The AI-Native PM: Tools, Tactics, and Workflows for the Next Era of Product

Across 90 minutes, we’ll dive into hands-on exercises that teach you how to design reliable, explainable, and efficient AI workflows without needing to write a single line of code. You’ll learn how to craft complex prompts that hold up under real-world variability — from metadata prompting and multi-turn collaboration to prompt chaining and token-efficient design. We’ll explore the mechanics of deep research with AI — including where it breaks, how to avoid bias traps, and how to validate insights before they mislead your roadmap.

Then we’ll move into applied workflow automation for non-technical PMs — using AI to capture messy requirements, translate them into n8n automations, and scaffold early LangGraph prototypes. We’ll also unpack the “FAT” (Familiarity, Autonomy, Trust) framework for phased AI integration and look at how GenAI workflows differ fundamentally from traditional ML pipelines.

You’ll get a peek at emerging methods like “LLM-as-a-judge,” learn lesser-known API parameters that can make or break performance, and close with the essential skill set every AI-native product manager will need to stay relevant — from data-informed strategy and competitive research to rapid validation and AI collaboration.