AI Officer Institute
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Prompt Library

Copy and paste any of these into your AI tool or NotebookLM. Replace text in [brackets] with your own details.

Prompt 01
Build a Tight Research Question

Use this before you start any research to make sure your question is specific enough to produce useful results.

Prompt
I want to do deep research on [broad topic - e.g., AI adoption in healthcare / customer retention in e-commerce / workforce automation].

Help me turn that into a tight research question. It should be:
- Small enough to be clear - one specific aspect, not the whole topic
- Big enough to matter - answerable with data that affects a real decision
- Answerable - not a philosophical question, a factual one

Give me 3 options for tight research questions. For each one, tell me what kind of sources I should look for to answer it.
Prompt 02
Evaluate a Source's Credibility

Use this when you find a source and want to decide whether it is worth adding to NotebookLM.

Prompt
I found the following source and I want to decide if it is credible enough to use in professional research:

Title: [title]
Author or organization: [author/org]
Publication: [where it was published]
Date: [date]
Link: [link if available]

Assess this source on:
1. Authority - is the author or organization a recognized expert in this field?
2. Accuracy - is it likely based on original research or primary data?
3. Currency - is it recent enough to be relevant?
4. Purpose - does it appear designed to inform or to sell?

Give me a credibility rating (high / medium / low) and one sentence on why.
Prompt 03
Extract Cited Insights from a Source

Use this inside NotebookLM or after pasting in a document excerpt to pull the most useful findings.

Prompt
I have uploaded [source name]. My research question is: [your tight question].

From this source, please extract:
1. The 3 most relevant findings to my research question
2. For each finding, the exact quote or data point from the source that supports it
3. Any limitations or caveats the authors note about their findings

Format the output so I can paste it directly into a research summary. Include the source name and publication date with each finding.
Prompt 04
Find Contradictions Across Sources

Use this when you have two or more sources in NotebookLM and want to do higher-level analysis.

Prompt
I have uploaded the following sources: [list source names].

My research question is: [your tight question].

Please do the following:
1. Identify the main claim each source makes about this topic
2. Find any points where the sources contradict or disagree with each other
3. Find any gaps - important questions that none of the sources fully answer
4. Tell me which source you find most credible for my specific question, and why

I want to understand where the evidence is strong and where it is still unclear.
Prompt 05
Turn Research Into Cited Content

Use this after your NotebookLM analysis to produce a usable output — a brief, a blog section, or a slide.

Prompt
I have completed research on [topic]. Here are my key findings with sources:

Finding 1: [finding] (Source: [name, date])
Finding 2: [finding] (Source: [name, date])
Finding 3: [finding] (Source: [name, date])

Please write a [short brief / 3-paragraph summary / executive summary / slide outline] for [audience - e.g., my leadership team / a client / a blog post].

Rules:
- Every claim must be tied to one of the sources above
- Plain language - no jargon
- Under [word count] words
- End with one clear recommendation or implication for the reader
Micro-Session Resources
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Deep Research · Micro-Session
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Hey! 👋 I've reviewed this session and I'm ready to go deeper with you. Here's what we're covering:
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🔍 Stop asking AI for answers — give it sources: Deep research uses NotebookLM to synthesise credible documents instead of generating from training data. The output is cited, not hallucinated.
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📋 The five-step workflow: Choose a topic → find a credible source → upload to NotebookLM → create a mind map or audio overview → pull your key insight. The difference from regular AI chat is full traceability.
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