Supercell's Project Paradox: long-horizon agents need experiments, not just prompts
AI Engineer · youtube · 2026-09-27
In an AI Engineer video, former Microsoft/Supercell engineer Erina Karati presents Project Paradox, built with Arunachalam Manikandan at Supercell's AI Innovation Lab — a framework giving game agents memory, emotions, and trust scores.
The problem: it worked in short scenes but broke down over long horizons. A rumor about a mango sale degrades as it spreads — agents forget who said it and turn "might" into fact.
The fix: an autoresearch loop
- Run controlled scenarios (spreading a fact, a rumor, a plan change) and collect traces.
- Score results on a balanced scorecard: reach, source retention, uncertainty preservation, replanning, and privacy.
- The loop may only edit a small, frozen policy surface, and changes are kept only if the scorecard improves.
Lessons beyond games
- Memory alone isn't enough — you must know where each fact came from.
- Rollback isn't optional.
- Long-horizon agents need experimental loops, not just prompt tweaks.
The video includes full demos (a picnic scenario, the fixed rumor) with timestamps.
More from coding & agent
- Sydney Codex Community Buildathon set for Nov 14 with Cerebras-backed ultrafast compute track — paw_lean · 2026-11-11
- shadcn's improve hits 10k stars: let top models plan, cheap models execute code fixes — shadcn · 2026-11-11
- OpenAI open-sources Codex Security CLI and SDK for AI-driven vulnerability scanning and fixing — openai · 2026-11-11
- Claude Opus 5.5 runs an architecture search and finds AttnRes-Canon, a new top Transformer design — SonglinYang4 · 2026-11-11
- 5 research habits worth knowing: read papers backwards, reproduce first, wire coding agents via MCP — cneuralnetwork · 2026-11-11
- 'Adam can now do CAE': AI agent showcase in engineering simulation draws buzz — burhop · 2026-11-11