Ready to build your own AI prototyping sandbox with AI Studio and Google Cloud? Check out this codelab → https://goo.gle/4ylGxOw Building a cool AI prototype over a cup of coffee is easier than ever. But inside a massive enterprise, vibe coding quickly hits a wall of infrastructure, data compliance, and security guardrails. In fact, only 5% of AI prototypes ever make it to production. So how does a billion-user platform like YouTube move fast without breaking things? In the premiere episode of Emergent, Stephanie goes into the engineering trenches with AI leaders to break down YouTube’s Prototyping Stack to show how they ship AI features fast and safely. Learn how to shift your mindset, embrace throw-away code, and build a sandbox that lets your team fail safely at hyper-speed. Chapters: 0:00 — Why 95% of AI apps fail in production 0:37 — The developer risk vs. speed dilemma 2:34 — The invisible friction of vibe coding 4:41 — YouTube's billion user blast radius 6:55 — The blank canvas prototyping trap 7:53 — Inside YouTube's AI prototyping stack 9:18 — Embracing throwaway code 10:19 — Democratizing prototyping at Google scale 11:46 — Becoming an architect of safety Subscribe to Google Cloud Tech for more deep dives into cloud architecture and AI dev workflows → https://goo.gle/GoogleCloudTech #GoogleCloud #GoogleAIStudio #Vibecoding Speakers: Stephanie Wong, Addy Osmani, Benji Bear Products Mentioned: Google AI Studio, Google Cloud