Policast enables anyone to participate in decentralized prediction markets. Users can bet on outcomes using ERC20 tokens, view real-time analytics, and share their stats with personalised images. The platform is designed for extensibility, security, and seamless integration with Farcaster and other social protocols.

Prediction markets existing platforms face several issues:

❌ Lack of transparency — Traditional betting and prediction platforms often rely on centralized operators who control liquidity, odds, and payouts.

❌ High barriers to entry — Many require KYC, fiat onboarding, and trust in custodial accounts, excluding global users.

❌ Poor community interaction — Existing markets often feel transactional, with little social context or discussion around predictions.

❌ Limited accessibility — Sharing performance or engaging socially with predictions is fragmented across multiple apps.

How Policast Makes It Easier & Safer

✅ Onchain Transparency
All market creation, trading, and resolution happens on Ethereum L2 (Base), ensuring fairness and trustless execution.

✅ Community-Driven Insights
Built-in comment threads, likes, and discussions turn markets into knowledge hubs, not just betting venues.

✅ Real-Time Analytics
Users can access live price charts, trade volumes, and market sentiment, making decisions safer and more data-driven.

✅ Social Integration with Farcaster
Predictions and stats can be shared directly in social feeds and mini-app frames, amplifying reach and enabling social accountability.

✅ Portable & Open-Source
Anyone can fork, extend, or deploy their own version thanks to its MIT license and modular architecture.

Building Policast came with several technical hurdles:

⚙️ Comment System & Personalized Frames
Setting up a full comment system with Supabase and generating personalized Satori frames for user stats was complex. Handling dynamic images while keeping them fast and lightweight required several iterations.

🖥️ Heavy Next.js Project Testing
Running everything locally was resource-intensive. To reduce load on my PC, I often deployed preview builds online just to test features in real conditions. This slowed down iteration but ensured stability.

🔗 Batch Transactions with Farcaster Wallet
While batch transactions worked smoothly with MetaMask and base app, they repeatedly failed on Farcaster Wallet — only one transaction in the batch would succeed. It took a lot of debugging before I finally got it working by leveraging wagmi’s sendCalls method.

👉 Each challenge forced me to optimize, debug deeply, and adapt, ultimately making the project more robust and production-ready.

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