Loops, Goals, and Token Bonfires

00:00 Introduction and Context of Fable Five Release 01:55 Unpacking the Fable Five Experience 03:16 Political Implications and AI Development 05:36 Comparative Analysis of Fable and Opus Models 08:09 User Experience and Model Selection 08:25 Cost Considerations in AI Usage 10:46 Conclusion and Future of AI Models 15:54 Exploring New AI Workflows 18:43 Understanding Loops and Goals in AI 21:01 The Power of Workflows in AI Development 23:55 Pros and Cons of AI Autonomy 27:10 Navigating AI's Limitations and Challenges 31:03 Building Trust in AI Tools 33:56 Innovative vs. Maintenance Tasks in AI Episode 12: Loops, Goals, and Token Bonfires Justin and Kellan are back from a stretch of client workshops to break down the strangest model launch yet — Fable Five, which shipped and got pulled inside of three days — and what it says about how you actually choose a model. Then they get into the vocabulary everyone's suddenly using: loops, goals, and workflows, and when each one is worth it. The Drip: Fable Five ships, gets jailbroken in a government demo, and is pulled three days later The irony of the pullback landing right after Dario's case for slowing AI down What three days with the model actually felt like — faster, fewer mistakes, less fake agreement Inside The Bottle: Model choice as a binary: just using AI vs. building agentic AI into software Why unit cost (price per token) matters less than the cost to achieve the objective A plain-English glossary: loops, goals, workflows, ultra plan, ultra code When workflows earn their keep — and when loops turn into a token bonfire Knowing whether you're in maintenance mode or invention mode before you automate New episodes every Wednesday. Subscribe to The Weekly Fizz newsletter at http://tinybottleai.com/the-fizz. Music licensed through Soundstripe. Code: LII7KUZSSCAEILJT