Google Developer: Building Gemini's coding capabilities

Author: Google for Developers - Bewertung: 41x - Views:364

Connie Fan, Product Lead for Gemini's coding capabilities, and Danny Tarlo, 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



Subscribe to Google for Developers → https://goo.gle/developers



Speaker: Logan Kilpatrick, Connie Fan, Danny Tarlow

Products Mentioned: Google AI, Gemini