Market Mechanics
Internal Markets vs. Public Markets
The prediction market landscape is currently dominated by "Public Markets" such as Polymarket or Kalshi, which focus on high-entropy global events like presidential elections or interest rate cuts. While valuable, these markets often lack relevance to specific crypto communities.
CogniFi introduces Internal Prediction Markets. These are hyper-localized markets tied specifically to the performance and roadmap of the token itself.
The Distinction:
Public Markets: "Who will win the US Election?" (Low relevance to a specific meme coin).
Internal Markets: "Will the $COGNI market cap exceed $50M by Friday?" or "Will the Agent deploy the v2 roadmap before February?"
Strategic Utility: Internal markets solve the "Dead Curve" problem by providing a secondary layer of engagement. When price action is flat (sideways), volatility in the prediction of future events can still generate yield for traders and fees for the protocol. It effectively monetizes community sentiment and insider knowledge.
The "Optimistic Oracle" Resolution Pattern
To resolve markets without a centralized authority, CogniFi employs an Optimistic Oracle mechanism, similar to UMA Protocol but optimized for Solana's sub-second block times.
The Resolution Lifecycle:
Assertion: When a market expires, the AI Agent (running in a TEE) scans the data sources and asserts an outcome (e.g., "YES, Market Cap > $50M").
Challenge Window: A distinct time period (e.g., 2 hours) begins. During this time, any user can dispute the Agent's assertion by posting a bond in $COGNI tokens.
Settlement:
No Dispute: If the timer runs out with no dispute, the outcome is finalized, and payouts are enabled.
Dispute Raised: The market enters arbitration. $COGNI token holders vote on the correct outcome. The winner takes the loser's bond.
This system assumes honesty is the default state (Optimistic) to maximize speed, while retaining a cryptoeconomic security net.
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