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Stop Prompting, Start Loop Engineering: Build Self-Iterating AI Agent Systems
The script explains why “loop engineering” is replacing manual prompting: instead of iterating with an AI yourself, you define what “done” looks like, let an agent act, and use an independent judge model to verify results and repeat until the goal is met. It cites industry figures and examples (including Anthropic and NVIDIA’s GTC keynote) to argue that better loops, not better prompts, will power future self-iterating agent systems. The speaker describes a doer/judge loop structure and shows four implementations inside an “agent operating system”: a Fusion loop with configurable rounds and separate builder/judge models, an agent Kanban board with planner/builder/reviewer roles, a Fusion “boardroom” combining multiple model outputs via a judge, and a Sakana/Fugu council approach. It also describes an Obsidian-based memory system and promotes the AI Profit Boardroom community and resources.
00:00 Why Loops Beat Prompts
00:48 What Loop Engineering Means
03:39 Prompting vs Looping
04:44 Doer and Judge Framework
05:37 Fusion Loop Walkthrough
06:26 Agent Kanban Loops
07:21 Fusion Boardroom Method
08:31 Sakana Fugu Council
09:05 Agent OS Bundle Overview
10:01 Memory Feedback Loop
11:26 Getting Started and Proof
12:01 Join the Community
12:35 Final Wrap Up
The script explains why “loop engineering” is replacing manual prompting: instead of iterating with an AI yourself, you define what “done” looks like, let an agent act, and use an independent judge model to verify results and repeat until the goal is met. It cites industry figures and examples (including Anthropic and NVIDIA’s GTC keynote) to argue that better loops, not better prompts, will power future self-iterating agent systems. The speaker describes a doer/judge loop structure and shows four implementations inside an “agent operating system”: a Fusion loop with configurable rounds and separate builder/judge models, an agent Kanban board with planner/builder/reviewer roles, a Fusion “boardroom” combining multiple model outputs via a judge, and a Sakana/Fugu council approach. It also describes an Obsidian-based memory system and promotes the AI Profit Boardroom community and resources.
00:00 Why Loops Beat Prompts
00:48 What Loop Engineering Means
03:39 Prompting vs Looping
04:44 Doer and Judge Framework
05:37 Fusion Loop Walkthrough
06:26 Agent Kanban Loops
07:21 Fusion Boardroom Method
08:31 Sakana Fugu Council
09:05 Agent OS Bundle Overview
10:01 Memory Feedback Loop
11:26 Getting Started and Proof
12:01 Join the Community
12:35 Final Wrap Up
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