Accelerate Any Topic Learning with AI: 6 Practical Workflows

1. Use Perplexity to quickly find the right resources and feed them into NotebookLM

This is the author’s preferred way to start learning a new topic. Instead of random Google searches, they open Perplexity and ask a specific query, e.g., “Recommend the best advanced resources for system design” or “Give me the top papers, blogs, and videos on reinforcement learning.” Perplexity returns a curated list of links, which the author copies into NotebookLM (the “Links” tab helps gather all URLs). They then ask NotebookLM to:

Explain the topic for a beginner

Plan a step‑by‑step learning path

Summarise core concepts in simple language

Generate a test to assess mastery

Produce a 3‑minute audio explanation

By selecting only the top 5‑10 links and organising them in NotebookLM, the author avoids aimless reading, saves hours, and keeps the learning process structured.

2. Turn YouTube videos into structured notes

The author searches YouTube for the target topic (e.g., “system design introduction”, “Transformer mechanics”, “sales psychology”) and selects 5‑7 popular, clear, and sufficiently long videos. They copy each video’s link into NotebookLM, which then:

Aggregates core points from all videos

Re‑explains the material for beginners

Highlights key concepts to remember

Creates a concise note or short podcast for later review

Generates test questions to verify understanding

This transforms scattered video content into a coherent learning unit, turning passive watching into active study.

3. Deep Research to compress extensive material

For in‑depth understanding, the author uses the “Deep Research” feature of large models (Perplexity, ChatGPT, Gemini). They craft detailed prompts such as:

Give me a data‑backed deep dive on vector databases, covering principles, use‑cases, pros/cons, and future trends in simple language.

The model returns a near‑research‑grade analysis, which the author copies together with related articles into NotebookLM. NotebookLM then helps to:

Build a learning roadmap from beginner to advanced

Simplify complex sections

Create analogies for easier comprehension

Produce a quick‑review cheat sheet

This prevents the loss of insight that often follows reading a long report once.

4. Guided Learning for step‑by‑step instruction

When a topic is too complex for a single summary, the author leverages Gemini’s “Guided Learning” or ChatGPT’s “Study and Learn” mode. They input a request such as:

I want to master system design from basics to advanced, teaching me step by step and testing me along the way.

The AI then adopts a layered teaching approach: it asks questions, breaks concepts into bite‑size explanations, provides examples, suggests next steps, and continuously tests the learner. This interactive style creates a feeling of having a personal tutor and reinforces memory.

5. Visualise the knowledge

After structuring the material, the author feeds the output into visual AI tools (via NotebookLM, ChatGPT, or Gemini) to generate infographics, concept maps, flowcharts, mind maps, or step‑by‑step frameworks. Visual representations make relationships between ideas instantly clear, speeding comprehension and extending retention, especially for AI concepts, business models, and technical systems.

6. Active retrieval to cement knowledge

The final step is to force the brain to recall. After each learning session, the author uses NotebookLM to:

Generate test questions from the notes

Write a one‑minute explainer script

Summarise the material in their own words

Create flashcards or quizzes

Because learning happens during recall, this dramatically boosts memory durability.

Core secret of accelerated learning

All six workflows share a common pattern: select high‑quality input, consolidate everything in one place, convert input into a structured format, learn using a preferred method, interact with the content, and finally force recall. AI does not magically make you smarter; it simply supports this systematic process, preventing information overload and enabling lasting understanding.

Readers are encouraged to start with one simple workflow for a week, then gradually add others, building a repeatable, lightweight learning system rather than piling on more tools.

References

How to Learn Anything Faster With AI (6 Practical Workflows I Use Every Day) – https://medium.com/@nitinfab/how-to-learn-anything-faster-with-ai-6-practical-workflows-i-use-every-day-e4144a112eb1

How I use Gemini NotebookLM to read faster than 99% of people without reading everything – https://medium.com/@nitinfab/how-i-use-gemini-notebooklm-to-read-faster-than-99-of-people-without-reading-everything-b135dc821a46

AI can do more than you think: the most practical ways to use AI every day – https://generativeai.pub/ai-can-do-more-than-you-think-the-most-practical-ways-to-use-ai-every-day-620bc26cfcc0

Perplexity – https://www.perplexity.ai/

NotebookLM – https://notebooklm.google.com/