Atlassian's Tamar Yehoshua explains what the AI builder era looks like for product managers in a company of more than 10,000 people. Using Confluence, RovoClaw, and Jira as examples, she covers when PMs should write code and prototypes, when they should steer the team instead, and how Atlassian is building AI fluency in its PM organization.
This video explores how James Martin's 1991 Rapid Application Development (RAD) methodology, with its emphasis on rapid prototyping, iterative development, and user feedback, offers a robust framework for contemporary AI coding and "vibe coding" workflows. It highlights how AI agents accelerate prototyping but introduces new challenges regarding production readiness and security. The solution proposed is spec-driven development, where human expertise formalizes requirements and verifies AI-generated code based on insights gained from early prototypes, ensuring quality and mitigating risks.
A developer-focused, demo-heavy session on rapid AI prototyping using the Google DeepMind stack. It covers how to leverage the full capabilities of AI Studio, from video analysis and code execution with Gemini 3.1 Flash, to building full-stack applications with databases, and exploring the frontiers of generative media with Genie 3, Veo 3.1 Lite, and Lyria 3.
Founders Alex and Teddy of Magic Patterns discuss their journey from numerous pivots to building a profitable, $1M ARR AI design tool with a two-person team. They share insights on finding product-market fit by focusing on customer obsession, the technical details of their prompt-to-prototype platform, and their experience in YC.
Astro Teller, Ivy Ross, and Isabelle Olsson recount the journey of creating Google Glass. They delve into the human-centered design philosophy, the innovative 'Explorer Program' as a public learning platform, the unexpected social and technical challenges, and the crucial lessons learned about timing and innovation in launching moonshot technologies.