Are Everyone a Prophet? The Democratization Wave and Practical Boundaries of Prediction Markets | MyToken AMA Recap

Meme is receding, and the prediction market is taking over. From 2023 to 2026, transitioning from experimental stages to becoming a core tool on Wall Street, the nature of capital has changed, and the underlying logic of participation has also evolved. When a market shifts from being questioned to gradually accepted, what kind of turning points does it experience? Where do opportunities for ordinary investors lie?

Recently, the well-known crypto data platform MyToken held a high-quality online seminar centered on prediction markets. As an early industry data aggregation platform founded in 2017, MyToken has established deep collaborations with over 300 centralized and decentralized exchanges and more than 1,000 project teams during the bull and bear cycles. This event gathered experienced practitioners from prediction project teams, exchanges, and top communities to analyze the democratization wave and practical boundaries of prediction markets.

Prediction Markets: From “Information Casinos” to “Social Prophets” – An Upgrade in Perception

At the start of the event, the participants first clarified a key misconception: prediction markets are not high-level gambling.

Peng Song, an early advocate of Dogecoin and promoter of the decentralized prediction market gougoubi_ai, pointed out that betting rules are fixed, only concerned with winning or losing, and can be manipulated; whereas prediction markets have variable rules, with the core being “concerned with the truth,” and outcomes can be disputed and governed. He believes that a mature decentralized prediction market’s governance resembles a micro-social system and is a prototype for social governance in the AI era.

Aoohaoo (Ahao), a representative of the Luffy community, offered a more practical perspective: “It standardizes our offline ‘bragging and betting’ scenarios. You vote with real money on opinions like ‘Can Trump win re-election?’—this is more authentic than any opinion poll.”

Crzaymath, head of the KTX exchange Japan market, added that traditional gambling involves users betting against house operators, while prediction markets are mostly P2P battles among users, with the platform only charging fees. He emphasized the “positive energy” attribute of prediction markets, which can be seen as real-world “information discoverers” or personal risk hedging tools.

Regarding how prediction markets are moving from the fringe to the mainstream, Crzaymath shared key observations. He believes that clear regulatory compliance is a crucial turning point. Taking the example of the prediction platform Kalshi winning a lawsuit against the U.S. Commodity Futures Trading Commission (CFTC), he pointed out that this laid the foundation for the legal operation of prediction markets in the U.S., moving them from the gray area into mainstream visibility.

Trends and Challenges: How Can Professionalization and Democratization Coexist?

Where there is value, capital follows. As prediction markets become more professional, arbitrage opportunities shrink. During the process of professionalization, can prediction markets still maintain their original intention of harnessing collective wisdom? Do ordinary users still have opportunities? How should they participate?

Ahao believes that ordinary users can participate in multiple ways: first, seize early-stage opportunities and potential platforms during the initial window; second, place bets based on their own cognition; third, deeply participate in community governance and development.

Peng Song and Dogbit (Yogenfun Chinese community ambassador for prediction platforms) both believe that professionalism and collective wisdom are not contradictory. Professional teams are responsible for providing liquidity, ensuring technical security and compliance, acting as the “infrastructure” of the market; while the broad user base contributes dispersed information, inspiration, and partial truths, serving as the “content providers” of the market. Both complement each other and together form the market’s vitality.

Insider Trading Debate: Efficiency vs. Fairness – An Eternal Topic

In financial markets, everyone hates insider trading, but in prediction markets, it seems insiders are seen as catalysts. If someone holds inside information and gathers trades, is that good or bad for the market? When the discussion delves into market ethics, an interesting divide emerges regarding “insider information.”

Ahao clearly opposes insider trading, equating it to “match-fixing,” which damages market fairness and ultimately harms the entire sector. He supports regulation through legislation.

Peng Song offers a different perspective from a decentralized viewpoint. He believes that in on-chain environments, “insider trading” can help reveal truths faster and promote the progress of real-world events. The key is to ensure “power symmetry”—information can be asymmetric, but the decision-making authority must be jointly held by the community to prevent single entities from manipulating results.

Dogbit emphasizes efficiency, arguing that pursuing real and rapid price discovery is the lifeline of prediction markets. Fairness should be defined as equal opportunity and data transparency, not equal outcomes.

The Ultimate Clash of Technical Approaches: AMM Mode vs. Order Book Mode

The most tense part of the discussion occurred between two prediction project builders. When the topic shifted to technical implementation paths, Peng Song and Dogbit engaged in a direct confrontation over efficiency and decentralization.

Peng Song advocates for the AMM (Automated Market Maker) model. He argues that the future of prediction markets lies in high decentralization and permissionless creation, similar to Uniswap, providing open liquidity pools for thousands of prediction events. “There are countless daily global events, and centralized order book servers cannot support this long tail and explosive ecosystem.”

Dogbit sharply questions the on-chain AMM model. Starting from user experience, he emphasizes the performance advantages of the order book model in high-concurrency scenarios. “When major events occur, congestion and high Gas fees on-chain can instantly ruin trading experience. Prediction markets need to react to market sentiment in real-time, and performance bottlenecks are a matter of life and death.”

This debate transcends mere technical choices, touching on the core contradiction in the crypto world: should we prioritize the pursuit of complete decentralization ideals, or focus on ensuring a commercial-grade user experience? Different paths may lead the entire sector toward very different futures.

Consensus and Future: Prediction Markets as the Value Anchor of Web3 Infrastructure

Despite disagreements over technical routes, all guests agree on the enormous potential of prediction markets. They are evolving from a financial tool into a new infrastructure connecting the real world with the crypto community. Whether it’s Peng Song’s advocacy for open protocols empowering all tokens, or Dogbit’s promotion of proprietary platforms providing staking scenarios for Memecoin, they are exploring practical value and new traffic entry points for the Web3 world.

Key Takeaways (Summary)

Value Reassessment: Prediction markets have completed a cognitive upgrade, redefining their core as information markets that utilize collective funds for probability discovery, rather than gambling.

Governance Core: The true challenge and appeal lie in building governance systems capable of effectively resolving disputes and balancing efficiency with fairness—more complex than the trading mechanisms themselves.

Path Divergence: The industry faces fundamental technical divergence: the AMM camp pursues extreme decentralization and ecosystem openness, while the order book camp emphasizes trading performance and user experience. This showdown will define the ultimate form of the market.

Ecosystem Confirmation: Regardless of the technical route, prediction markets have established their strategic position as “core infrastructure for empowering Web3 community value,” providing key practical scenarios for assets.