Ponder is a daily prediction game where users earn cash rewards by guessing what everyone else will choose. Built on the Keynesian beauty-contest concept, players stake between $0.50 and $10 to predict collective sentiment on simple polls that stay open for 24 hours. Success depends on reading group intuition, not luck, and winners share the pool proportionally.

Votes remain hidden for the whole 24-hour period to prevent herd behavior, ensuring each participant relies on independent judgment. A machine-learning trust-scoring system guards against collusion and bots by dynamically re-weighting suspicious clusters while protecting legitimate players.

The platform is natively integrated into Farcaster as a Mini-App with instant USDC rewards on Base, requiring no gas fees or manual claims. Users can also create their own polls and earn a percentage of rewards.

Ponder transforms casual prediction into a game that actually rewards deep understanding of crowd psychology. The platform generates meaningful engagement while maintaining integrity through sophisticated anti-manipulation technology.

As a backend and AI engineer, I architected and built backend Node.js and Python services for real-time poll management, rewards distribution on Base, notification delivery, and ETL. I integrated machine-learning systems for trust scoring and bot detection. I also deployed AI agents across Farcaster and the Base App, utilizing LangChain, to enable users to interact with the product directly in the social feed and in direct messages.

Ponder scaled to 30,000+ active users, generated $250,000+ in total volume, and distributed $10,000+ in creator rewards within its first months on Farcaster.