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The probability just spiked here.

I don't know what this means in the broader context of what will happen in the markets today, but this is not good that he felt the need to make this video.

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Lately I’ve been thinking a lot about what our real specialty should be. It’s not “prediction markets” in the abstract. It’s three areas where outcomes are deeply uncertain, narratives move fast, and second-order effects actually matter: • EV & energy technology • U.S.

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13/ If you want to get better at prediction markets: Stop asking “Is this true?” Start asking “What would have to change if it were?” That shift alone puts you ahead of most participants.

12/ Whether this battery works or not almost doesn’t matter. What matters is: “What does the market think happens next?” “Where is that belief wrong?” That’s the game.

11/ This is why prediction markets are misunderstood. They’re not about “predicting the future.” They’re about: • mapping narratives → consequences • consequences → verifiable events • events → mispriced probabilities

10/ Step 5: Trade attention before adoption. Before adoption data moves, something else moves first: • earnings call mentions • regulatory tone • OEM language shifts • analyst framing Prediction markets often price these late.

9/ If those checkpoints don’t fail, confidence compounds. Markets tend to underprice early credibility cascades.

8/ Step 4: Identify FALSIFIERS. Good prediction market thinkers always ask: “What event would kill this narrative?” In this case: • no real customer deliveries • no independent validation • no teardown confirmation • timelines quietly slip These become checkpoints.

7/ That’s why EV delivery markets, EV share markets, and auto OEM milestone markets are powerful proxy bets. You don’t need to name the tech. You trade the outcome.

6/ Example: EV adoption. If charging becomes “gas-station fast,” EV adoption isn’t linear anymore — it bends. So instead of “is the battery real?”, the market question becomes: “Are EV adoption or delivery targets priced too low?”

5/ Step 3: Look for SECOND-ORDER effects (this is the key). You don’t bet on the startup. You bet on the effects: • EV adoption accelerates • ICE vehicles lose appeal faster • Gas demand expectations soften • Battery metals demand shifts • OEM timelines compress These are

4/ Step 2: Ask “what breaks?” if this works. If batteries suddenly: • charge in minutes • last forever • don’t catch fire Then what stops being a bottleneck? Range anxiety. Charging time. Battery degradation. These are behavioral constraints, not specs.

3/ Here’s the framework I use anytime a flashy tech claim appears 👇 Step 1: Ignore hype. Extract CLAIMS. From the video, the real claims are: • fast charging • higher energy density • production-ready • safer • cheaper materials Each claim implies downstream consequences.

2/ In prediction markets, you don’t need something to be true. You need to ask: “If this is directionally true, what changes in the world?” That’s where edge lives.

Thread: How to think about prediction markets when a “breakthrough” drops 🧵 1/ A video is making the rounds claiming a solid-state battery breakthrough: • 5-minute charging • massive energy density • safer than lithium • already going into production vehicles Most people

Get your questions ready!

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