1. Go to your notebook
2. Click "Chat"
3. Select which sources to include (context)
4. Type your question
5. Click "Send"
6. Read the response
7. Ask a follow-up (context stays same)
8. Repeat until satisfied

You set: Paper A → Full Content
AI sees: Every word of Paper A
AI can: Cite specific sentences, notice nuances
Result: Precise, detailed answers (higher cost)

You set: Paper B → Summary Only
AI sees: Condensed summary, key points
AI can: Reference main ideas but not details
Result: Faster, cheaper answers (loses precision)

You set: Paper C → Not in Context
AI sees: Nothing (completely excluded)
AI can: Never reference it
Result: No cost, no privacy risk for that source

1. Click "Select Sources"
   (Shows list of all sources in notebook)

2. For each source:
   □ Checkbox: Include or exclude

   Level dropdown:
   ├─ Full Content
   ├─ Summary Only
   └─ Excluded

3. Check your selections
   Example:
   ✓ Paper A (Full Content) - "Main focus"
   ✓ Paper B (Summary Only) - "Background"
   ✓ Paper C (Excluded) - "Keep private"
   □ Paper D (Not included) - "Not relevant"

4. Click "Save Context"

5. Now chat uses these settings

Use when:
  - Analyzing one source deeply
  - Budget-conscious
  - Want focused answers

Use when:
  - Comprehensive analysis
  - Unlimited budget
  - Want AI to see everything

Use when:
  - Mix of important and reference material
  - Want thorough but not expensive
  - Most common strategy

Use when:
  - Company confidential materials
  - Personal sensitive data
  - Complying with data protection

"What do you think?"

Problems:
- Too vague (about what?)
- No context (what am I analyzing?)
- Can't verify answer (citing what?)

Result: Generic, shallow answer

"Based on the paper's methodology section,
what are the three main limitations the authors acknowledge?
Please cite which pages mention each one."

Strengths:
- Specific about what you want
- Clear scope (methodology section)
- Asks for citations
- Requires deep reading

Result: Precise, verifiable, useful answer

"What does the paper say about X?"
"Who are the authors?"
"What year was this published?"

Result: Simple, factual answers with citations

"How does this approach differ from the traditional method?"
"What are the main assumptions underlying this argument?"
"Why do you think the author chose this methodology?"

Result: Deeper thinking, comparison, critique

"How do these two sources approach the problem differently?"
"What's the common theme across all three papers?"
"If we combine these approaches, what would we get?"

Result: Cross-source insights, connections

"What are the practical implications of this research?"
"How could we apply these findings to our situation?"
"What's the next logical research direction?"

Result: Practical, forward-looking answers

Poor: "What about transformers?"
Good: "In this research paper on machine learning,
      explain the transformer architecture in 2-3 sentences,
      then cite which page describes the attention mechanism."

First question:
"What's the main finding?"

AI: "The study shows X [citation]"

Follow-up question:
"How does that compare to Y research?"

AI: "The key difference is Z [citation]"

Next question:
"Why do you think that difference matters?"

AI: "Because it affects A, B, C [explained]"

Round 1: Get overview
"What's this source about?"

Round 2: Get details
"What's the most important part?"

Round 3: Compare
"How does it relate to my notes on X?"

Round 4: Apply
"What should I do with this information?"

Context stays same, but you ask new questions:

Question 1: "What's the methodology?"
Question 2: "What are the limitations?"
Question 3: "What about the ethical implications?"
Question 4: "Who else has done similar work?"

All in one conversation, reusing context.

After question 3, you realize:
"I need more context from another source"

1. Click "Adjust Context"
2. Add new source or change context level
3. Your conversation history stays
4. Continue asking with new context

AI Response with Citation:
"The paper reports a 95% accuracy rate [see page 12]"

What this means:
✓ The claim "95% accuracy rate" is from page 12
✓ You can verify by reading page 12
✓ If page 12 doesn't say that, the AI hallucinated

If you get a response without citations:

Ask: "Please cite the page number for that claim"
or: "Show me where you found that information"

AI will:
- Find the citation
- Provide page numbers
- Show you the source

1. Get answer from Chat
2. Check citation (which source? which page?)
3. Click citation link (if available)
4. See the actual text in source
5. Does it really say what AI claimed?

If YES: Great, you can use this answer
If NO: The AI hallucinated, ask for correction

1. Set context: One source (Full Content)
2. Question 1: Overview
3. Question 2: Main argument
4. Question 3: Evidence for argument
5. Question 4: Limitations
6. Question 5: Next steps

Result: Complete understanding of one source

1. Set context: 2-3 sources (all Full Content)
2. Question 1: What does each source say about X?
3. Question 2: How do they agree?
4. Question 3: How do they disagree?
5. Question 4: Which approach is stronger?

Result: Understanding differences and trade-offs

1. Set context: Many sources (mix of Full/Summary)
2. Question 1: What are the main perspectives?
3. Question 2: What's missing from these views?
4. Question 3: What questions does this raise?
5. Question 4: What should I research next?

Result: Understanding landscape and gaps

1. Set context: Relevant sources (Full Content)
2. Question 1: What's the problem?
3. Question 2: What approaches exist?
4. Question 3: Pros and cons of each?
5. Question 4: Which would work best for [my situation]?

Result: Decision-making informed by research

Option A: All sources, Full Content
  Cost per response: 5,000 tokens

Option B: Only relevant sources, Summary Only
  Cost per response: 1,000 tokens

Savings: 80% cheaper, same conversation

Verbose: "Could you please analyze the methodology
         section of this paper and explain in detail
         what the authors did?"

Concise: "Summarize the methodology in 2-3 points."

Savings: 20-30% per response

GPT-4o: $0.15 per 1M input tokens
GPT-4o-mini: $0.03 per 1M input tokens
Claude Sonnet: $0.90 per 1M input tokens

For chat: Mini/Haiku models are usually fine
For deep analysis: Sonnet/Opus worth the cost