ALEX STUDY GUIDE

Science

Alex for Scientists

Study Guide: Alex for Scientists

Your reference for using Alex in research, experimentation, and scientific communication. Ready-to-run prompts for hypothesis development, data interpretation, scientific writing, and collaboration.

What This Guide Is Not

This is not a habit formation guide (see Self-Study Guide for that). This is a research toolkit — the specific ways Alex can accelerate your scientific work, and the prompts that deliver results.

Core Principle for Scientists

Science is about generating reliable knowledge. Alex can help you think more clearly, write more efficiently, and explore ideas faster — but it cannot replace scientific rigor. Every claim must trace back to evidence. Every interpretation must be yours to defend.

Use Alex as a thinking partner for brainstorming, literature synthesis, and drafting. Never use it as a source of scientific fact. The moment you cite something Alex said without verifying it, you’ve compromised your work.

The Seven Use Cases

1. Hypothesis Development and Refinement

When to use: When you have an observation, a hunch, or a phenomenon — but not yet a testable hypothesis.

Prompt pattern:

I'm developing a hypothesis in [field/subfield]:

Observation: [what you've noticed or found]
Existing theory: [current understanding in the field]
The puzzle: [what doesn't fit or isn't explained]
My intuition: [what you suspect might be happening]

Help me:
1. Articulate this as a testable hypothesis
2. Identify the key variables and their relationships
3. State the null hypothesis explicitly
4. List what would falsify this hypothesis
5. Suggest alternative hypotheses I should consider

Follow-up prompts:

Is this hypothesis too broad? How do I scope it for a single study?

What's the most common criticism this hypothesis would face?

What's the minimum viable experiment to test this?

2. Experimental Design Review

When to use: Before committing resources to an experiment. Catching design flaws early saves months.

Prompt pattern:

Review my experimental design:

Hypothesis: [what you're testing]
Method: [describe the experimental approach]
Variables:
- Independent: [what you're manipulating]
- Dependent: [what you're measuring]
- Controls: [what you're holding constant]
Sample: [subjects, specimens, data points]
Analysis plan: [how you'll analyze results]

Critique this design:
1. What confounds could produce false positives?
2. What could produce false negatives (miss a real effect)?
3. Is my sample size/power adequate?
4. What am I not controlling that I should?
5. What's the weakest link in this design?

Follow-up prompts:

How would I design this as a pilot study first?

What would a reviewer's first methodological criticism be?

If I find a positive result, what follow-up would strengthen the claim?

3. Literature Synthesis and Gap Analysis

When to use: Understanding the state of a field, finding research gaps, positioning your contribution.

Prompt pattern:

Help me synthesize the literature on [topic]:

What I've read:
[list key papers/findings you're aware of]

What I understand:
[your current mental model of the field]

What I'm trying to do:
[your research goal]

Help me:
1. Identify the major debates or unresolved questions
2. Find where the literature converges vs. contradicts
3. Spot methodological patterns (common approaches, limitations)
4. Identify gaps where new research is needed
5. Position my work relative to existing literature

Follow-up prompts:

What's the intellectual history here? How did the field arrive at this point?

Which papers are cited by everyone? Which important work is under-cited?

What would a paradigm-shifting result in this area look like?

Critical Note: Always verify specific claims, citations, and author attributions in primary sources. LLMs hallucinate papers and misattribute ideas.

4. Data Interpretation and Sense-Making

When to use: When you have results but aren’t sure what they mean. When patterns emerge but interpretation is unclear.

Prompt pattern:

Help me interpret these results:

Experiment: [what you did]
Hypothesis: [what you expected]
Results: [what you found — be specific with numbers/patterns]
Surprising elements: [what you didn't expect]

Help me think through:
1. What do these results suggest if taken at face value?
2. What alternative explanations exist?
3. What artifacts or confounds could produce this pattern?
4. What follow-up analysis would clarify the interpretation?
5. What should I NOT claim based on this data?

Follow-up prompts:

I want to claim [X]. What evidence would I need to support that claim confidently?

A colleague argues this is just [alternative explanation]. How do I distinguish?

What's the most conservative interpretation? The most exciting?

5. Scientific Writing and Manuscript Preparation

When to use: Drafting papers, structuring arguments, improving clarity.

Prompt pattern:

Help me with this section of my manuscript:

Section: [abstract / intro / methods / results / discussion]
Target journal: [where you're submitting]
Field conventions: [any specific norms]

Current draft:
[paste your text]

Help me:
1. Improve clarity and flow
2. Strengthen the logical structure
3. Cut unnecessary words without losing content
4. Ensure the key claims are front and center
5. Match the tone expectations of the field

Follow-up prompts:

This is too long. What can I cut without losing essential information?

A reviewer says this is unclear: [specific passage]. Rewrite for clarity.

Write three alternative opening sentences for this section.

Critical Note: The final scientific claims must be yours. Use Alex for clarity and structure — not for generating findings or interpretations you haven’t verified.

6. Collaboration and Communication

When to use: Preparing for lab meetings, collaborator discussions, or explaining work to non-specialists.

Prompt pattern:

Help me explain my research:

Audience: [lab group / collaborators / funding agency / general public]
Technical level: [expert / informed / lay]
Time/space: [5 min talk / 1 paragraph / poster]

My research:
[describe your work]

Key finding or contribution:
[what you want them to take away]

Create an explanation that:
1. Opens with why this matters
2. Explains the approach without jargon
3. Makes the key insight memorable
4. Anticipates common questions
5. Fits the constraints

Follow-up prompts:

Make this accessible to a smart non-scientist.

What analogy would make this concept click for someone unfamiliar with [field]?

What questions will the audience ask? Help me prepare answers.

7. Grant Writing and Funding Applications

When to use: Writing proposals, specific aims, significance sections.

Prompt pattern:

Help me strengthen this grant section:

Section: [specific aims / significance / innovation / approach]
Funder: [agency and program]
Page limit: [constraints]

Current draft:
[paste your text]

Help me:
1. Sharpen the significance — why does this matter?
2. Clarify the gap — what's unknown that this addresses?
3. Strengthen the approach — why will this work?
4. Anticipate reviewer concerns
5. Make the innovation explicit

Follow-up prompts:

The significance is weak. What framing would make this more compelling?

A study section reviewer will ask about feasibility. Help me address that.

What's the one-sentence version of this proposal?

Practice Progression

Week 1: Run your current hypothesis through the Development prompts. Sharpen it before your next experiment.

Week 2: Take one manuscript section through Scientific Writing. Compare before and after.

Week 3: Review an experimental design — yours or a student’s — using the critique prompts.

Week 4: Prepare an explanation of your work for two different audiences. Notice how the framing changes.

What Great Looks Like

After consistent use, you should notice:

The goal isn’t for Alex to do your science — it’s for Alex to help you think and communicate more clearly.

A Note on Scientific Integrity

Using AI in research raises important questions:

Your reputation is built on the reliability of your work. Protect it.