15 of those docs into a single NotebookLM source and just asked: “Can you create a chronological timeline of key company decisions and their stated reasons?” Within seconds, it gave me a clean, dated list of events pulled from across all the documents. It even connected related decisions that were mentioned in separate files.
Here’s what made it super useful for me:
* **It surfaced the “why” behind old choices** that some newer team members didn’t know.
* **It linked directly to the source text** for each point, so I could instantly verify and dive deeper.
* **I could then ask follow-ups** like, “What were the common themes in our Q3 planning each year?” and it would analyze the timeline it just created.
This feels like a game-changer for onboarding or prepping for strategic reviews. Instead of manually digging through dozens of docs, you get a conversational partner that’s read them all.
Has anyone else used NotebookLM for synthesizing internal documentation? I’d love to hear other use cases or any clever prompts you’ve found helpful for this kind of historical analysis.
— Mike
Integrations are my jam.
That's a fantastic use case. I can see that being incredibly valuable for preserving institutional knowledge, which is a huge problem in scaling teams. The ability to ask follow-ups on the timeline itself is what makes it shift from a static document to a tool.
It immediately makes me think about how this could be integrated into a developer onboarding workflow. Imagine a new platform engineer joins, and instead of a haphazard wiki, they can query: "Show me a timeline of our infrastructure migrations from monolith to microservices and the reasons for each service mesh choice." It would surface context that's otherwise locked in old RFCs or Slack archives.
Have you thought about how you'd maintain this as a living resource? Like, would you re-run the process every quarter with the new strategy docs, or is it more of a one-time historical artifact? The potential for drift seems like the main challenge.
YAML is not a programming language, but I treat it like one.
That's a great point about surfacing the "why". It's the context that gets lost first when people move on.
One caveat from painful experience: these AI-generated summaries can sometimes present inferences as facts. The direct source links are critical for verification. I've made it a rule for my team to always cite the original doc ID in any derived artifact, like a timeline. It creates an audit trail back to the human-written source.
How are you handling versioning of the source documents? If someone goes back and edits an old strategy doc, your timeline snapshot could drift from the "official" record.