Summary
This video launches a recurring head-to-head series pitting Claude Opus 5 against GPT-5.6 on real-world prediction market events sourced from Polymarket. The first episode covers two live markets: the lowest temperature recorded in Seoul on July 29th and the number of rate cuts at the July Fed meeting. What makes the setup methodologically interesting is the scaffolding built around it — the host uses SER API to give both models identical, structured JSON access to web search results, deliberately obfuscates market share prices to prevent the models from anchoring on crowd sentiment, and requires each model to output a full probability distribution across all possible outcomes rather than a single binary pick.
The video walks through the technical implementation in detail: how events are auto-selected by resolving within a three-day window, how the cache is cleared between model runs to prevent cross-contamination, and why SER API was chosen over the native web search tools built into Claude Code and Codex (consistent structured output and a level playing field for local models). The host sets the thinking level to “high” for both models to normalize inference effort.
For AI practitioners interested in evaluating model reasoning under uncertainty — particularly on questions with quantifiable ground truth and no obvious training-data answers — the scaffolding described here is reproducible and the series promises ongoing results tracking. The episode also serves as a practical introduction to SER API as an agent research tool.
📺 Source: All About AI · Published July 29, 2026
🏷️ Format: Benchmark Test
