Connie Fan, Product Lead for Gemini's coding capabilities, and Danny Tarlow, Research Lead for Gemini's coding capabilities, join host Logan Kilpatrick for an in-depth discussion on how the team built one of the world's leading AI coding models. Learn more about the early goals that shaped Gemini's approach to code, the rise of 'vibe coding' and its impact on development, strategies for tackling large codebases with long context and agents, and the future of programming languages in the age of AI.Watch on YouTube: ⁠https://www.youtube.com/watch?v=jwbG_m-X-gE⁠Chapters:0:00 - Intro1:10 - Defining Early Coding Goals6:23 - Ingredients of a Great Coding Model9:28 - Adapting to Developer Workflows11:40 - The Rise of Vibe Coding14:43 - Code as a Reasoning Tool17:20 - Code as a Universal Solver20:47 - Evaluating Coding Models24:30 - Leveraging Internal Googler Feedback26:52 - Winning Over AI Skeptics28:04 - Performance Across Programming Languages33:05 - The Future of Programming Languages36:16 - Strategies for Large Codebases41:06 - Hill Climbing New Benchmarks42:46 - Short-Term Improvements44:42 - Model Style and Taste47:43 - 2.5 Pro’s Breakthrough51:06 - Early AI Coding Experiences56:19 - Specialist vs. Generalist Models⁠⁠ 

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