AI PM - From Doing Tasks to Designing Loops

Join us for an evening focused on closed loops, the operating model behind AI-native companies, and the significant shift in how product work is accomplished. 🤖

A closed loop is a concept from control theory: act, measure the outcome, feed it back, and improve the next run. This approach transforms your role from executing tasks to designing loops — where an agent performs the work, verifies results against goals, learns from outcomes, and iterates. Your job evolves to setting goals, quality standards, and feedback mechanisms that enhance each iteration. 🔄

What Closed Loops Offer:

• Compounding Output: Each run generates feedback, leading to continuous quality improvement.
• Real Leverage: One person can design and oversee multiple loops running simultaneously.
• Queryable Organization: Work flowing through loops is captured, measurable, and improvable.

Trends We’re Seeing:

• Y Combinator’s AI-native playbook: AI as the core operating system, with all key processes in intelligent closed loops.
• Boris Cherny, creator of Claude Code, focuses on writing loops and supervising fleets of agents that iterate until goals are achieved.
• Loops triggering loops: agents activated by schedules, webhooks, and other agents, rather than human intervention.
• Mistakes transformed into memory: corrections embedded into lasting instructions and skills to prevent repeated errors.
• Progress measured in loops and tokens, not by headcount or hours.

Live Demo:

We’ll demonstrate how to implement your first product loops in an AI-native workspace — defining goals, delegating tasks, and closing the feedback loop.

Come ready to learn, share, and leave with actionable loops to build! 🚀

Agenda:

• ⏰ Doors Open · 16:40
• 👋 Welcome & Introduction · 17:00
• 🤖 Talk & Demo: Designing Product Loops · 17:10
• 🎉 Wrap-up & Networking · 18:30
• 🚪 Close Doors · 19:00
• 🥙 Optional After Event Drinks and Food?