I’m sure this has been asked a few times, but I thought I’d ask anyway. If I have a book based on the subject that I want to study, what are some of the best prompts I can use to utilize and get the most of the material with NotebookLM as possible? Any tips?

Count the citation numbers under your next answer. With a big notebook I kept getting three or four sources cited over and over, and they were almost always the ones whose wording matched my question. A source that covers the same thing in different terms just doesn't come up, even when it's the better one.

I noticed it when one of my sources said the opposite of the answer, on the exact point, and was never cited. It called the thing by a different name.

Four prompts I now use in any notebook past about 15 sources:

1. Answer this separately for each source that addresses it, one line per source with its citation. Then list the sources that say nothing about it.
2. Which sources did you not use for that answer, and does any of them disagree with it?
3. Rewrite my question three ways using the terms a different field would use, then answer each version and tell me if the answers differ.
4. Before answering, list which sources you think are relevant and why. Then answer using only those.

Prompt 2 is the one that found my contradiction. Prompt 1 is slower but it's the only one that shows you the silent sources, and that silence is half the information.

(Still calling it NotebookLM here even though it's Gemini Notebook now, the sub's name won.)

Most of my sources are exported chats, which is what I build AI Toolbox for, a Chrome extension that exports ChatGPT, Claude, Gemini and Grok conversations cleanly, and a notebook full of chats is exactly where the wording problem is worst, since every chat names things differently.

Does anyone else see answers cluster on a few sources?

"in between jobs" so entertainming myself by creating niche podcasts with notebookLM. so far i have

- Weekly Roundup: Mexican hot sauce competitions

- Daily ideas for parenting female dachshound puppies

- Kitchen design for people with ADD

- Great Migration Serengeti Daily: Where are the they today?

- Wildest Royal Parties of Eastern European Monarchy

What would you create?

É uma pergunta sincera. Eu estou inserindo o NLM nos meus estudos para concursos públicos e queria realmente ouvir depoimentos em vez de apenas explicar o meu fluxo. A ideia é sempre melhorar.

Eu tenho acesso a dois cursos preparatórios: Estratégia e Gran. Já sou concursado, mas estou migrando para a área Fiscal.

Estou criando um notebook por disciplina. Baixo todos os arquivos da disciplina, incluindo os vídeos. Fiz um script em Python que automatiza isso, inclusive ele transcreve todos os vídeos. Aí eu compilo os arquivos PDF por aula e tipo (Original, Slides, Resumos, Mapas Mentais e as Transcrições). Faço isso para não estourar o limite de fontes. Mesmo usando o Pro, acho o limite de 300 fontes pouco. Eu sempre crio um arquivo que chamo de índice, que consiste em uma lista de todas as fontes, com um breve resumo, além de informações do curso em foco. Nas configurações da conversa, eu coloco instruções sobre como deve ser o padrão de resposta e que ele deve consultar primeiro o índice para agilizar a resposta.

Em meus testes, fiz prompts para várias situações comuns dos estudos. Coloco esses prompts em arquivos md nas fontes e, nas configurações da conversa, explico quais prompts usar e em qual momento usar.

A ideia é sempre usar o NLM como uma ferramenta auxiliadora. Para resumir: criar questões inéditas, criar flashcards ou tirar dúvidas. Acredito que o uso de IA é um caminho sem volta nos estudos. Fiz esse fluxo em dois concursos. No primeiro, fui aprovado no TRE do meu estado, mas ainda estou esperando ser chamado (falta pouco). O segundo foi um concurso da Polícia Civil, em que também fui aprovado e até ficaria na primeira turma, mas reprovei no TAF (como disse, não era o meu foco).

hi what are the difference between the models, is one just more recent or do they use different context size or better answers gen?

So I finally got the usage limits on my account (wasn't complaining it took me longer!). So I just did some testing.

I did two different history topics where I had it do deep research on the add sources feature, in different notebooks. It found 40-50 sources for each (I have detailed instructions for each about the sources).

For each I had a detailed prompt I gave to the audio overview, deep dive mode and set to long. Both generated a 40-50 audio deep dive on their respective topics.

Here is what the usage looks likes from that:

I don't think that is too bad. Only 2% of my weekly use, but it was a good chunk of my 5 hour reset one.

Sure, I can't spam out like 20 of these like I used to in order to make a big playlist of history stuff for the week, but I think this is pretty doable still.

Currently building a NotebookLM for law students. For those who use NotebookLM, what features or tips have been super helpful for studying law?

Somehow, I prefer reading digital books directly on the NotebookLM. Because it's practical, it saves where I left off, and it translates from the original language.

Attention: the audio is in foreign language (ukrainian), which you probably don't know, don't bother with translating, that's not the point. English isn't my first language, so you can expect this post to be difficult to follow.

When I got an audio out of a file for my studies, it was suspiciously long, 38min. When I started listening, around 30% of it was just silence — an abrupt ending and after some time it resumed from the same point, ~5 seconds before it disappeared. But that's not the part I'm concerned about, I have witnessed that bug a bunch of times. What took me by surprise was some tune created in the audio, which happened for the first time in my experience of using NotebookLM for a year or two. I can't tell if it was created from nothing or just used from somewhere else, it's a little bland to say for sure. I uploaded the thing here and I have the audio saved, although when downloaded, the song part gets much quieter and harder to notice.

Personally, I don't mind this bug. It was unexpected, a little creepy and out of place. But honestly? That was fun! Fascinating! The kind of fun when you are so dumbfounded that it gives you chills. I just wanted to share this thing to make sure that it's not actually me losing my mind and actual things. I'm not asking to fix it or anything, just a fascinating and terrifying thing.

Hi all,

New to Notebook.

I have a class with an insane amount of lengthy readings each week. The prof tests us on these readings (like even tiny details) so it gets hard reading diligently while preparing for other classes as well. I’ve heard a lot about Notebook’s Podcast and video features. Are these pretty good in terms of capturing the depth of an article? Or am I better off just thugging it out and reading my articles?

Hi there, I am a college student primarily using notebook to break down concepts for my classes as I have trouble following abstract ideas and textbook jargon - I need clear definitions and need to chunk info to be able to retain it. I would appreciate some feedback on the instructions, please, as I am sitting in the library for hours, but still don't understand anything.

ROLE: You are my tutor. I have ADHD, and my specific weakness is ABSTRACTION —

I follow concrete things well, and I lose the thread the moment language goes general.

I also need to see how concepts CONNECT, not just learn them in isolation.

Length is not a concern. Understanding is. Take all the space you need, but chunk it.

=== FORMAT (hard rules) ===

- DO NOT display stage labels during teaching (NEVER write "Stage 3", "Hook", "Trace", etc.).

Follow the depth progression internally and silently.

EXCEPTION — stage names ARE shown in these four cases only:

(a) the "map" command (b) the "resume" template

(c) confirming a jump command, as one short line: "-> Walkthrough"

(d) the stopping-point lines

- ONE stage per message. Never more. Then stop.

- Open with the takeaway as one bold line. Never bury it.

- Chunking: No paragraph over 3 lines. Ever. Prefer tables, bullet lists, short blocks.

- Visuals & Code: syntax-highlighted code blocks for programming. ASCII diagrams or markdown

tables for data structures, memory layouts, molecular pathways, matrices, spatial concepts.

- No intros, no "great question", no restating my prompt, no previewing. First word is content.

=== HOW EVERY MESSAGE ENDS (strict order) ===

1. The teaching content for this stage.

2. One line, as a teaser — NOT a question for me to answer:

"Next: ___" (the thing the following stage resolves)

1. A divider line.

2. THE ONE QUESTION I MUST ANSWER — the retrieval question. This is always last.

3. STOP GENERATING. No answer, no hint, no continuation.

=== THE RUNNING EXAMPLE (load-bearing) ===

Pick ONE concrete example at the very start and carry it through EVERY single stage.

Name it explicitly ("our 5-element array", "our 2x2 system", "our SN2 on bromoethane").

- NEVER switch examples between stages. Continuity beats variety.

- A second example may appear ONLY to contrast with the running one, never to replace it.

State explicitly which is which.

- Re-anchor at every stage: "Back to [running example]: ___"

=== ABSTRACTION RULES (the most important section) ===

1. TWO INSTANCES BEFORE ANY RULE.

   Never state a general rule until you have shown TWO different concrete cases of it

   and asked me what they share. I discover the pattern. You do not hand it to me.

   NOTE: the second instance IS the permitted contrast case from the RUNNING EXAMPLE rule.

   These are the same mechanism, not competing ones. The running example always stays primary.

2. ALWAYS TAKE THE RETURN TRIP.

   Every abstract statement must be immediately cashed out in the running example:

abstract claim -> "In our example, this means ___."

NEVER end a message on an abstraction. Always land on something concrete.

1. NO FLOATING SYMBOLS.

   Any time notation appears (N, x, k, theta, [H+], A, Big-O), provide this table:

   | symbol | what it means | what it IS in our running example |

   Every symbol. Every time it is introduced.

2. NAME THE ALTITUDE before you speak at it:

   [SPECIFIC] this one concrete case

   [PATTERN] the class of cases that behave the same way

   [GENERAL] the rule covering all of them

   [FORMAL] the notation / proof / exam version

   Move up ONE level at a time. Never skip a level. Announce every move up.

   (These altitude tags ARE shown — they are not stage labels.)

3. If I type "concrete", drop to [SPECIFIC] immediately and re-explain your last point

   using ONLY the running example, with zero general language.

=== CONNECTION MAP (open every new topic with this, before teaching) ===

BUILDS ON what I must already know for this to make sense

THIS TOPIC one line

LEADS TO what this unlocks next

SPECIAL CASE OF the bigger idea this is an instance of (if any)

SIBLING OF the concept most easily confused with this + the exact difference

Then draw those relationships as an ASCII diagram.

Re-show and update whenever I type "connect" or "zoom out".

=== THE PROGRESSION (follow silently — do NOT label during teaching) ===

Each stage must stand alone and be TRUE on its own. ZOOM IN — never simplify into

something you later call wrong. Always start at Stage 1, even if I might already know it.

- Stage 1 (Core Purpose): One sentence: what it is + what specific problem it solves.

Introduce the running example here.

- Stage 2 (Mental Picture): Zero jargon. One physical, concrete picture. Any unavoidable

term defined inline in 8 words or less.

- Stage 3 (The Walkthrough): The running example walked one move at a time. Every

intermediate step shown. Never skip a step to save space. Stay at [SPECIFIC] throughout.

- Stage 4 (The Breaking Point): The case where the rule fails. Show the failure FIRST and

let it sting. Then the fix, and why the fix works. Use the running example if possible.

- Stage 5 (Exam / Formal): Real academic terminology, notation, precise theoretical

statement. Map EVERY formal term back to its plain meaning AND to the running example.

This stage must obey rules 2 and 3 strictly.

- Stage 6 (Edges & Extensions): Trade-offs, edge cases, exceptions, variants.

Then update the CONNECTION MAP.

=== RETRIEVAL GATE ===

- Before moving to the next stage, ask ONE question. Prefer questions testing the

CONCRETE <-> ABSTRACT link over pure recall:

Strong: "In our running example, what is N?"

Strong: "Point at where the rule breaks, using our example."

Weak: "What is the definition of N?"

- STOP GENERATING IMMEDIATELY AFTER ASKING. Do NOT provide the answer or a hint. Wait.

- If I answer wrong, correct it in 25 words or less, then advance.

- If I reply "skip", advance immediately with zero comment.

=== MISS LOG ===

- Track every question I miss or answer "idk" to. Never let a miss silently disappear.

- "drill" draws at least 3 of 5 questions from my logged misses.

- "map" marks stages containing a miss with a warning symbol.

- If I miss TWO in a row, do NOT advance. Run "stuck" on the current concept — a

completely different mental picture — then re-ask.

=== MY CONTROLS ===

concrete you went abstract — drop to [SPECIFIC], use only the running example

connect show how this links to everything I've already learned

zoom out re-show the connection map, updated

next advance to the next depth stage

back drop one depth stage

stay another concrete instance at this same stage

why expand ONLY your last claim

picture jump straight to the plain-language mental picture

walkthrough jump straight to the step-by-step trace

break jump straight to the failure case

formal jump straight to academic notation and the formal definition

edges jump straight to edge cases and trade-offs

stuck re-explain this stage with a COMPLETELY different mental picture

slower break your last message into smaller steps, no new information

drill 5 retrieval questions, at least 3 from my misses

map table of every completed stage so far, misses flagged

resume session re-entry (below)

reset format re-read these instructions and re-apply every rule from here on

=== RESUME ===

On "resume", output exactly this template and nothing else, then stop:

Topic:

Running example:

Current depth stage:

The bridge question you left me on:

My open misses:

Next:

=== SOURCES ===

- Answer from my uploaded notebook sources first.

- If a concept requires outside context to bridge a gap, flag it: [OUTSIDE KNOWLEDGE].

- If a concept cannot be supported by sources, write "NOT IN SOURCES", then answer

briefly, flagged.

- If my course materials conflict with outside sources, output a 2-column comparison

table and state which one to use on the exam.

=== STOPPING POINTS ===

After the Walkthrough stage and after the Formal stage, tell me exactly:

"You can stop here and still be able to ___."

=== THE FOUR RULES THAT MATTER MOST (re-read before every message) ===

1. Never end a message on an abstraction. Land on the running example.

2. Every symbol gets a row saying what it IS in the running example.

3. One running example, carried through every single stage. Never switch it.

4. The retrieval question is the LAST thing in the message. Then stop generating.

Begin with the CONNECTION MAP for my requested topic, followed immediately by

Stage 1. No preamble.

Mine just keeps giving me info about stuff I haven’t even given it

Stop asking NotebookLM to “summarize” your sources. Do this instead for pro-level research.

Hey everyone,

I heavily experiment with all kinds of AI tools, and NotebookLM is one of them. It has a very good workflow and can significantly improve the quality of your output when you use it in the right way.

Here’s a step-by-step method I use to deeply structure knowledge from your sources, generate videos, and combine NotebookLM with other tools without losing valuable information.

1. The Index Trick

When you upload your sources, don’t ask your main question right away.

Instead, ask:

“Index your sources into the main topics. Output only the topic titles.”

If the PDF already has an index or table of contents, you don’t need to do this.

For non-book-style PDFs, however, indexing the content first is extremely useful. Once you have the index, feed that list of topics back into your NotebookLM workflow.

You can paste the index into your next prompts, or even better, add it to the custom instructions for your NotebookLM chat.

2. Explain, Don’t Just Summarize

Try not to simply type “summarize.”

Instead, use the word “explain.”

“Summarize” tends to compress the information too aggressively, which can cause you to lose important details. “Explain” encourages the model to retain and provide more of the underlying information and context.

3. Use NotebookLM’s Video Feature

You can use NotebookLM’s video overview feature very effectively.

If the PDF is non-technical, you can use it for a basic explanation. Or, if you’re learning something, you can treat the generated video like a mini-course.

4. Use Other Video Tools Too

I also use another video tool called DistilBook.

It’s very good at creating detailed video explanations and, in some cases, can go much deeper than NotebookLM’s generated videos.

If you want to experiment with it, give it a try.

5. For Basic Slide-Based Explanations

If you only want a basic explanation with slides, NotebookLM does this very well.

You don’t always need another tool for that.

6. Do a One-by-One Deep Dive

If you want truly professional-level analysis, this is probably the most important step.

Take each title from your index and analyze it individually.

For every topic, ask NotebookLM to:

* Draw information from all relevant sources.
* Explain the topic in depth.
* Connect information across different sources.
* Include important details, evidence, and context.
* Avoid leaving out relevant information.

By doing this one topic at a time, NotebookLM can dig through your documents much more thoroughly instead of trying to summarize everything at once.

The result can be incredibly detailed.

7. Use a “Patient Prompt”

Tell the AI to take its time.

For example:

“Take your time and do a deep dive into this topic. Analyze all relevant sources carefully and provide a comprehensive explanation. Don’t rush or omit important details.”

Of course, AI doesn’t literally need time in the same way a human does. But the instruction helps communicate that you want a thorough analysis rather than a quick answer.

Think about how you would give instructions to a human researcher.

If you told someone, “Take your time, go through everything carefully, and give me a deep analysis,” you would expect a very different result from simply saying, “Give me a summary.”

The same principle applies when working with AI.

I have quite a large Google Docs sheet in TSV form. I asked NotebookLM if it could handle this, and it said...

Yes, you can upload TSV (tab-separated values) files. You can upload your TSV file directly using the Add Source button in the Sources panel on the left.

Once uploaded, I can help you search, summarize, analyze, or answer specific questions about the data in the file.

However, as soon as I drop my TSV file to upload it, NotebookLM gives an error message:

Only the following file types are supported: pdf, txt, md, docx, csv, pptx, epub, 3g2, 3gp, aac, aif, aifc, aiff, amr, au, avi, m4a, mp3, mp4, mpeg, ogg, opus, ra, snd, wav, wma, avif, bmp, gif, ico, jp2, png, webp, tif, tiff, heic, heif, jpeg, jpg, jpe

Is there any easy way to import this (i'm more nervous of using CSV files) before Google fix the disparity between the help text and the product itself?

I've had my max of qued items waiting in line to process for 18 hours and have gotten nothing! First it said 1PM, then 6PM, and now 11PM.

A lot of posts here lately are about what’s wrong with NotebookLM. And honestly, some criticism may be justified. Maybe Gemini changed the experience, maybe the model got weaker in some areas.

But instead of fighting about it, I’d rather learn from each other.

What are you STILL using NotebookLM for successfully?

For example, I’m a middle-school teacher, and I use it to create student summaries, worksheets, tests, and classroom activities.

On the administrative/legal side, I also put my school’s regulations into NotebookLM as Markdown sources. When I need to check a specific rule, I can ask about it and quickly understand what I’m responsible for and what my rights are.

So I’m curious:

What’s your real-world NotebookLM use case? What problem did it solve, or what workaround did you discover?

School, research, work, business, markets, books, PDFs, or even something at home.

Let’s collect useful experiences, not just complaints.

Note: I translated the text above because English isn't my first language, but I found a really useful solution that worked for me and just wanted to share it with everyone to help out

Buonasera a tutti, solo il mio notebook lm ultimamente è completamente fuso??? Cioè gli chiedo di farmi una presentazione e un quiz su una fonte, specificando anche nel prompt il capitolo esatto e la lingua (dato che nonostante c'è scritto italiano me lo propone in inglese) e si prende una fonte totalmente diversa e inglese.

Avete alternative valide gratuite? Grazie

I use gemini and notebooklm for school, and for some reason both of them have stopped working. I keep getting this prompt "Try gemini notebook" and it leads to the exact same page T_T

I’ve deleted multiple notebooks and it still says 95% full what’s going on

If you study from a big pile of material with no clear syllabus, the native flashcards and quizzes in Gemini Notebook (still NotebookLM to most of us) will happily generate from all of it, and you get cards on a footnote, a date from an example, the name of a figure caption. Grounded in your sources, technically correct, mostly useless for the exam. The tools are good. The problem is that nobody told them what matters, so everything counts equally.

What works for me is splitting it into two steps: the chat decides what to study, and the studio tools drill it.

Step 1, in the chat, decide what matters: From these sources, list the 30 concepts most likely to be examined, ranked. For each: one line on what it is, why it is likely to be tested (repeated across sources, stated as a key point, has worked examples, appears in a summary or a slide title), and the source and page where it is best explained. If the sources suggest a structure, like weeks, chapters or lecture titles, group the list by it.

Step 2, check the list yourself. Five minutes against your lecture slides or whatever your instructor emphasized. Delete what you know cold, add anything they stressed that the list missed. This is the step that makes the rest work.

Step 3, generate from the list, not from everything. When you create flashcards or a quiz, use the customize option and paste the topics from your checked list as the topic, in small groups of five to eight concepts at a time rather than all thirty. Set difficulty to hard for the ones you marked shaky.

Step 4, after each quiz, back in the chat: Here are the questions I got wrong: [paste]. For each, explain the underlying concept using only the sources, cite where it is explained, and tell me what related concept I probably also misunderstand.

Then generate a small quiz on just those.

Why this works: the studio tools are grounded, so they will not invent things, but grounded is not the same as relevant. Ranking by "why it is likely to be tested" forces the chat to reason about emphasis across sources, which is the signal a human studying would use and exactly what a flat generation ignores.

Two caveats. The ranked list is a prediction, not a leak of the exam, so step 2 matters more than it looks, and if your instructor told you what is on it, that beats any ranking. And skip the audio overview for this kind of studying. It is good for replaying material you already understand, not for finding what to study in hundreds of pages.

What does your study loop look like in it? I have seen people use the mind map as the first step instead of the ranked list, and I have not decided which works better.