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Prediction markets are a (poorly understood) multi-billion dollar industry. This Law of Code episode is a multi-hour deep dive on prediction markets, from conclave betting in 15th century Rome to proposed rulemaking from the CFTC earlier this month. My goal: the internet's most comprehensive explainer on prediction markets. I...

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Jacob Robinson

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FROM A $50 SALARY IN SYRIA TO A $6M ROUND Episode 5 of PredictTime is live, and you'll hear it from a founder who restarted from zero three times and never sent a single cold email to close his round Ali, founder and CEO of XO Market. We go deep into why 400+ prediction markets are just copies of the same model, why a whale unfairly resolving his Polymarket bet became the tipping point, and how AI agents now decide market outcomes instead of humans Now he's building XO Market, where anyone can turn any idea into a conviction market. Everything you need to know about user-generated markets, XO Vaults and the future of prediction markets is in this episode --- Win 1,000 Conviction Points and get access to XO's weekly parlays with prizes up to $50,000 (we'll pick the winner on July 13): - sign up via the link: -drop your username with your most creative comment or question about the episode and follow Predict Time and XO Market --- Timecodes: 00:00 Intro 00:38 Raising $6M without pitching a single VC 04:29 Why not just copy Polymarket 07:05 Advice for builders: grants over VC money 12:15 Building a team across every continent 15:52 Ali's story: from Syria to Switzerland 19:29 Leaving corporate (Roche) for crypto 22:24 Why raising money is a liability, not a win 25:42 How XO Market conviction markets actually work 29:43 What stops thousands of dead markets 32:41 The tech that gives markets instant liquidity 37:43 How to create your own market 39:14 Getting attention: local communities & ambassadors 44:20 Not the of prediction markets 48:22 Who decides the outcome: AI resolution 51:43 XO Vault: market making for everyone 56:47 The moment XO Market took off 1:02:14 Is prediction market usage exaggerated? 1:05:17 Elon Musk and mention markets 1:07:04 AI vs humans: jobs and the jury system 1:13:56 Are Polymarket & Kalshi overvalued? 1:16:16 What's next: Parlays, Vaults & the World Cup 1:23:06 Is XO Market becoming a sportsbook? 1:25:15 AI agents trading on their own 1:27:40 Regulation & staying permissionless 1:33:08 The investors: 20VC, Harry & a cricket legend 1:44:55 Will there be a token? 1:46:45 Blitz: rapid-fire round 1:52:59 Closing & giveaway
1:55:06

FROM A $50 SALARY IN SYRIA TO A $6M ROUND Episode 5 of PredictTime is live, and you'll hear it from a founder who restarted from zero three times and never sent a single cold email to close his round Ali, founder and CEO of XO Market. We go deep into why 400+ prediction markets are just copies of the same model, why a whale unfairly resolving his Polymarket bet became the tipping point, and how AI agents now decide market outcomes instead of humans Now he's building XO Market, where anyone can turn any idea into a conviction market. Everything you need to know about user-generated markets, XO Vaults and the future of prediction markets is in this episode --- Win 1,000 Conviction Points and get access to XO's weekly parlays with prizes up to $50,000 (we'll pick the winner on July 13): - sign up via the link: -drop your username with your most creative comment or question about the episode and follow Predict Time and XO Market --- Timecodes: 00:00 Intro 00:38 Raising $6M without pitching a single VC 04:29 Why not just copy Polymarket 07:05 Advice for builders: grants over VC money 12:15 Building a team across every continent 15:52 Ali's story: from Syria to Switzerland 19:29 Leaving corporate (Roche) for crypto 22:24 Why raising money is a liability, not a win 25:42 How XO Market conviction markets actually work 29:43 What stops thousands of dead markets 32:41 The tech that gives markets instant liquidity 37:43 How to create your own market 39:14 Getting attention: local communities & ambassadors 44:20 Not the of prediction markets 48:22 Who decides the outcome: AI resolution 51:43 XO Vault: market making for everyone 56:47 The moment XO Market took off 1:02:14 Is prediction market usage exaggerated? 1:05:17 Elon Musk and mention markets 1:07:04 AI vs humans: jobs and the jury system 1:13:56 Are Polymarket & Kalshi overvalued? 1:16:16 What's next: Parlays, Vaults & the World Cup 1:23:06 Is XO Market becoming a sportsbook? 1:25:15 AI agents trading on their own 1:27:40 Regulation & staying permissionless 1:33:08 The investors: 20VC, Harry & a cricket legend 1:44:55 Will there be a token? 1:46:45 Blitz: rapid-fire round 1:52:59 Closing & giveaway

Predict Time

24,425 views • 1 month ago

E174: Tarek Mansour - Launching the First Regulated Perps In The U.S and building the next generation of financial markets Tarek Mansour is the co-founder and CEO of Kalshi, the first regulated prediction market exchange in the US, valued at $22 Billion. He grew up in Lebanon with a single mom, studied at MIT, worked at Citadel, and spent 6 years years building a company most people ignored before it finally took off. We talk about what it actually takes to not give up, why markets are better at finding truth than experts, why Kalshi is launching the first regulated Perps in the US, and how his team is building what he calls the next generation of financial markets. Timestamps: 0:00 Intro 1:54 Urgency 3:11 Anime 4:53 Who is Tarek? 7:02 Mathematics & Certainty 9:10 Tarek's chip on the shoulder 13:33 Partnerships: Trezor Bitwise 15:19 Resilience 16:31 Entrepreneurship is Therapy 18:23 The startup emotional rollercoaster 22:16 Showing up for 2000 days with no results 24:45 First time Founder advantage 26:40 When Kalshi almost made it, but did not 29:54 Partnerships: KAST 31:19 Focus Inputs, Not Results 33:16 The Kalshi beginnings story 36:00 The True Innovation Of Prediction Markets 38:28 How Prediction Markets Revolutionize The Media 41:37 Prediction Markets and Hedging explained simply 44:55 Leverage In Prediction Markets 47:16 Partnerships: Jupiter Ethena 48:00 Insider Trading 51:19 Insider Trading Rules enforcement: who is responsible? 55:26 How Kalshi spots Suspicious Behavior 56:59 Tarek's Honest View On Crypto 59:41 Launching the first Regulated Perps In The U.S 1:00:30 What Does Regulated Perps Mean? 1:02:22 Was Kalshi perps launch inspired by Hyperliquid? 1:03:41 Competition 1:05:58 Kalshi Endgame 1:07:06 What is Kalshi doing with the billions of $ they raised 1:08:31 Happiness and engagement 1:13:08 One Thing Tarek Should Let Go Of 1:14:18 Closing Thoughts
1:15:03

E174: Tarek Mansour - Launching the First Regulated Perps In The U.S and building the next generation of financial markets Tarek Mansour is the co-founder and CEO of Kalshi, the first regulated prediction market exchange in the US, valued at $22 Billion. He grew up in Lebanon with a single mom, studied at MIT, worked at Citadel, and spent 6 years years building a company most people ignored before it finally took off. We talk about what it actually takes to not give up, why markets are better at finding truth than experts, why Kalshi is launching the first regulated Perps in the US, and how his team is building what he calls the next generation of financial markets. Timestamps: 0:00 Intro 1:54 Urgency 3:11 Anime 4:53 Who is Tarek? 7:02 Mathematics & Certainty 9:10 Tarek's chip on the shoulder 13:33 Partnerships: Trezor Bitwise 15:19 Resilience 16:31 Entrepreneurship is Therapy 18:23 The startup emotional rollercoaster 22:16 Showing up for 2000 days with no results 24:45 First time Founder advantage 26:40 When Kalshi almost made it, but did not 29:54 Partnerships: KAST 31:19 Focus Inputs, Not Results 33:16 The Kalshi beginnings story 36:00 The True Innovation Of Prediction Markets 38:28 How Prediction Markets Revolutionize The Media 41:37 Prediction Markets and Hedging explained simply 44:55 Leverage In Prediction Markets 47:16 Partnerships: Jupiter Ethena 48:00 Insider Trading 51:19 Insider Trading Rules enforcement: who is responsible? 55:26 How Kalshi spots Suspicious Behavior 56:59 Tarek's Honest View On Crypto 59:41 Launching the first Regulated Perps In The U.S 1:00:30 What Does Regulated Perps Mean? 1:02:22 Was Kalshi perps launch inspired by Hyperliquid? 1:03:41 Competition 1:05:58 Kalshi Endgame 1:07:06 What is Kalshi doing with the billions of $ they raised 1:08:31 Happiness and engagement 1:13:08 One Thing Tarek Should Let Go Of 1:14:18 Closing Thoughts

MR SHIFT 🦁

603,699 views • 3 months ago

DROPS E39: Worm - The permissionless truth machine Nass Diba studied quantum physics, worked at Facebook, then left to build in crypto. He's now building Worm - a permissionless prediction market on Solana with leverage. His thesis: prediction markets are the only mechanism that consistently surfaces truth, and they're about to matter more than ever. He grew up in Iran under a dictatorship. He watched state TV claim there was no inflation while the money in people's pockets shrank. That's not a metaphor for him - it's the problem he's building to solve. We talk about: - Why CNN and Fox both showed different election results in 2024 - Growing up in Iran and experiencing information asymmetry under dictatorship firsthand - Building a Poly Market Telegram mini app in September 2024 and getting 56,000 users overnight - Why 90% of those users weren't American - and what that revealed about the technology - How leverage works on prediction markets, why it took 9 months to build, and what liquidation actually means when there's no price - just probability - Why Polymarket and Kalshi are scratching the surface of what's possible - Prediction markets as the engagement layer for Web3 - and what Worm is launching on HyperLiquid HIP-4 And much more… Timestamps: 0:00 Introduction 1:17 Welcome to DROPS 1:57 Prediction Markets in 2026 3:08 Can the crowd be wrong? 4:26 Money Creates Better Truth Discovery 5:22 Who is Nass? 5:55 Growing up in Iran 6:52 Entered Crypto in 2019 8:05 Discovering Prediction Markets 10:08 Signal Behind the 2024 Elections 11:59 How Prediction Markets Disrupt Traditional Media 13:16 Traditional Media Prioritizes Incentives Over Truth 17:33 Polymarket vs Kalshi: Which Model Wins? 18:25 Why is Kalshi or Polymarket enough? 19:43 Lessons Learned Building on Polymarket 21:07 Building Worm on Solana 21:56 What Is Worm and its special elements? 23:36 How Leverage Works on Prediction Markets 25:29 Hedging 27:33 Prediction Markets vs Options & Perps 29:15 How Liquidations Work 31:13 Why Leverage is more than a Gimmick 33:04 Building Leverage Was Harder Than Expected 34:12 Solving Liquidity Problem 36:05 How Worm Acquires Users 36:59 Inflection Point for Prediction Markets 39:06 Why Worm chose Solana 40:24 Becoming the Hyperliquid of Prediction Markets 42:26 Solana vs Hyperliquid: Which Wins? 45:00 Conclusion
46:11

DROPS E39: Worm - The permissionless truth machine Nass Diba studied quantum physics, worked at Facebook, then left to build in crypto. He's now building Worm - a permissionless prediction market on Solana with leverage. His thesis: prediction markets are the only mechanism that consistently surfaces truth, and they're about to matter more than ever. He grew up in Iran under a dictatorship. He watched state TV claim there was no inflation while the money in people's pockets shrank. That's not a metaphor for him - it's the problem he's building to solve. We talk about: - Why CNN and Fox both showed different election results in 2024 - Growing up in Iran and experiencing information asymmetry under dictatorship firsthand - Building a Poly Market Telegram mini app in September 2024 and getting 56,000 users overnight - Why 90% of those users weren't American - and what that revealed about the technology - How leverage works on prediction markets, why it took 9 months to build, and what liquidation actually means when there's no price - just probability - Why Polymarket and Kalshi are scratching the surface of what's possible - Prediction markets as the engagement layer for Web3 - and what Worm is launching on HyperLiquid HIP-4 And much more… Timestamps: 0:00 Introduction 1:17 Welcome to DROPS 1:57 Prediction Markets in 2026 3:08 Can the crowd be wrong? 4:26 Money Creates Better Truth Discovery 5:22 Who is Nass? 5:55 Growing up in Iran 6:52 Entered Crypto in 2019 8:05 Discovering Prediction Markets 10:08 Signal Behind the 2024 Elections 11:59 How Prediction Markets Disrupt Traditional Media 13:16 Traditional Media Prioritizes Incentives Over Truth 17:33 Polymarket vs Kalshi: Which Model Wins? 18:25 Why is Kalshi or Polymarket enough? 19:43 Lessons Learned Building on Polymarket 21:07 Building Worm on Solana 21:56 What Is Worm and its special elements? 23:36 How Leverage Works on Prediction Markets 25:29 Hedging 27:33 Prediction Markets vs Options & Perps 29:15 How Liquidations Work 31:13 Why Leverage is more than a Gimmick 33:04 Building Leverage Was Harder Than Expected 34:12 Solving Liquidity Problem 36:05 How Worm Acquires Users 36:59 Inflection Point for Prediction Markets 39:06 Why Worm chose Solana 40:24 Becoming the Hyperliquid of Prediction Markets 42:26 Solana vs Hyperliquid: Which Wins? 45:00 Conclusion

MR SHIFT 🦁

31,109 views • 2 months ago

Over a trillion dollars worth of perps are traded every month, yet 99% people have never heard of them. This Law of Code episode is a multi-hour deep dive on perps, starting from the history of grain futures in Chicago to Friday's historic CFTC announcements. It took me months to put this together. My goal: the internet's most comprehensive explainer on perps. You'll hear from the world's leading experts on the legal layer of perps; Jake Chervinsky and Brad Bourque of Hyperliquid Policy Center, Brett Harrison of Architect, Katherine Kirkpatrick Bos, Ryne Miller 🇺🇸, Mike Frisch and David Shafer of Coinbase 🛡️. By the end of this episode, I promise you'll be in the top percentile for understanding perps, regardless of where you're starting from. (You just might need to listen twice. There's a lot here.) Timestamps: 0:00 Intro 4:04 What is a perp Brett Harrison 7:18 Why futures contracts exist 8:15 Liquidity fragmentation 11:01 History of U.S. futures Ryne Miller 🇺🇸 17:08 Richard Nixon, the gold standard and financial futures 21:27 Birth of the CFTC 24:27 Robert Shiller's 1992 paper Katherine Kirkpatrick Bos 30:09 Price convergence 32:00 The funding rate 43:41 Oracles and manipulation risk 47:39 Are perps swaps or futures? 52:44 A Mike Selig clip on perps 54:02 The DCM framework 59:16 DCMs, DCOs and FCMs explained 1:04:55 History of crypto perps (BitMEX) 1:13:00 How Hyperliquid works 1:25:41 CFTC's historic announcements on May 29, 2026 1:35:00 Fireside with Jake Chervinsky and Brad Bourque of Hyperliquid Policy Center Nothing in this podcast is legal or investment advice.
2:13:32

Over a trillion dollars worth of perps are traded every month, yet 99% people have never heard of them. This Law of Code episode is a multi-hour deep dive on perps, starting from the history of grain futures in Chicago to Friday's historic CFTC announcements. It took me months to put this together. My goal: the internet's most comprehensive explainer on perps. You'll hear from the world's leading experts on the legal layer of perps; Jake Chervinsky and Brad Bourque of Hyperliquid Policy Center, Brett Harrison of Architect, Katherine Kirkpatrick Bos, Ryne Miller 🇺🇸, Mike Frisch and David Shafer of Coinbase 🛡️. By the end of this episode, I promise you'll be in the top percentile for understanding perps, regardless of where you're starting from. (You just might need to listen twice. There's a lot here.) Timestamps: 0:00 Intro 4:04 What is a perp Brett Harrison 7:18 Why futures contracts exist 8:15 Liquidity fragmentation 11:01 History of U.S. futures Ryne Miller 🇺🇸 17:08 Richard Nixon, the gold standard and financial futures 21:27 Birth of the CFTC 24:27 Robert Shiller's 1992 paper Katherine Kirkpatrick Bos 30:09 Price convergence 32:00 The funding rate 43:41 Oracles and manipulation risk 47:39 Are perps swaps or futures? 52:44 A Mike Selig clip on perps 54:02 The DCM framework 59:16 DCMs, DCOs and FCMs explained 1:04:55 History of crypto perps (BitMEX) 1:13:00 How Hyperliquid works 1:25:41 CFTC's historic announcements on May 29, 2026 1:35:00 Fireside with Jake Chervinsky and Brad Bourque of Hyperliquid Policy Center Nothing in this podcast is legal or investment advice.

Jacob Robinson

156,503 views • 3 months ago

Inside the mind of an ex-SIG quant trader who can't turn off the EV brain - even for his kid's school choice Andrew Courtney (Andrew Courtney) ran the International ETFs Trading Desk at Susquehanna International Group for ~15 years before leaving in 2023. He now runs Kalshionomics (Kalshinomics), a prediction markets analytics tool, and writes the Whirligig Bear, one of the sharpest prediction markets Substacks out there. "I think of everything as a bet. I kind of don't understand how you talk to normal people — they do not do that." SIG trains their junior traders with poker, spending 2hrs/day turning over cards after every hand, justifying every decision quantitatively AND qualitatively. 15 years later, Andrew views prediction markets the same way: read who's on the other side, size accordingly, fold when the whale comes back at you 10x. We cover: - Why SIG pays junior traders to play poker for 2hrs/day — & what happens after every single hand - The "one eye on the market, always" attention tax that destroys most people's careers - How to find edge in prediction markets by asking: who am I actually trading against? - Why meme-heavy, overhyped markets (Taylor Swift at the Super Bowl) might be the juiciest trades - The insider trading debate in prediction markets — & why it's "socially corrosive" - Floor trading vs. upstairs quant: why the transition saved his career - 40 connections after ~15 years at one of the world's best firms — the hidden cost of prop trading - Why he doesn't have collision insurance on his car (& the EV math behind it) Thank you so much Andrew Courtney for coming on the pod! Timestamps: 00:00 Intro 05:00 Floor trading vs. electronic trading 06:28 What makes an upstairs trader 10:16 Poker as trader training 13:00 Thinking in bets as a mental framework 15:11 Decision trees in real life 16:40 Where prediction markets actually have edge 19:00 Why the LLM forecasting layer falls short 19:40 Liquidity incentives and trading low-volume markets 22:00 Limiting downside even when the model is wrong 24:32 Executing in illiquid markets 25:44 Fair value vs. directional conviction 27:11 Bayesian updating when liquidity responds 28:40 Fading hype and crowded narratives 31:07 Longshot bias vs. fanbase bias 34:20 How to judge whether you really have edge 36:40 Building analytics tools for prediction markets 38:20 The temporary edge for smart amateurs 40:35 Where prediction markets fit best 41:20 Markets that shouldn’t exist 43:20 Why insider trading corrodes incentives 46:52 Are prediction markets a net good or bad 50:47 Minimizing degeneracy and maximizing signal 53:32 A simple EV mindset anyone can use
56:48

Inside the mind of an ex-SIG quant trader who can't turn off the EV brain - even for his kid's school choice Andrew Courtney (Andrew Courtney) ran the International ETFs Trading Desk at Susquehanna International Group for ~15 years before leaving in 2023. He now runs Kalshionomics (Kalshinomics), a prediction markets analytics tool, and writes the Whirligig Bear, one of the sharpest prediction markets Substacks out there. "I think of everything as a bet. I kind of don't understand how you talk to normal people — they do not do that." SIG trains their junior traders with poker, spending 2hrs/day turning over cards after every hand, justifying every decision quantitatively AND qualitatively. 15 years later, Andrew views prediction markets the same way: read who's on the other side, size accordingly, fold when the whale comes back at you 10x. We cover: - Why SIG pays junior traders to play poker for 2hrs/day — & what happens after every single hand - The "one eye on the market, always" attention tax that destroys most people's careers - How to find edge in prediction markets by asking: who am I actually trading against? - Why meme-heavy, overhyped markets (Taylor Swift at the Super Bowl) might be the juiciest trades - The insider trading debate in prediction markets — & why it's "socially corrosive" - Floor trading vs. upstairs quant: why the transition saved his career - 40 connections after ~15 years at one of the world's best firms — the hidden cost of prop trading - Why he doesn't have collision insurance on his car (& the EV math behind it) Thank you so much Andrew Courtney for coming on the pod! Timestamps: 00:00 Intro 05:00 Floor trading vs. electronic trading 06:28 What makes an upstairs trader 10:16 Poker as trader training 13:00 Thinking in bets as a mental framework 15:11 Decision trees in real life 16:40 Where prediction markets actually have edge 19:00 Why the LLM forecasting layer falls short 19:40 Liquidity incentives and trading low-volume markets 22:00 Limiting downside even when the model is wrong 24:32 Executing in illiquid markets 25:44 Fair value vs. directional conviction 27:11 Bayesian updating when liquidity responds 28:40 Fading hype and crowded narratives 31:07 Longshot bias vs. fanbase bias 34:20 How to judge whether you really have edge 36:40 Building analytics tools for prediction markets 38:20 The temporary edge for smart amateurs 40:35 Where prediction markets fit best 41:20 Markets that shouldn’t exist 43:20 Why insider trading corrodes incentives 46:52 Are prediction markets a net good or bad 50:47 Minimizing degeneracy and maximizing signal 53:32 A simple EV mindset anyone can use

Ethan Kho

436,074 views • 6 months ago

Sports books take 10% of every bet and ban winners. Novig founder and CEO Jacob Fortinsky joins our Stateful podcast, hosted by Mason Strom. In this episode, they discuss why prediction markets may replace the casino model in sports: - Sports books kick out profitable users. - 5% better odds on average vs. traditional platforms - CFTC shift: sports event contracts regulated as financial products nationwide - Be your own house: set your own odds, collect the spread - $2T global sports market with zero dominant exchange 00:17 The $75M Bet on Sports Prediction Markets 01:08 From StubHub Algorithms to Prediction Markets 02:21 Replacing the House: Peer-to-Peer Sports Betting 03:59 Do Sportsbooks Survive? 06:14 Be Your Own House: The Market Maker Model 08:35 How Novig Makes Money Without a Vig 10:23 Why Now? The Regulatory Shift Changing Everything 11:51 The Modern Sports Bettor: More Trader Than Fan 14:58 Prediction Market Regulation: Lawsuits, CFTC & Congress 17:45 Novig vs. DraftKings, Polymarket & Robinhood 20:18 Where Prediction Markets Go From Here 22:48 Quickfire: Favorite Sport to Bet On 24:37 Founder Advice: Stay Alive & Don't Chase Trends 26:22 Hiring for Culture Over Raw Talent
29:30

Sports books take 10% of every bet and ban winners. Novig founder and CEO Jacob Fortinsky joins our Stateful podcast, hosted by Mason Strom. In this episode, they discuss why prediction markets may replace the casino model in sports: - Sports books kick out profitable users. - 5% better odds on average vs. traditional platforms - CFTC shift: sports event contracts regulated as financial products nationwide - Be your own house: set your own odds, collect the spread - $2T global sports market with zero dominant exchange 00:17 The $75M Bet on Sports Prediction Markets 01:08 From StubHub Algorithms to Prediction Markets 02:21 Replacing the House: Peer-to-Peer Sports Betting 03:59 Do Sportsbooks Survive? 06:14 Be Your Own House: The Market Maker Model 08:35 How Novig Makes Money Without a Vig 10:23 Why Now? The Regulatory Shift Changing Everything 11:51 The Modern Sports Bettor: More Trader Than Fan 14:58 Prediction Market Regulation: Lawsuits, CFTC & Congress 17:45 Novig vs. DraftKings, Polymarket & Robinhood 20:18 Where Prediction Markets Go From Here 22:48 Quickfire: Favorite Sport to Bet On 24:37 Founder Advice: Stay Alive & Don't Chase Trends 26:22 Hiring for Culture Over Raw Talent

Pantera Capital

25,422 views • 5 months ago

Inside the Billionaire Backed Prediction Markets Hedge Fund. Run by a 24-Year-Old. Camilo Saravia (camilo), founder of BlueWalker Capital, a systematic prediction markets fund backed by Daniel Howard of Halo Capital. "I don't want more capital. I'm extremely long our equity." We cover: - Why insider trading in prediction markets is terrible for liquidity and GOOD for society - Prediction markets as cash-backed truth in a world of AI slop and disinformation - Why he turned down the allocator question entirely, and the "Goldilocks zone" that makes a fund this size work - His research team's actual mission statement: "collapse the entropy of the internet into signal" - Trading Spotify streams and measuring how fast Mamdani viralizes vs Cuomo on TikTok - Why beating earnings has almost no correlation with the stock going up, and why only testing reveals that - Mention markets as literal next-word prediction, and how makers got sniped out - Hiring missionaries with a mercenary work style, and why every hire takes a pay cut vs Citadel, Jane Street, Wintermute - Daniel Howard's mandate: faster, more risk, more aggression. "They haven't backed me to print 7% APY" - The abundance mindset, from a kid with immigrant parents sitting across from generational wealth - A venture mindset applied to public equities: pulling the thread from free cash flow down to Glassdoor culture - Why you never need to be binarily right: buy at 20, sell at 40, never wait for resolution Highlights: (00:00) Intro (00:56) Taker vs maker, reflexive vs proactive: the strategy map (03:08) What makes an event contract different from an equity (04:53) Insider trading in prediction markets: bug or feature (08:18) Cash-backed truth in a world of AI slop (12:43) Where edge actually comes from (14:19) The dataset: billions of records a day (17:44) Building a money management business from an empty office (21:34) Why asset management competes with software as a business model (23:51) How to underwrite elite talent (25:50) Missionaries vs mercenaries, and why the tension is the point (30:54) Recruiting against Citadel money (and losing on salary every time) (37:32) "We can't compromise speed": the Daniel Howard mandate (44:45) The abundance mindset (48:28) "Why should I invest?" / "I don't want more capital" (50:12) Collapsing the entropy of the internet (51:04) Spotify streams, TikTok virality, and mention markets (53:17) The one data provider he'd long if he could (55:49) There's a business behind everything (01:00:07) How to find the real drivers in any market (01:04:04) A venture mindset applied to public equities (01:10:06) Prediction markets 101: where to actually start (01:12:05) Why you don't need to be binarily right (01:13:19) Final question: building personal edge against the models
1:16:45

Inside the Billionaire Backed Prediction Markets Hedge Fund. Run by a 24-Year-Old. Camilo Saravia (camilo), founder of BlueWalker Capital, a systematic prediction markets fund backed by Daniel Howard of Halo Capital. "I don't want more capital. I'm extremely long our equity." We cover: - Why insider trading in prediction markets is terrible for liquidity and GOOD for society - Prediction markets as cash-backed truth in a world of AI slop and disinformation - Why he turned down the allocator question entirely, and the "Goldilocks zone" that makes a fund this size work - His research team's actual mission statement: "collapse the entropy of the internet into signal" - Trading Spotify streams and measuring how fast Mamdani viralizes vs Cuomo on TikTok - Why beating earnings has almost no correlation with the stock going up, and why only testing reveals that - Mention markets as literal next-word prediction, and how makers got sniped out - Hiring missionaries with a mercenary work style, and why every hire takes a pay cut vs Citadel, Jane Street, Wintermute - Daniel Howard's mandate: faster, more risk, more aggression. "They haven't backed me to print 7% APY" - The abundance mindset, from a kid with immigrant parents sitting across from generational wealth - A venture mindset applied to public equities: pulling the thread from free cash flow down to Glassdoor culture - Why you never need to be binarily right: buy at 20, sell at 40, never wait for resolution Highlights: (00:00) Intro (00:56) Taker vs maker, reflexive vs proactive: the strategy map (03:08) What makes an event contract different from an equity (04:53) Insider trading in prediction markets: bug or feature (08:18) Cash-backed truth in a world of AI slop (12:43) Where edge actually comes from (14:19) The dataset: billions of records a day (17:44) Building a money management business from an empty office (21:34) Why asset management competes with software as a business model (23:51) How to underwrite elite talent (25:50) Missionaries vs mercenaries, and why the tension is the point (30:54) Recruiting against Citadel money (and losing on salary every time) (37:32) "We can't compromise speed": the Daniel Howard mandate (44:45) The abundance mindset (48:28) "Why should I invest?" / "I don't want more capital" (50:12) Collapsing the entropy of the internet (51:04) Spotify streams, TikTok virality, and mention markets (53:17) The one data provider he'd long if he could (55:49) There's a business behind everything (01:00:07) How to find the real drivers in any market (01:04:04) A venture mindset applied to public equities (01:10:06) Prediction markets 101: where to actually start (01:12:05) Why you don't need to be binarily right (01:13:19) Final question: building personal edge against the models

Ethan Kho

114,296 views • 18 days ago

I CAUGHT THE $436,000 INSIDER Episode 3 of PredictTime is live - and you'll hear this story straight from the source tre 🇨🇦, founder of Polysights. We go deep - into how his platform catches insiders on Polymarket before the news drops and into his life journey Everything you need to know about insider trading in prediction markets - is in this episode Timecodes: 00:00 — Cold open / Highlights 00:51 — The $436k profit case: how a $34k order paid out before the news 01:05 — Meet Tre, founder of Polysights 01:35 — How Polysights spots anomalies: radar score and wallet clusters 03:17 — What Polysights actually does: advanced analytics for prediction markets 04:00 — From aircraft engineering to the Canadian Air Force 05:01 — Entrepreneurial roots: e-commerce and dropshipping 06:13 — Selling the first company at 23 and getting paid in crypto 08:21 — Were meme coins detrimental or a launchpad into Web3? 09:46 — The "Fatherhood Buff": how a son changes drive and risk 12:03 — Rank 1 in WoW: gaming as training for founders 14:35 — From PredictFun on Blast to Polymarket: trader-first, builder-second 16:35 — Building Insider Finder: scoring every trade on Polymarket 19:34 — The Maduro case in detail: why it wasn't posted publicly 21:18 — Mayor Eric Adams dropout: prediction markets vs mainstream media 22:24 — MicroStrategy markets: 6–0 on recycled wallets 26:50 — Philosophy: why insider trading accelerates truth 30:56 — Disagreeing with Kalshi's CEO: the centralized vs decentralized divide 35:19 — If the CFTC bans insider trading: validation or death? 48:09 — Arbitrage across Polymarket, Kalshi and sportsbooks 50:48 — Why prediction markets finally boomed in 2024–2025 54:39 — Alpha decay and growing to 45,000 users 55:59 — The Bloomberg / WSJ / NYT moment 58:08 — Fundraising $1.5M from Halifax: the lead VC drama 01:02:26 — Business model: moving away from subscriptions 01:04:21 — No-code automated trading strategies as the future 01:13:20 — Roadmap: V1 by Q2 and a regulated prediction market in Canada 01:16:24 — Solo founder reality: from intern-only to an ex-Meta tech lead 01:18:46 — Crucial advice: don't build another trading terminal 01:20:27 — Breaking in with no connections, no VCs, no hub 01:24:58 — Rapid-fire: Ferrari, Bitcoin to $1M, Hyperliquid vs Kalshi 01:27:35 — The biggest insider trade he can't prove: Lord Miles 01:28:12 — Role models: CZ, Kobe, Shane, Elon 01:30:00 — Final advice: stop overthinking and take the swing
1:32:53

I CAUGHT THE $436,000 INSIDER Episode 3 of PredictTime is live - and you'll hear this story straight from the source tre 🇨🇦, founder of Polysights. We go deep - into how his platform catches insiders on Polymarket before the news drops and into his life journey Everything you need to know about insider trading in prediction markets - is in this episode Timecodes: 00:00 — Cold open / Highlights 00:51 — The $436k profit case: how a $34k order paid out before the news 01:05 — Meet Tre, founder of Polysights 01:35 — How Polysights spots anomalies: radar score and wallet clusters 03:17 — What Polysights actually does: advanced analytics for prediction markets 04:00 — From aircraft engineering to the Canadian Air Force 05:01 — Entrepreneurial roots: e-commerce and dropshipping 06:13 — Selling the first company at 23 and getting paid in crypto 08:21 — Were meme coins detrimental or a launchpad into Web3? 09:46 — The "Fatherhood Buff": how a son changes drive and risk 12:03 — Rank 1 in WoW: gaming as training for founders 14:35 — From PredictFun on Blast to Polymarket: trader-first, builder-second 16:35 — Building Insider Finder: scoring every trade on Polymarket 19:34 — The Maduro case in detail: why it wasn't posted publicly 21:18 — Mayor Eric Adams dropout: prediction markets vs mainstream media 22:24 — MicroStrategy markets: 6–0 on recycled wallets 26:50 — Philosophy: why insider trading accelerates truth 30:56 — Disagreeing with Kalshi's CEO: the centralized vs decentralized divide 35:19 — If the CFTC bans insider trading: validation or death? 48:09 — Arbitrage across Polymarket, Kalshi and sportsbooks 50:48 — Why prediction markets finally boomed in 2024–2025 54:39 — Alpha decay and growing to 45,000 users 55:59 — The Bloomberg / WSJ / NYT moment 58:08 — Fundraising $1.5M from Halifax: the lead VC drama 01:02:26 — Business model: moving away from subscriptions 01:04:21 — No-code automated trading strategies as the future 01:13:20 — Roadmap: V1 by Q2 and a regulated prediction market in Canada 01:16:24 — Solo founder reality: from intern-only to an ex-Meta tech lead 01:18:46 — Crucial advice: don't build another trading terminal 01:20:27 — Breaking in with no connections, no VCs, no hub 01:24:58 — Rapid-fire: Ferrari, Bitcoin to $1M, Hyperliquid vs Kalshi 01:27:35 — The biggest insider trade he can't prove: Lord Miles 01:28:12 — Role models: CZ, Kobe, Shane, Elon 01:30:00 — Final advice: stop overthinking and take the swing

Predict Time

58,073 views • 3 months ago

Semil Shah (Semil) is one of the greatest seed investors ever, with early bets on Figma, DoorDash, and Instacart. He's also the next guest on Lightspeed's Out of Office, Episode 2. A few weeks ago, he and I hosted a talk on seed investing, prediction markets, startup launch videos, and AI with a bunch of our friends and co-investors at the famed NYC music venue, Joe's Pub. We also filmed our pre-game walk and talk before we got to the venue. Full video here. If you enjoy it, please subscribe below. Chapters: 0:00 – Launch videos and why everything looks the same 1:30 – New podcast formats 2:30 – The launch video arms race 6:30 – Generative media & the true cost collapse of video 10:59 – Is any app category safe from OpenAI? 13:10 – Sam Altman & execution 18:00 – How consumers actually use AI 20:01 – What Sora means for social media 24:09 – Seed investors and the “AI wave” 29:24 – Live at Joe’s Pub: Scott Rogowsky intro 30:39 – Sports and the betting market 35:40 – Polymarket and prediction markets 43:30 – Why seed is under attack 47:20 – People vs. markets 52:20 – AI and category risk 59:00 – Signs of an AI bubble 1:06:03 – The AI roll-up craze 1:11:08 – Audience Q&A
1:20:10

Semil Shah (Semil) is one of the greatest seed investors ever, with early bets on Figma, DoorDash, and Instacart. He's also the next guest on Lightspeed's Out of Office, Episode 2. A few weeks ago, he and I hosted a talk on seed investing, prediction markets, startup launch videos, and AI with a bunch of our friends and co-investors at the famed NYC music venue, Joe's Pub. We also filmed our pre-game walk and talk before we got to the venue. Full video here. If you enjoy it, please subscribe below. Chapters: 0:00 – Launch videos and why everything looks the same 1:30 – New podcast formats 2:30 – The launch video arms race 6:30 – Generative media & the true cost collapse of video 10:59 – Is any app category safe from OpenAI? 13:10 – Sam Altman & execution 18:00 – How consumers actually use AI 20:01 – What Sora means for social media 24:09 – Seed investors and the “AI wave” 29:24 – Live at Joe’s Pub: Scott Rogowsky intro 30:39 – Sports and the betting market 35:40 – Polymarket and prediction markets 43:30 – Why seed is under attack 47:20 – People vs. markets 52:20 – AI and category risk 59:00 – Signs of an AI bubble 1:06:03 – The AI roll-up craze 1:11:08 – Audience Q&A

Michael Mignano

28,448 views • 9 months ago

My conversation with Rob Hadick ＞|＜. As General Partner at Dragonfly, Rob has one of the clearest views on how blockchain is evolving from speculative crypto into the actual infrastructure of global capital markets. In this episode we dig into why finance, payments, asset issuance, and markets are the only parts of crypto that are truly scaling and how the industry is quietly becoming TradFi’s onchain upgrade. We spend a lot of time mapping traditional capital markets primitives directly onto blockchain rails and examining where value is actually going to accrue as tokenization, stablecoins, and onchain trading mature. At the center of the conversation is the belief that blockchain is no longer building a parallel financial system it is becoming the settlement, issuance, and trading layer for the existing one, while crypto itself settles into a more mature “capital markets +” phase focused on real assets, institutional flows, and sustainable business models. We discuss: - The current state of crypto as capital markets infrastructure and the decline of pure speculative narratives - Why finance, payments, and tokenization are winning while most other crypto applications struggle - The architectural parallel between traditional capital markets and on-chain systems - Tokenized assets = Securities - Stablecoins = Cash / settlement - DEXs & on-chain venues = Exchanges - Prediction markets = Information markets - Why institutions are moving on-chain and what they actually want (control, privacy, segregated markets) - Token vs equity: where value accrues in a non-Clarity Act world - The mass extinction event in crypto VC and why Dragonfly is doubling down on financial infrastructure - Stablecoins, RWAs, and the real path to “tokenization of everything” - Prediction markets (and why Polymarket matters) as the next interface layer - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of Crypto as Capital Markets 2:00 – Why Speculative Narratives Are Fading 7:00 – Finance, Payments & Tokenization as the Only Scaling Verticals 12:00 – Institutional Adoption & What Wall Street Actually Wants 18:00 – Token vs Equity Value Accrual 25:00 – Blockchain as the New Settlement & Issuance Layer 35:00 – Prediction Markets, Information & the Next Interface 45:00 – Crypto VC Consolidation & Dragonfly’s Thesis 55:00 – Real-World Assets, Stablecoins & On-Chain Markets 1:05:00 – Closing Thoughts: Where Value Accrues Next Enjoy!
1:06:45

My conversation with Rob Hadick ＞|＜. As General Partner at Dragonfly, Rob has one of the clearest views on how blockchain is evolving from speculative crypto into the actual infrastructure of global capital markets. In this episode we dig into why finance, payments, asset issuance, and markets are the only parts of crypto that are truly scaling and how the industry is quietly becoming TradFi’s onchain upgrade. We spend a lot of time mapping traditional capital markets primitives directly onto blockchain rails and examining where value is actually going to accrue as tokenization, stablecoins, and onchain trading mature. At the center of the conversation is the belief that blockchain is no longer building a parallel financial system it is becoming the settlement, issuance, and trading layer for the existing one, while crypto itself settles into a more mature “capital markets +” phase focused on real assets, institutional flows, and sustainable business models. We discuss: - The current state of crypto as capital markets infrastructure and the decline of pure speculative narratives - Why finance, payments, and tokenization are winning while most other crypto applications struggle - The architectural parallel between traditional capital markets and on-chain systems - Tokenized assets = Securities - Stablecoins = Cash / settlement - DEXs & on-chain venues = Exchanges - Prediction markets = Information markets - Why institutions are moving on-chain and what they actually want (control, privacy, segregated markets) - Token vs equity: where value accrues in a non-Clarity Act world - The mass extinction event in crypto VC and why Dragonfly is doubling down on financial infrastructure - Stablecoins, RWAs, and the real path to “tokenization of everything” - Prediction markets (and why Polymarket matters) as the next interface layer - Sustainable business models and where value will ultimately capture Timestamps: 0:00 – Introduction & State of Crypto as Capital Markets 2:00 – Why Speculative Narratives Are Fading 7:00 – Finance, Payments & Tokenization as the Only Scaling Verticals 12:00 – Institutional Adoption & What Wall Street Actually Wants 18:00 – Token vs Equity Value Accrual 25:00 – Blockchain as the New Settlement & Issuance Layer 35:00 – Prediction Markets, Information & the Next Interface 45:00 – Crypto VC Consolidation & Dragonfly’s Thesis 55:00 – Real-World Assets, Stablecoins & On-Chain Markets 1:05:00 – Closing Thoughts: Where Value Accrues Next Enjoy!

Logan Jastremski

45,906 views • 13 days ago

This is not Meta In this episode of Deeply Intents (🎙️,🎧) I chat with ceteris, Head of Research at Delphi. This episode provides an essential perspective on how to survive and thrive over multi-year cycles. In this episode we discuss: - Do cycles still exist? - Meta games & how they work - Onboarding into crypto - Not enough of the right infra - Solana (You eat what you kill) - How to survive – building, investing, or trading Timestamps 0:00 - Welcome to CT 7:22 - Unique perspectives on infrastructure 13:48 - Do cycles still exist? 17:59 - Few assets do well 23:28 - DeFi summer cycle was different 28:02 - Early in a new meta 29:47 - Onboarding into crypto 33:43 - Privacy as a king maker 37:19 - Capital formation use case 42:24 - Too much of the wrong infra 47:08 - New things take time to build 49:43 - Rollup specialization 51:16 - Why build on Solana? 53:32 - RWA issuance is a weird narrative 57:05 - Prop AMMs, BAM, ACE, MCP, Firedancer 1:00:53 - You eat what you kill 1:04:19 - Prediction markets and sports betting 1:09:38 - The whole world is becoming financialized 1:13:00 - Investing in bid ideas 1:19:07 - How to survive? Don't blow up! 1:26:12 - Try things out 1:27:38 - Shitposting on CT
1:29:08

This is not Meta In this episode of Deeply Intents (🎙️,🎧) I chat with ceteris, Head of Research at Delphi. This episode provides an essential perspective on how to survive and thrive over multi-year cycles. In this episode we discuss: - Do cycles still exist? - Meta games & how they work - Onboarding into crypto - Not enough of the right infra - Solana (You eat what you kill) - How to survive – building, investing, or trading Timestamps 0:00 - Welcome to CT 7:22 - Unique perspectives on infrastructure 13:48 - Do cycles still exist? 17:59 - Few assets do well 23:28 - DeFi summer cycle was different 28:02 - Early in a new meta 29:47 - Onboarding into crypto 33:43 - Privacy as a king maker 37:19 - Capital formation use case 42:24 - Too much of the wrong infra 47:08 - New things take time to build 49:43 - Rollup specialization 51:16 - Why build on Solana? 53:32 - RWA issuance is a weird narrative 57:05 - Prop AMMs, BAM, ACE, MCP, Firedancer 1:00:53 - You eat what you kill 1:04:19 - Prediction markets and sports betting 1:09:38 - The whole world is becoming financialized 1:13:00 - Investing in bid ideas 1:19:07 - How to survive? Don't blow up! 1:26:12 - Try things out 1:27:38 - Shitposting on CT

apriori

21,739 views • 9 months ago

The world’s youngest self-made woman billionaire took on the U.S. government…and won. Luana Lopes Lara, co-founder of Kalshi, opens up about taking on the feds, her billionaire moment, and her Bitcoin story. I really enjoyed this interview and I hope you will too! TIMESTAMPS: 00:00 Ballerina to in Brazil 03:41 Meeting Her Co-Founder at MIT 09:18 65 Lawyers Said It Was Impossible 13:59 How Kalshi Stops Insider Trading 16:56 The Most Surprising Market on Kalshi 17:32 Why She Sued the U.S. Government 21:00 Why Women Are Joining Prediction Markets 22:25 Her First Bitcoin: A $100 Story 23:49 Becoming the Youngest Female Billionaire 27:16 Advice for Young Women and Founders 29:23 Is the American Dream Still Alive? 32:36 Where Crypto and Prediction Markets Collide 35:48 Kalshi Goes Global 37:33 The Currency Problem No One Talks About 39:06 Are Prediction Markets Actually Right? 40:23 Can You Create Your Own Market? 42:29 The Moment They Almost Gave Up 45:09 What She’d Tell Her Younger Self 46:58 The One Market She Wants to Trade
50:07

The world’s youngest self-made woman billionaire took on the U.S. government…and won. Luana Lopes Lara, co-founder of Kalshi, opens up about taking on the feds, her billionaire moment, and her Bitcoin story. I really enjoyed this interview and I hope you will too! TIMESTAMPS: 00:00 Ballerina to in Brazil 03:41 Meeting Her Co-Founder at MIT 09:18 65 Lawyers Said It Was Impossible 13:59 How Kalshi Stops Insider Trading 16:56 The Most Surprising Market on Kalshi 17:32 Why She Sued the U.S. Government 21:00 Why Women Are Joining Prediction Markets 22:25 Her First Bitcoin: A $100 Story 23:49 Becoming the Youngest Female Billionaire 27:16 Advice for Young Women and Founders 29:23 Is the American Dream Still Alive? 32:36 Where Crypto and Prediction Markets Collide 35:48 Kalshi Goes Global 37:33 The Currency Problem No One Talks About 39:06 Are Prediction Markets Actually Right? 40:23 Can You Create Your Own Market? 42:29 The Moment They Almost Gave Up 45:09 What She’d Tell Her Younger Self 46:58 The One Market She Wants to Trade

Natalie Brunell ⚡️

1,180,077 views • 4 months ago

LIVE NOW - Is The Crypto-Native Era Coming to an End? - Lessons from 10 Years in Crypto Joey Krug (Founders Fund partner, former Pantera Capital co-CIO, and Augur co-founder) returns to unpack whether the “crypto-native era” is fading as institutions and mainstream apps adopt crypto rails without adopting crypto culture. We dig into: - The prediction markets breakout (and why Polymarket finally found product-market fit). - The coming regulatory fights around market structure and “insider” edges. - What’s next for founders building in a post-cypherpunk, distribution-first phase of crypto. Enjoy the episode! -------------- TIMESTAMPS 0:00 Intro 5:45 Is Crypto-Native Dead? 16:37 Lessons From Augur 20:29 Prediction Market’s Success 25:24 Just Gambling? 27:50 Prediction Market Regulation 41:03 Founders Fund Polymarket Bet 44:37 FBI Raid 46:47 Founders Fund Crypto Investment Thesis 53:46 DATs 57:02 Layer1 Valuation 1:00:40 ETH Valuation 1:04:32 What Would Joey Build Today? 1:06:13 Crypto x AI 1:10:09 Frontier Tech x Crypto 1:14:26 4-Year Cycles 1:16:16 Less Upside in Crypto Now? 1:19:37 Crypto Privacy 1:20:41 Last & Next Decade 1:23:05 Closing & Disclaimers
1:23:50

LIVE NOW - Is The Crypto-Native Era Coming to an End? - Lessons from 10 Years in Crypto Joey Krug (Founders Fund partner, former Pantera Capital co-CIO, and Augur co-founder) returns to unpack whether the “crypto-native era” is fading as institutions and mainstream apps adopt crypto rails without adopting crypto culture. We dig into: - The prediction markets breakout (and why Polymarket finally found product-market fit). - The coming regulatory fights around market structure and “insider” edges. - What’s next for founders building in a post-cypherpunk, distribution-first phase of crypto. Enjoy the episode! -------------- TIMESTAMPS 0:00 Intro 5:45 Is Crypto-Native Dead? 16:37 Lessons From Augur 20:29 Prediction Market’s Success 25:24 Just Gambling? 27:50 Prediction Market Regulation 41:03 Founders Fund Polymarket Bet 44:37 FBI Raid 46:47 Founders Fund Crypto Investment Thesis 53:46 DATs 57:02 Layer1 Valuation 1:00:40 ETH Valuation 1:04:32 What Would Joey Build Today? 1:06:13 Crypto x AI 1:10:09 Frontier Tech x Crypto 1:14:26 4-Year Cycles 1:16:16 Less Upside in Crypto Now? 1:19:37 Crypto Privacy 1:20:41 Last & Next Decade 1:23:05 Closing & Disclaimers

Bankless

12,983 views • 8 months ago

Debunking Coffeezilla’s prediction market claims In his recent video “prediction markets aren’t just gambling,” Coffeezilla made the three untrue or misleading claims below: 1) “The only way you get the news early, by the way, is if it’s insider trading.” 2) “All these prediction markets are doing is aggregating sentiment on the news.” 3) “The only way you can get something not in the news from these markets is if someone with non-news information trades, which is AKA inside information.” I want to start by saying that I’ve really enjoyed Coffeezilla’s content in the past, and I appreciate him blacking out my name in the tweet he screenshared. I also watched the full video and agreed with parts of it (and disagreed with other parts). That said, these three claims are egregiously incorrect, and I want to correct the record. I hope Coffeezilla reads this and reconsiders these points 1) “The only way you get the news early, by the way, is if it’s insider trading.” Merriam-Webster defines insider trading as “the illegal use of information available only to insiders in order to make a profit in financial trading.” This claim is wrong because it is clearly possible to get information early in entirely legal ways. For example, in CPI inflation markets, someone might notice prices rising on goods they regularly buy, or a sophisticated trader might aggregate pricing data across many products and form a forecast before the CPI release. Journalists may later report on inflation, but the information existed beforehand. Markets also react faster to sudden events, like a Trump Truth Social post or an earthquake, than journalists do. Traders are financially incentivized to react in seconds; journalists are not. Recent high-profile examples include Nobel Peace Prize, Spotify, and Time POTY markets, where traders had information before the news broke. In the Nobel case, there was disinformation claiming insider trading, but as far as most observers can tell, the information was obtained legally via web-scraping. Even if the Nobel Committee disliked it, legally obtained information is fair game. 2) “All these prediction markets are doing is aggregating sentiment on the news.” This is easy to debunk. Prediction markets do aggregate information, but not merely sentiment or headlines. That’s likely why CNN and CNBC partnered with Kalshi. News is filtered through editors, incentives, and bias. Taking headlines at face value is not a winning trading strategy. Savvy traders treat news as one input among many variables. If a headline says “Poll X shows Clinton up 10 points,” markets may adjust, but they don’t blindly price the headline. They factor in other variables. I’d argue markets are often smarter than the news. Domer❤️‍🔥 has even argued that Fed markets on Kalshi are more accurate than CME due to traders like himself making them more efficient, and I think he’s right. 3) “The only way you can get something not in the news from these markets is if someone with non-news information trades, which is AKA inside information.” Merriam-Webster defines insider information as “information not known to the public that one has obtained by virtue of being an insider.” You can obtain non-news information without being an insider. This overlaps with point one, but here’s a concrete example. For the recent TN-07 special election, I traveled to TN-07 and spoke with voters leaving early-voting sites and with everyday residents. I learned how little awareness there was that a special election was even happening, and how voters were thinking about the race. That information wasn’t in the news, but it informed how I traded. I’m not an insider. This was “alpha hunting” through firsthand observation. Almost every serious prediction market trader has similar stories. This is certainly not "insider trading." I’m genuinely curious to hear your thoughts, Coffeezilla, and hope for a good-faith dialogue. I hope you are doing well!
0:24

Debunking Coffeezilla’s prediction market claims In his recent video “prediction markets aren’t just gambling,” Coffeezilla made the three untrue or misleading claims below: 1) “The only way you get the news early, by the way, is if it’s insider trading.” 2) “All these prediction markets are doing is aggregating sentiment on the news.” 3) “The only way you can get something not in the news from these markets is if someone with non-news information trades, which is AKA inside information.” I want to start by saying that I’ve really enjoyed Coffeezilla’s content in the past, and I appreciate him blacking out my name in the tweet he screenshared. I also watched the full video and agreed with parts of it (and disagreed with other parts). That said, these three claims are egregiously incorrect, and I want to correct the record. I hope Coffeezilla reads this and reconsiders these points 1) “The only way you get the news early, by the way, is if it’s insider trading.” Merriam-Webster defines insider trading as “the illegal use of information available only to insiders in order to make a profit in financial trading.” This claim is wrong because it is clearly possible to get information early in entirely legal ways. For example, in CPI inflation markets, someone might notice prices rising on goods they regularly buy, or a sophisticated trader might aggregate pricing data across many products and form a forecast before the CPI release. Journalists may later report on inflation, but the information existed beforehand. Markets also react faster to sudden events, like a Trump Truth Social post or an earthquake, than journalists do. Traders are financially incentivized to react in seconds; journalists are not. Recent high-profile examples include Nobel Peace Prize, Spotify, and Time POTY markets, where traders had information before the news broke. In the Nobel case, there was disinformation claiming insider trading, but as far as most observers can tell, the information was obtained legally via web-scraping. Even if the Nobel Committee disliked it, legally obtained information is fair game. 2) “All these prediction markets are doing is aggregating sentiment on the news.” This is easy to debunk. Prediction markets do aggregate information, but not merely sentiment or headlines. That’s likely why CNN and CNBC partnered with Kalshi. News is filtered through editors, incentives, and bias. Taking headlines at face value is not a winning trading strategy. Savvy traders treat news as one input among many variables. If a headline says “Poll X shows Clinton up 10 points,” markets may adjust, but they don’t blindly price the headline. They factor in other variables. I’d argue markets are often smarter than the news. Domer❤️‍🔥 has even argued that Fed markets on Kalshi are more accurate than CME due to traders like himself making them more efficient, and I think he’s right. 3) “The only way you can get something not in the news from these markets is if someone with non-news information trades, which is AKA inside information.” Merriam-Webster defines insider information as “information not known to the public that one has obtained by virtue of being an insider.” You can obtain non-news information without being an insider. This overlaps with point one, but here’s a concrete example. For the recent TN-07 special election, I traveled to TN-07 and spoke with voters leaving early-voting sites and with everyday residents. I learned how little awareness there was that a special election was even happening, and how voters were thinking about the race. That information wasn’t in the news, but it informed how I traded. I’m not an insider. This was “alpha hunting” through firsthand observation. Almost every serious prediction market trader has similar stories. This is certainly not "insider trading." I’m genuinely curious to hear your thoughts, Coffeezilla, and hope for a good-faith dialogue. I hope you are doing well!

Benjamin Freeman

80,021 views • 8 months ago

Here is my conversation with Foresight Institute's Allison Duettmann. She's about as brilliant as it gets; one of those rare polymath futurist Moloch-slaying goddess types, as you'll see. So if you want to solve coordination problems, I highly recommend a listen. Chapters below, and give her a follow at Allison Duettmann 2:18 - Existential Hope 5:45 - Utopian vs Dystopian Art 11:00 - The Story Circle 16:03 - Naturalistic Arguments vs Transhumanism 25:29 - Foresight Institute 27:46 - World-building Hackathons 33:20 - Pareto-topia 35:24 - How to make win-wins more obvious? 41:02 - Building Cooperation in Society 45:38 - Avoiding 1984 50:58 - Building the Third Attractor 1:11:00 - Crypto Solutions to Tragedy of Commons 1:15:56 - Prediction markets 1:21:00 - AGI & the Cooperation Game 1:28:00 - Super Rationality 1:32:48 -Advice to Listeners 1:41:31 - Favorite Games 1:44:14 - Rapid fire Predictions
1:53:37

Here is my conversation with Foresight Institute's Allison Duettmann. She's about as brilliant as it gets; one of those rare polymath futurist Moloch-slaying goddess types, as you'll see. So if you want to solve coordination problems, I highly recommend a listen. Chapters below, and give her a follow at Allison Duettmann 2:18 - Existential Hope 5:45 - Utopian vs Dystopian Art 11:00 - The Story Circle 16:03 - Naturalistic Arguments vs Transhumanism 25:29 - Foresight Institute 27:46 - World-building Hackathons 33:20 - Pareto-topia 35:24 - How to make win-wins more obvious? 41:02 - Building Cooperation in Society 45:38 - Avoiding 1984 50:58 - Building the Third Attractor 1:11:00 - Crypto Solutions to Tragedy of Commons 1:15:56 - Prediction markets 1:21:00 - AGI & the Cooperation Game 1:28:00 - Super Rationality 1:32:48 -Advice to Listeners 1:41:31 - Favorite Games 1:44:14 - Rapid fire Predictions

Liv Boeree

38,280 views • 1 year ago

"These aren't just labels. They are categorizations of financial instruments that actually determine who can trade these products, how your money's protected, what taxes you pay." This week on CoinDesk's Policy Protocol, John Lothian and Kalshi's Udesh Jha debate whether crypto perpetuals are futures or swaps with Rebecca Rettig and Renato Mariotti. Chapters/Timecodes: 00:00 Welcome to The Policy Protocol 01:10 CFTC's 267-Page Prediction Markets Rule 03:10 60+ CEOs Back the BRCA 05:30 The Perpetuals Debate 07:43 John Lothian's Case: Do Perpetuals Look Like Swaps? 09:45 Kalshi's Udesh Jha on Funding Rates and Cost of Carry 12:43 Would Swap Status Shut Out Retail? 16:45 Is Kalshi Making the Rules Up? 19:25 John's Closing: Market Manipulation Concerns 20:46 Udesh's Closing: 'Regulation First' 23:29 Person of the Week: State Regulators 23:38 Illinois' Digital Asset Trading Tax 24:20 NY DFS Aligns With Genius
25:59

"These aren't just labels. They are categorizations of financial instruments that actually determine who can trade these products, how your money's protected, what taxes you pay." This week on CoinDesk's Policy Protocol, John Lothian and Kalshi's Udesh Jha debate whether crypto perpetuals are futures or swaps with Rebecca Rettig and Renato Mariotti. Chapters/Timecodes: 00:00 Welcome to The Policy Protocol 01:10 CFTC's 267-Page Prediction Markets Rule 03:10 60+ CEOs Back the BRCA 05:30 The Perpetuals Debate 07:43 John Lothian's Case: Do Perpetuals Look Like Swaps? 09:45 Kalshi's Udesh Jha on Funding Rates and Cost of Carry 12:43 Would Swap Status Shut Out Retail? 16:45 Is Kalshi Making the Rules Up? 19:25 John's Closing: Market Manipulation Concerns 20:46 Udesh's Closing: 'Regulation First' 23:29 Person of the Week: State Regulators 23:38 Illinois' Digital Asset Trading Tax 24:20 NY DFS Aligns With Genius

CoinDesk

19,653 views • 2 months ago

NEW POD | EP 76 🎙️ Q4 State of The Crypto Market ft. Imran & qw 1:05 We’re Back 2:25 Where Are We In This Cycle? 4:31 AI and Stock Market 6:27 AI Bubble 10:15 Energy Consumption and Production 16:34 China and US Innovation 17:44 Aster 18:52 Hyperliquid and Aster Competition 22:48 Proxy Wars in Crypto 26:33 Future of Crypto Exchanges 27:32 Binance vs Solana 32:59 Moats in Crypto 33:43 Crypto Lending 35:25 TradFi Banking and Crypto Custody 36:48 Social Aspect in Crypto 38:09 AI Glasses and Social Media 45:05 Waymo and Robo Taxis 49:10 Prediction Markets 50:54 Kalshi and PolyMarket Competition 55:27 Convergence of Speculative Markets 57:35 59:00 Overheard 1:02:08 DATs 1:05:26 Stripe and Stablecoins 1:07:10 Genius Act and New Stablecoins 1:07:43 Stablecoin as a Micropayment 1:11:23 Pump and Streaming 1:14:53 Apps to Watch 1:17:12 Stablecoin Growth 1:19:11 Stablecoin Startups in Different Regions 1:20:05 Novel Ideas for Startups 1:24:03 Wen Cycle Top? Link ↓
1:27:10

NEW POD | EP 76 🎙️ Q4 State of The Crypto Market ft. Imran & qw 1:05 We’re Back 2:25 Where Are We In This Cycle? 4:31 AI and Stock Market 6:27 AI Bubble 10:15 Energy Consumption and Production 16:34 China and US Innovation 17:44 Aster 18:52 Hyperliquid and Aster Competition 22:48 Proxy Wars in Crypto 26:33 Future of Crypto Exchanges 27:32 Binance vs Solana 32:59 Moats in Crypto 33:43 Crypto Lending 35:25 TradFi Banking and Crypto Custody 36:48 Social Aspect in Crypto 38:09 AI Glasses and Social Media 45:05 Waymo and Robo Taxis 49:10 Prediction Markets 50:54 Kalshi and PolyMarket Competition 55:27 Convergence of Speculative Markets 57:35 59:00 Overheard 1:02:08 DATs 1:05:26 Stripe and Stablecoins 1:07:10 Genius Act and New Stablecoins 1:07:43 Stablecoin as a Micropayment 1:11:23 Pump and Streaming 1:14:53 Apps to Watch 1:17:12 Stablecoin Growth 1:19:11 Stablecoin Startups in Different Regions 1:20:05 Novel Ideas for Startups 1:24:03 Wen Cycle Top? Link ↓

Good Game

52,911 views • 11 months ago

🚨 we’re back with the superteam india podcast! we’ve all heard of prediction markets but how do prediction markets with precision look like? on the first episode back, this episode of the superteam india podcast, Harkirat Singh sits down with Anam, blockchain engineer at Trepa — a precision prediction market built on solana (Colosseum hackathon winners by the way) where you don’t just bet yes or no, you predict exact numbers and get rewarded based on accuracy. we go deep into the technical architecture: why they store predictions in logs instead of on-chain, how rpc providers can silently truncate your program logs at 12kb, the emit cpi fix that saved them, why they rebuilt v1 from scratch over missing reserved bytes in their pdas, and the real cost challenges of sponsoring gas fees for a consumer app on solana. ⏱️ timestamps: 00:00 - cold open 00:38 - intro & guest welcome 01:08 - anam’s journey: mlh fellow → solana foundation → helius → trepa 03:04 - working at solana foundation & helius 04:20 - what are precision prediction markets? 05:03 - trepa vs polymarket: how payouts work 06:05 - the three factors: accuracy, stake & time 06:56 - what if no one else joins the pool? 08:09 - liquidity & market making challenges 09:17 - how prediction precision & steps work 10:37 - why they rebuilt v1 → v2 (reserved bytes) 12:28 - onchain storage optimization & rent reclaim 13:39 - security audit with adware labs 15:12 - the 12kb rpc log truncation discovery 15:59 - emit cpi fix: storing data as instruction data 16:33 - on-chain vs off-chain architecture deep dive 17:17 - why trepa sponsors gas (and the cost implications) 20:45 - top open source solana contracts to learn from 22:12 - what’s next: flash pools (2-minute prediction cycles) 23:38 - team size & hiring at trepa 25:50 - advice for aspiring solana smart contract devs 27:10 - outro
27:20

🚨 we’re back with the superteam india podcast! we’ve all heard of prediction markets but how do prediction markets with precision look like? on the first episode back, this episode of the superteam india podcast, Harkirat Singh sits down with Anam, blockchain engineer at Trepa — a precision prediction market built on solana (Colosseum hackathon winners by the way) where you don’t just bet yes or no, you predict exact numbers and get rewarded based on accuracy. we go deep into the technical architecture: why they store predictions in logs instead of on-chain, how rpc providers can silently truncate your program logs at 12kb, the emit cpi fix that saved them, why they rebuilt v1 from scratch over missing reserved bytes in their pdas, and the real cost challenges of sponsoring gas fees for a consumer app on solana. ⏱️ timestamps: 00:00 - cold open 00:38 - intro & guest welcome 01:08 - anam’s journey: mlh fellow → solana foundation → helius → trepa 03:04 - working at solana foundation & helius 04:20 - what are precision prediction markets? 05:03 - trepa vs polymarket: how payouts work 06:05 - the three factors: accuracy, stake & time 06:56 - what if no one else joins the pool? 08:09 - liquidity & market making challenges 09:17 - how prediction precision & steps work 10:37 - why they rebuilt v1 → v2 (reserved bytes) 12:28 - onchain storage optimization & rent reclaim 13:39 - security audit with adware labs 15:12 - the 12kb rpc log truncation discovery 15:59 - emit cpi fix: storing data as instruction data 16:33 - on-chain vs off-chain architecture deep dive 17:17 - why trepa sponsors gas (and the cost implications) 20:45 - top open source solana contracts to learn from 22:12 - what’s next: flash pools (2-minute prediction cycles) 23:38 - team size & hiring at trepa 25:50 - advice for aspiring solana smart contract devs 27:10 - outro

Superteam India

12,312 views • 6 months ago

E159: Hyperliquid: Housing all of Finance jeff.hl came back on the When Shift Happens Podcast to talk about the Hyperliquid journey since the TGE and what the future holds for one of the most loved and prolific protocols in the space Hyperliquid Timestamps 0:00 Intro 2:01 Singapore 2:27 Reminiscing on the Token Launch 5:00 Was This Scale Of Wealth Expected? 6:28 Doing The Right Thing In Crypto 9:07 The Responsibility that comes with Billions of $ 11:10 Jupiter KAST 11:51 Bringing Hyperliquid to the masses 15:21 Pre TGE and Post TGE: Operational difference 20:13 Choices on what to build Internally vs Externally 22:05 How to build a reliable team 24:51 Did the Team celebrate the HYPE wealth Generation event? 26:45 How to test talents for High Integrity 28:31 How much does the Hyperliquid team sleep? 30:05 Employee Vesting Fears 31:41 Dealing with FUD 32:28 How Does Jeff Personally Handle FUD 35:02 Token "Buybacks" critics 37:20 Why Hyperliquid can't have Discretionary "Buybacks" 39:04 HyperEVM, explained Simply 40:00 Paradex Zodl 40:41 HyperEVM: Success so Far? 44:05 HIP-3, explained Simply 47:44 What makes Hyperliquid's approach different 48:19 Why Should People Care? 51:33 Bring All Finance On Chain 52:08 Why Is The Hyperliquid Approach Better? 53:47 Key Numbers showing that Hyperliquid Is Doing it right 59:01 What Has the Unit team demonstrated with spot trading on Hyperliquid in 2025 1:03:29 HIP-4: Outcome Markets 1:08:01 Trezor Sui 1:08:58 What does "Housing All Of Finance" mean? 1:10:51 Why Hyperliquid is not a crypto company 1:12:23 Why Does Hyperliquid have A Stablecoin USDH (Native Markets) 1:14:39 What Is Kinetiq & Why Does It Matter? 1:16:15 Why Is What HyperLend Is Building Important For HyperLiquid 1:23:39 Where did Fairness cost the most? 1:24:47 What should Hyperliquid be Remembered for? 1:25:24 Why should people stay in Crypto when there's an AI brain drain? 1:28:10 Closing Thoughts
1:29:06

E159: Hyperliquid: Housing all of Finance jeff.hl came back on the When Shift Happens Podcast to talk about the Hyperliquid journey since the TGE and what the future holds for one of the most loved and prolific protocols in the space Hyperliquid Timestamps 0:00 Intro 2:01 Singapore 2:27 Reminiscing on the Token Launch 5:00 Was This Scale Of Wealth Expected? 6:28 Doing The Right Thing In Crypto 9:07 The Responsibility that comes with Billions of $ 11:10 Jupiter KAST 11:51 Bringing Hyperliquid to the masses 15:21 Pre TGE and Post TGE: Operational difference 20:13 Choices on what to build Internally vs Externally 22:05 How to build a reliable team 24:51 Did the Team celebrate the HYPE wealth Generation event? 26:45 How to test talents for High Integrity 28:31 How much does the Hyperliquid team sleep? 30:05 Employee Vesting Fears 31:41 Dealing with FUD 32:28 How Does Jeff Personally Handle FUD 35:02 Token "Buybacks" critics 37:20 Why Hyperliquid can't have Discretionary "Buybacks" 39:04 HyperEVM, explained Simply 40:00 Paradex Zodl 40:41 HyperEVM: Success so Far? 44:05 HIP-3, explained Simply 47:44 What makes Hyperliquid's approach different 48:19 Why Should People Care? 51:33 Bring All Finance On Chain 52:08 Why Is The Hyperliquid Approach Better? 53:47 Key Numbers showing that Hyperliquid Is Doing it right 59:01 What Has the Unit team demonstrated with spot trading on Hyperliquid in 2025 1:03:29 HIP-4: Outcome Markets 1:08:01 Trezor Sui 1:08:58 What does "Housing All Of Finance" mean? 1:10:51 Why Hyperliquid is not a crypto company 1:12:23 Why Does Hyperliquid have A Stablecoin USDH (Native Markets) 1:14:39 What Is Kinetiq & Why Does It Matter? 1:16:15 Why Is What HyperLend Is Building Important For HyperLiquid 1:23:39 Where did Fairness cost the most? 1:24:47 What should Hyperliquid be Remembered for? 1:25:24 Why should people stay in Crypto when there's an AI brain drain? 1:28:10 Closing Thoughts

MR SHIFT 🦁

582,834 views • 6 months ago

And now for something (almost) completely different. Welcome to Out of Scope, a new sub-series of Validated where Austin Federa | 🇺🇸 and Tori Pastore, aka Chairman Birb Bernanke, aka Birb, riff with guests on hot takes so off-topic you’ll forget this is typically a blockchain-centric podcast. In this debut episode, they sit down with Austin Campbell to discuss what some might call too many subjects for one hour. Running stablecoin reserves, repealing the 17th Amendment, why some banks resemble cartels, market structure, why regulators should be paid more and held to higher standards, modernizing the BSA, and (most importantly) a definitive ranking of video conferencing tools. Timestamps: ↓ 00:00 - Introducing Tori (as if you don’t know her) 01:24 - Chinese Peptides Explained 02:45 - GLP 1 Hype Cycle 05:40 - Peptides and Food Science 10:49 - Enter Austin Campbell 16:11- Stablecoin Reserve Rules 20:35 - Gold Doom Scenarios 22:59 - Banks' Payment Monopoly 34:38 - AI Lobbying and EA critiques 38:20 - Prediction Markets Incentives 43:59 - Fixing Regulator Accountability 47:39 - More on Prediction Markets 48:47 - Market Manipulation Debate 59:54 - Perps Versus Futures 01:02:51 - Assassination Markets Debate 01:06:21 - Austin's Magic Wand Reforms 01:10:40 - Blooper Reel
1:12:03

And now for something (almost) completely different. Welcome to Out of Scope, a new sub-series of Validated where Austin Federa | 🇺🇸 and Tori Pastore, aka Chairman Birb Bernanke, aka Birb, riff with guests on hot takes so off-topic you’ll forget this is typically a blockchain-centric podcast. In this debut episode, they sit down with Austin Campbell to discuss what some might call too many subjects for one hour. Running stablecoin reserves, repealing the 17th Amendment, why some banks resemble cartels, market structure, why regulators should be paid more and held to higher standards, modernizing the BSA, and (most importantly) a definitive ranking of video conferencing tools. Timestamps: ↓ 00:00 - Introducing Tori (as if you don’t know her) 01:24 - Chinese Peptides Explained 02:45 - GLP 1 Hype Cycle 05:40 - Peptides and Food Science 10:49 - Enter Austin Campbell 16:11- Stablecoin Reserve Rules 20:35 - Gold Doom Scenarios 22:59 - Banks' Payment Monopoly 34:38 - AI Lobbying and EA critiques 38:20 - Prediction Markets Incentives 43:59 - Fixing Regulator Accountability 47:39 - More on Prediction Markets 48:47 - Market Manipulation Debate 59:54 - Perps Versus Futures 01:02:51 - Assassination Markets Debate 01:06:21 - Austin's Magic Wand Reforms 01:10:40 - Blooper Reel

Validated

13,701 views • 2 months ago