Everybody does this. You find an AI tool that’s genuinely great at something, then slowly pile on more expectations until it can’t possibly deliver.
NotebookLM is one of the best examples. A developer on r/PromptEngineering recently broke down why, and the core insight is sharp: understanding something once is not the same as absorbing it, connecting it to older ideas, or turning it into something useful six months later.
NotebookLM answers one question well: “what do these sources say?” It’s not built to answer: “how does this fit into everything I’ve ever learned?” Those are completely different jobs. One is retrieval from a defined document set. The other is synthesis across years of reading, thinking, and experience. Expecting one tool to handle both is what makes the whole system feel broken.
Old way: Load everything into one app. Expect it to handle capture, synthesis, long-term memory, audio learning, and reasoning all at once. Wonder why it feels chaotic. End up with 47 uploaded sources, three half-finished audio overviews, and no actual memory of what you learned last month.
New way: Give each tool exactly one job.
Here’s the stack:
📥 Readwise (capture layer) – Kindle highlights, articles, newsletters, tweets. Its only job: save things before they disappear into random tabs and screenshots. No synthesis here. Just intake that feeds the rest of the system. The key is letting it run automatically in the background so capture doesn’t become a manual chore you skip when things get busy.
🗃️ Obsidian (knowledge base layer) – One note per idea, written in your own words, linked to related notes. The backlinks are the whole point. When a note from a psychology book connects to a business podcast from two years ago, you stop storing information and start building a thinking system. A practical rule: every note should have at least one link to an existing note before you close it. If you can’t find a connection, the idea might not be ready yet. And simple rule: if you’re spending more time designing folders than thinking, you’re procrastinating.
🔬 NotebookLM (research layer) – This is where it belongs. Source-grounded Q&A on a defined document set. Finding contradictions across papers. Getting oriented fast in a new topic. Good concrete example: drop five research papers into a notebook and ask it to surface where the authors disagree. That kind of structured comparison is genuinely hard to do manually and NotebookLM handles it well. Strong when the question is specific to a defined source set. Not a replacement for long-term memory.
🎧 BeFreed (absorption layer) – The one most people skip. Learning doesn’t only happen at a desk. BeFreed converts saved materials into audio with adjustable depth and style. This is how you actually work through your backlog instead of just adding to it forever. Commute, gym, evening walk. Materials that would sit unread for months actually get processed. The depth setting matters: shallow mode for quick orientation on a new topic, deeper mode when you need to actually retain something.
Claude (thinking + writing layer) – Not for memory or document retrieval. For working with ideas. Challenging arguments, finding hidden assumptions, turning messy notes into structured outlines. The prompt that actually works: “here are my notes, help me find the core argument, weak points, and how this connects to [topic].” Another use: paste a rough draft written from your Obsidian notes and ask it to identify where the logic jumps. You’ll find gaps you didn’t know were there. A thinking partner, not a filing cabinet.
OpenClaw (action layer) – Still experimental, but the concept is solid. An agent layer that gives the whole system hands. Message it from WhatsApp and the workflow runs automatically across your tools. The other layers hold and process knowledge. This one helps you act on it. The value isn’t any single automation. It’s that the friction between having an idea and doing something with it drops significantly.
The real lesson here isn’t about any specific app. It’s about job design.
When every tool is responsible for everything, you get confusion and inconsistency. When every tool has one clearly defined role, you stop blaming the tools and start seeing where information actually flows. That’s when a system becomes useful instead of just elaborate.
Once every tool has one clearly defined role, the whole system gets less chaotic. Not because the tools got better. Because you stopped asking them to do things they were never built for.
What’s your stack? Especially curious if anyone has a better answer for the absorption layer.
Frequently Asked Questions
Q: Can you ask NotebookLM questions about your documents?
Yes, you upload sources and ask follow-up questions grounded in those documents. But NotebookLM excels at one-time understanding, not long-term retention or connection. That’s why this stack separates concerns: use NotebookLM for fast research, then shift key insights to Obsidian where backlinks help you connect ideas over time.
Q: How do you keep notes from becoming “saved but never touched”?
Define repeatable workflows (extract key points → outline → task list → schedule) and run them consistently. One commenter also mentioned automating continuous summaries, tools like Podlog turn GitHub commits into podcast episodes, so information reaches you passively instead of sitting in a growing backlog.
Q: Why does Obsidian’s backlink system matter if you’re using NotebookLM?
Understanding something once isn’t the same as absorbing and using it. Backlinks let you connect a psychology note to a business insight from months ago to a journal entry, turning notes into a thinking system instead of static storage. That’s when knowledge becomes actionable.
Q: What tools connect Obsidian to your action layer (tasks, automation, etc.)?
Commenters mention MCP, scripts, and shortcuts as connectors. The idea is automation, moving Obsidian insights into real workflows without manual effort. Resources like aiosnow.com offer GTD templates to formalize this bridge between thinking and doing.
How I built a full knowledge system around NotebookLM instead of forcing it to do everything
by u/PuzzleheadedBeat797 in PromptEngineering