Release Notes: Building Gemini's coding capabilities

From the creator

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. Listen to this podcast: Apple Podcasts → https://goo.gle/3Bm7QzQ Spotify → https://goo.gle/3ZL3ADl Chapters: 0:00 - Intro 1:10 - Defining Early Coding Goals 6:23 - Ingredients of a Great Coding Model 9:28 - Adapting to Developer Workflows 11:40 - The Rise of Vibe Coding 14:43 - Code as a Reasoning Tool 17:20 - Code as a Universal Solver 20:47 - Evaluating Coding Models 24:30 - Leveraging Internal Googler Feedback 26:52 - Winning Over AI Skeptics 28:04 - Performance Across Programming Languages 33:05 - The Future of Programming Languages 36:16 - Strategies for Large Codebases 41:06 - Hill Climbing New Benchmarks 42:46 - Short-Term Improvements 44:42 - Model Style and Taste 47:43 - 2.5 Pro’s Breakthrough 51:06 - Early AI Coding Experiences 56:19 - Specialist vs. Generalist Models Watch more Release Notes → https://goo.gle/4njokfg Subscribe to Google for Developers → https://goo.gle/developers Speaker: Logan Kilpatrick, Connie Fan, Danny Tarlow Products Mentioned: Google AI

Published 2025-06-16 · Watch on YouTube ↗
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