This Friday, our Co-Founder and CEO @claberus joins HOC & Frens: RWAs, AI & The Next Capital Market. He opens the day on the panel "The Next Capital Market: What Does It Look Like?" at 12:00 UTC, alongside @glider__, @securitize and @ProprXYZ, moderated by @Mantle_Official.

Prediction market war intensifies in Kentucky… regulation battle expanding fast 📊⚖️

Cboe launches a prediction market suite with binary options today. Regulated forecasting platforms merge with decentralized market models. Swap noncustodially to manage your portfolio securely. Trade directly on chain. #DeFi #Swap

$WORLDCUP is extremely over sold, peak fear and disinterest in the narrative is abundant right now. But check the chart and the flows: • RSI showing a bullish divergence • Volume weak on this second breakdown • Whales have net bought $26K over the past 7 days of mundane PA Looking like an excellent R/R bid right here again. The narrative doesn’t care about CTs emotions. It was hot before the World Cup began, it’ll be hot again when the finals come around. Track whale flows like this with Sun Flow in the replies👇

I built PULSE today. A live FIFA Worldcup Ai trading desk.. I have named it PULSE Monitors live match. streaming whale positions and trades in real time.. One screen, one live match at a time. Every number on the dashboard is a real on-chain position you can verify yourself in 30 seconds.. This isn't a betting tool. It's a complete trading desk. ▫️ 4 sections i have added for now 1) Live Match. The current highest-volume live game with moving odds, the biggest bet on each side, and a live tape tagging every trade as a whale buy, an accumulation, a repeat buyer, or a side flip. 2) World Cup Whales. The biggest real money in the tournament, ranked by position size. Every whale, every team, every dollar at risk. 3) Arbitrage. Flags any 3-way moneyline where the prices add up to less than 100¢. That's a free edge. 4) All Matches. Every fixture in one list with a model edge for the upcoming ones. Live games hide the pre-match number because once the ball is rolling, that number is dead. ▫️Now, How i built it ? - Polymarket's public APIs for markets, holders, and positions. WebSocket feed for the live tape… - Python backend. Main loop picks the focus match every cycle and rewrites a JSON file the dashboard reads in real time. - The AI Read runs on Claude Haiku. Hard-instructed to never invent a number, predict a winner, or talk profit. If the AI goes offline, it falls back to a deterministic templated read. Never blank. Never made up.. ▫️ What it's actually for ? Reading a market that was always public but never readable.. Seeing where the size is sitting. Catching arbitrage gaps before they close. And Watching which whale flipped sides right after a goal and what they're holding now.. etc etc

Unpopular prediction: The next big India Silicon Valley crossover could be Elon Musk backing Zerodha and Nikhil Kamath leading X. Bookmark 🔖 this post.

Well there ya go. Everyone is doing prediction markets

The hardest part of a prediction market is not predicting the future. It is agreeing on what actually happened. Take Polymarket. A market like “Will company X launch product Y before December 31?” sounds binary until reality gives you a private beta, a limited regional release, a product rename, or an announcement with no usable product. A normal smart contract can distribute funds after receiving YES or NO, but it cannot read all that evidence and decide what “launched” really means. This is where @GenLayer could supercharge prediction markets. An Intelligent Contract could read the market rules, examine real-world sources, and ask multiple validators running different AI models to evaluate the outcome independently. They would need to reach consensus, with disagreement and appeals handled by the network rather than trusting one company or one AI model to make the final call. To me, the real opportunity is not resolving more obvious markets about scores or election results. It is safely creating markets around questions that require interpretation: whether a roadmap milestone was genuinely delivered, whether a policy took effect, whether research met its stated criteria, or whether an AI agent completed a task as agreed. Polymarket showed that people want markets on real-world events. GenLayer could help expand what “resolvable” means when the real world refuses to give us a clean YES or NO

If you’d bet on a draw in this match, you could have made a tidy profit. But it was incredibly difficult to predict the outcome of a match like this🙂