Google’s Gemini Team Breaks Down How AI Writes Code, And Where It's Headed Next

Google dropped a fresh episode of its AI: Release Notes podcast, and this one spotlights Gemini’s coding skills. Logan Kilpatrick sat down with Connie Fan and Danny Tarlow, the product and research leads behind Gemini’s programming model, to break down how they built one of the top AI tools for code.

From the start, the team had a clear goal: make Gemini useful for developers without turning it into a black box. Instead of chasing flashy demos, they focused on code quality, testability, and real-world use cases. That approach paid off, Gemini now supports multiple programming languages and can handle tasks from bug fixes to writing entire functions.

A standout moment in the discussion came when Tarlow brought up “vibe coding.” It’s a way to describe the growing shift from writing code line-by-line to prompting an AI with a feeling or intention. This trend signals a major shift in how future developers, or even non-developers, might build software.

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Fan added that while Gemini handles plenty of autocomplete tasks, the next frontier lies in collaborating with users during problem-solving. “You don’t just want the answer,” she said. “You want the process to be understandable.”

You can hear the full conversation now on Apple Podcasts or Spotify by searching for Google AI: Release Notes. Whether you code for a living or just want to understand what AI means for the future of software, this episode gives a clear, inside look, without the buzzwords.

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