Before building the Gem, let's identify the structure:

Go to Gemini → Gem manager → New Gem. Name it: Peer Response Coach

Paste these instructions:

You are my peer response writing coach for ENGL 170. When I share a peer's post, help me through these steps:

1. SUMMARIZE: State the peer's main argument in 2-3 sentences. Be charitable—represent them fairly, as Zay does with Caleb.

2. STEELMAN: What's the strongest version of their argument? What would make it even more convincing?

3. MY ANGLE: Ask me what domain expertise or personal knowledge I bring (like Zay brings sports knowledge). Help me connect it to their argument.

4. THESIS OPTIONS: Generate 2 possible thesis statements:
   - One that builds on their argument (agreement with extension)
   - One that challenges a specific assumption (respectful pushback)

5. NETWORK CONNECTIONS: Suggest ways to reference other bloggers in the network. "Who else has written about similar themes?"

6. EVIDENCE GAPS: What claims would need outside sources? What specific examples (like Zay's Super Bowl reference) would strengthen my argument?

7. OUTLINE: Create a 5-section structure:
   - Opening (peer summary + my question)
   - My expertise/angle
   - Analysis with evidence
   - Network connections
   - Thesis and closing

8. DRAFT: Write a ~800 word draft with [CITATION NEEDED] placeholders. Match Zay's tone: thoughtful, engaged, charitable to peers.

9. VERIFICATION: List every factual claim that needs a source.

Tone: Confident but respectful. Charitable to peers. Let personal perspective emerge naturally, not forced.

Open your new Gem and share the peer post you're responding to. You can paste the post text directly, or share the URL:

Here's the peer post I'm responding to:

https://zayamaro.github.io/markets-and-metrics.html

The Gem will begin with Step 1: SUMMARIZE.

After the summary, the Gem asks about your angle:

Gem: "What domain expertise or personal knowledge do you bring? What's your equivalent of Zay's sports fan perspective?"

You: "I know a lot about gaming — both video games and tabletop RPGs. I'm interested in how randomness works in games versus in real prediction markets."

The Gem generates thesis options:

Option A (Build): Caleb's right that prediction markets aggregate knowledge, but they work better for games with known rules than for real-world events with hidden variables.

Option B (Challenge): Prediction markets mistake "information aggregation" for "prediction" — the same way video games mistake high-score leaderboards for skill measurement.

You choose and refine:

I like Option B. Can you help me develop the gaming analogy? I'm thinking about RNG (random number generation) in games and how players complain about "unfair" randomness.

Ask the Gem to help you connect to other bloggers:

Who else in the network has written about prediction, randomness, or uncertainty?

The Gem might not know your specific classmates, but it will prompt you:

I don't have access to your class dashboard, but think about:

- Who has written about AI prediction or automation?
- Who has discussed the limits of data-driven decision-making?
- Who has a contrasting view you could engage with?

Check the dashboard and let me know who you'd like to reference.

Gabriel Bell wrote about the "Consumption Paradox" and how predictions about AI abundance might be wrong. Tom Bishop wrote about boxing and how stats can't capture "heart."

Ask for the draft:

Generate a draft using Thesis Option B, my gaming angle, and references to Gabriel and Tom.

The Gem produces ~800 words with your structure. Sections will include:

• Fair summary of Caleb's prediction markets argument
• Your gaming expertise introduction
• RNG analysis with specific examples
• Connections to Gabriel's and Tom's posts
• Your thesis about the limits of prediction

Look for [CITATION NEEDED] placeholders marking claims that need sources.

What claims in this draft need verification?

Sample response:

Claims needing verification:

1. Any statistics about prediction market accuracy
2. Specific game titles and their RNG systems (if you named them)
3. The claim about Kalshi's limitations
4. Any quotes attributed to Gabriel or Tom

Before publishing, verify these against the original sources.

Copy the draft to Google Docs. Your revision checklist:

• Replace all [CITATION NEEDED] with actual sources
• Check that quotes from Gabriel and Tom are accurate
• Adjust voice to sound like you (not like "generic AI")
• Add transitions that feel natural
• Cut anything that feels forced or off-topic