HomeTechnologyGoogle spent 1 year on a task, Claude Code did it in 1 hour, says Google engineer

Google spent 1 year on a task, Claude Code did it in 1 hour, says Google engineer

A Google engineer revealed that Claude Code solved in one hour a coding task Google teams had been working on for a year. Her viral post has sparked fresh debate on AI coding speed and innovation.

January 04, 2026 / 21:22 IST
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Snapshot AI
  • Google engineer: Anthropic's Claude Code equaled a year's work in one hour
  • Claude Code built a multi-agent AI system from a brief public prompt
  • AI coding tools now rebuild entire codebases, far outpacing expectations

Imagine spending one year building something at work, with meetings, whiteboards, debates, snacks, and more meetings. Now imagine a rival shows up and does almost the same thing in one hour. That’s basically the story Google engineer Jaana Dogan accidentally dropped on the internet, and of course, it exploded.

Dogan, a principal engineer working on Google’s Gemini API, recently tested Anthropic’s Claude Code, an AI tool that helps write and organise code. She fed it a problem her team had been wrestling with for a year. The result? Claude delivered something shockingly close to Google’s work in 60 minutes. Dogan posted on X saying, “I’m not joking and this isn’t funny. We have been trying to build this since last year. I gave Claude a description, and it generated what we built last year in an hour.”

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To make things clearer for the non-Google crowd: the task was about building systems that manage multiple AI agents working together. Think of it like traffic control, but for AI bots instead of cars. Google had tried many ideas, but the team still hadn’t agreed on a final design. Dogan wanted to test Claude without using Google’s private data, so she created a simplified version of the problem using public ideas. Her prompt was just three short paragraphs. No secret sauce. Just curiosity and three paragraphs.

She admitted Claude’s answer isn’t perfect and still needs polish, but she encouraged people who doubt AI coding tools to test them on problems they already understand deeply. Because that’s where the shock value really hits.