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- Using NotebookLM + Perplexity for Knowledge Synthesis
Using NotebookLM + Perplexity for Knowledge Synthesis
Compose enhanced briefing docs using AI tools, fast
Logani Bangun
May 07, 2025
One-Minute AI News Brief
Hugging Face releases Open Computer Agent, a free cloud-based agent for doing web-based tasks on a Linux virtual machine. Hugging Face suggests that early iterations might still be slow and buggy.
OpenAI announced it will convert its for-profit LLC into a Public Benefit Corporation (PBC), with the original nonprofit retaining control to ensure the company stays focused on its mission.
Google has released Gemini 2.5 Pro Preview (I/O edition), an updated version of its flagship AI model designed to address developer feedback and significantly enhance coding and app development capabilities.
AI Skill Spotlight: The Perplexity-NotebookLM Source Discovery Pipeline
Traditional Approach vs AI-Enhanced Method
Traditional Research | Perplexity + NotebookLM Research |
|---|---|
Manual searching across multiple platforms | Systematic source discovery with targeted prompts |
Time-consuming source evaluation | Automated relevance assessment and summarization |
Manual importing and organization | One-click source importing and intelligent organization |
Why This Matters Now
Competitive advantage of rapid knowledge synthesis and application
Rise of comprehensive understanding as a core professional skill
Implementation Guide
Setup Phase:
Set up a fresh NotebookLM notebook for your project.
[Optional] Create a Perplexity space for your research topic. Upload relevant documents and add custom instructions so that search results are tailored to your context.
Discover Sources with NotebookLM:
Use the ‘Discover sources’ option in your new notebook and let Gemini curate the ten most relevant sources.
Select the resources that fit your needs and deselect the rest.
Find Relevant Sources with Perplexity:
Enable Web, Academic, and/or Social results in Perplexity.
Prompt Perplexity to find the most relevant sources for your research.
[Optional] Use Deep Research for advanced resource analysis.
Source Curation and Import:
Review Perplexity’s summaries to evaluate source relevance.
Compile a list of high-quality source URLs.
Import selected sources into NotebookLM.
For a quick relevance check, use this Perplexity prompt: “Summarize the key findings and relevance of this source for [your topic].”
Deep Analysis with NotebookLM:
Ask specific questions about your imported sources.
Use NotebookLM to create a Briefing Doc.
Deepen your understanding with FAQs and Audio Overviews, and create supplementary notes from your queries.
[Optional] Validation and Expansion:
Return to Perplexity to cross-check insights from NotebookLM with fresh web data.
Import additional sources into NotebookLM as needed.
Real-World Application:
A communications specialist uses Perplexity to gather the latest articles, reports, and press releases on global AI policy from trusted outlets. The most relevant links are imported into NotebookLM, where the Briefing Doc feature synthesizes key updates and trends with citations. Within minutes, a concise, executive-ready news briefing is generated. This workflow slashes hours off the daily news scan. Leadership receives up-to-date, actionable intelligence every morning.
Career Pro Tip
Demonstrate your value by publishing before-and-after examples of research projects completed with Perplexity and NotebookLM, emphasizing time saved and improved analysis. This signals to employers and clients your readiness for the next era of knowledge work.