.@poetiq_ai is a new startup founded by former DeepMind researchers (@itfische & @sbpoetiq) that recently achieved a major jump on the ARC-AGI benchmark by layering a recursive self-improvement system on top of Gemini 3. In this conversation at NeurIPS, @FrancoisChauba1 sat down with Poetiq co-founder Ian Fischer to find out how they're increasing performance using prompts and system design alone. They also explore recursive self-improvement, benchmarking progress toward AGI, and why automating prompt engineering may be one of the most powerful levers in AI today. 00:11 — Introducing Poetiq and the ARC-AGI Breakthrough 00:49 — How Big Is the Performance Jump? 01:18 — Ian Fisher’s Background: YC, Google, DeepMind 02:00 — Recursive Self-Improvement Explained 03:00 — Why Poetiq Targeted ARC-AGI 03:58 — Improving Models Without Access to Weights 04:26 — Ensembles, Voting, and System-Level Optimization 05:30 — Why Gemini 3 Changed Everything 06:21 — What’s Next: Benchmarks, Research, and Customers 07:14 — Is Recursive Self-Improvement a Path to AGI? 08:46 — When to Stop Hill-Climbing 09:16 — Automating Prompt Engineers and Agents