I agree with this! Infofi, perps, AI agents and pms are closely related together,they form a vertical stack rather than a loose set of related narratives each layer consumes the output of the one below it and produces a more structured, capitalised form of the same underlying thing which is priced attention > InfoFi is the raw attention and information layer, this may include: mindshare scores, social signals, data markets, and reputation systems that turn scattered trends and claims into measurable flows > AI agents sit on top of that layer as the processing layer. agents read the InfoFi feeds, cross-reference other data, and convert noisy attention into structured intelligence, probability estimates, theses, or ranked signals. the agent's main role in the stack is not to invent the information; instead it compresses and operationalises what the InfoFi layer has already made visible > Prediction markets are the pricing and commitment layer. they take the intelligence produced by agents (or humans) and force it into a continuous probability. once capital is at risk, the forecast stops being an opinion and becomes a market price that other systems can read. > Perps are the expression and leverage layer. they let that priced forecast be traded with size, direction, and continuous funding rather than binary settlement of prediction markets basically, each layer exists to turn the previous layer’s output into something that can be risked and settled

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MetaMask's Predict tab has routed about $323M in Polymarket volume, and users never leave the wallet. Prediction markets have a new distribution layer, and it isn't the venues. It's the apps people already use 🧵

MetaMask's Predict tab has routed about $323M in Polymarket volume, and users never leave the wallet. Prediction markets have a new distribution layer, and it isn't the venues. It's the apps people already use 🧵

First weekend of live @NBA markets on PRED. Raptors vs Heat tips off Saturday at 7:00 PM ET, followed by Sunday's double-header. Best odds all season. With zero fees. Get in early. 👇 @Raptors @MiamiHEAT @warriors @LAClippers @utahjazz @nuggets

What’s weird is seeing takes on why things are the way they are in markets, and what that means, often with a complete absence of first principles when it comes to PMs. “Prediction market traders want…” If you assessed PMs in 2017-19 you could’ve concluded “people don’t want them.” Now it’s “people only care about price”, “they’ll only trade on…” Wait a second, half a decade ago we barely had retail scale for event contracts. We’ve had almost no time to discover what people actually want to trade, or how. Financial products don’t arrive fully formed around pre-existing preferences. People build things, experiment, firms find new ways to abstract, transfer and speculate on risk, users respond, new use cases emerge etc. Futures, options, perps etc all evolved through different paths. There isn’t one predetermined user, use case or product form. PMs are incredibly early. Treating what people trade today as some fixed expression of what they want from them seems completely backwards.

Everyone wants to build the 1inch of prediction markets. But 1inch worked because one token is the same on every venue. Prediction market contracts aren't. Here's what it actually takes to build the aggregation and routing layer

Everyone wants to build the 1inch of prediction markets. But 1inch worked because one token is the same on every venue. Prediction market contracts aren't. Here's what it actually takes to build the aggregation and routing layer

If you’re building anything in the prediction market space and looking to raise funds, one of the most important questions you need to answer is “what makes my product harder to replicate” It doesn’t matter if what you’re building is a venue, terminal, an agentic layer or an SDK your product could be an aggregator, a router.., but you need to have an answer for that question what makes your product harder to replicate? this will help you identify your moat

Looked into polymarket's data on @DefiLlama and the numbers were so all over the place, the reason was because I didn't quite understand the difference between a prediction market Dex volume, OI and Notional volume. so I had to restart the learning process all over again to understand it better and I'll be sharing it with you as well. join me for a 3 minute read 🧵