Just one more AI experiment.

There’s always one more thing to try. Dara and Matthew compare the promise of AI assistants with their own experiments in making them useful. They talk through agents, Paperclip, cloud environments, model routing and T3 Code, alongside subscription limits, context handovers and the temptation to keep tinkering. When does one quick test become a fragile system, and when is it time to stop? Plus the odd tangent, an experiment graveyard and a fizz update. Recorded 5 October 2026. Product availability, model names and limits reflect the conversation at recording. Watch: https://youtu.be/aiq6JmURXrY Chapters: 00:00 Show intro 00:15 Episode 2 and the name 01:11 Planning the episode and grinding axes 03:17 Dots, regional rollouts and the promised assistant 10:19 Coding AI and everyday knowledge work 15:57 Keeping up with AI news 17:23 Compaction, models and subscription limits 28:51 Clear answers and human oversight 36:33 Predicting the next AI releases 41:14 Always-on agents and the practical fallback 01:00:34 Multiple providers, CLIProxyAPI and T3 Code 01:05:46 Local models and routing 01:09:42 Context and handovers between providers 01:13:47 Tinkering and the experiment graveyard 01:17:26 The fizz reading and Ziggy 01:20:34 Outro Resources discussed: - Paperclip: https://github.com/paperclipai/paperclip - OpenClaw: https://openclaw.ai/ - T3 Code: https://github.com/pingdotgg/t3code - CLIProxyAPI: https://github.com/router-for-me/CLIProxyAPI - OpenCode: https://opencode.ai/ - OpenRouter: https://openrouter.ai/ Production: AI-generated intro voice and theme music.