Can Real Podcasters Beat the Prediction Market Algorithm? скачать в хорошем качестве

Can Real Podcasters Beat the Prediction Market Algorithm?

Can we use AI combined with podcasts to predict what happens next in prediction markets? I built an end-to-end pipeline using PodSips and Polymarket to find out. From concept to working app in about 2 hours using Claude Code. In this video, I use PodSips (a semantic search engine for podcast transcripts across 100+ shows) to identify emerging trends from expert podcast discussions, then cross-reference those signals against active Polymarket prediction markets. The goal: find mispriced markets where podcast experts see something the market hasn't priced in yet. I build a paper trading simulator with a $1,000 budget, a live dashboard with Google Stitch, and set up autonomous hourly scanning, all with Claude Code and AI agent teams working in parallel. == Timestamps == 0:00 - Intro & the idea 1:12 - What is PodSips? 2:15 - What is Polymarket? 3:30 - Setting up the project with Claude Code 5:45 - Installing the PodSips skill 8:20 - Market-first vs podcast-first strategy 11:00 - Finding overlap between podcasts and markets 14:30 - Building the cross-referencing pipeline 18:00 - Running the first scan (42 matches!) 20:45 - Paper trading simulator setup 24:00 - The AI agent self-corrects its logic 26:30 - Designing the dashboard with Google Stitch 29:00 - Live dashboard demo & first trade 31:30 - Setting up autonomous scanning 33:00 - Wrap-up & what's next == Tools Used == PodSips: https://developer.podsips.com/ Polymarket: https://polymarket.com Claude Code: https://claude.ai/code Google Stitch: https://stitch.withgoogle.com/ Subscribe if you like building weird, experimental apps with AI — more updates on this project coming soon.