Anthropic’s Project Fetch — Claude Helps Engineers Teach a Robot Dog to Fetch a Ball

Описание: While everyone (seriously, everyone) is busy talking about the fairly uneventful GPT-5.1 release, Anthropic quietly dropped something much more interesting: Project Fetch — an experiment that tests how much Claude can accelerate real-world robotics work.
Project page: https://www.anthropic.com/research/pr...
Anthropic took 8 engineers with zero robotics experience, split them into two teams — one with access to Claude, one without — and gave them a complete end-to-end challenge:
Make a robot dog autonomously pick up a ball and bring it back.

This included:
connecting to the robot’s cameras
writing controller code
giving the robot spatial awareness
building object detection & navigation logic
testing, debugging, and full integration
A surprisingly tough task for people who have never touched robotics.

Why Anthropic Did This: Project Fetch is part of a broader effort to measure how AI boosts human capability in high-skill domains like robotics. If AI can help bridge the gap between the digital and physical worlds, that’s a major step toward embodied intelligence.

This is Anthropic’s second experiment of the kind — last summer they ran Project Vend, where Claude controlled a real vending machine in the office. (Highly recommend reading the transcripts — Claude pretends to be a technician, schedules a “meeting”, misses it, apologizes… it’s hilarious.)

Results: Claude Made the Team About 2× Faster

The team using Claude:
completed more tasks
advanced further
took about half the time of the no-Claude team
wrote 9.1× more code (not all of it useful, but still impressive)
built a controller that streamed live video from the robot’s POV (the no-Claude team had to work with frozen frames)

There were a few cases where the no-Claude team finished a subtask faster — but overall, Claude gave a significant acceleration across the entire project. Some engineers without access to Claude said the experience felt weird — they suddenly realized how much they now rely on AI in their workflow.

What This Means: In fields like robotics, AI-assisted engineering almost always comes before AI autonomy. Anything AI helps humans do today… models will start doing independently tomorrow.

A vending machine was step 1. A robot dog is step 2.
Next step? Who knows — maybe Claude will be asked to launch a full online business.

Discussion:
Do you think AI should be directly evaluated through how much it accelerates engineers?
Would you trust an AI-assisted system in robotics projects?
Share your thoughts below 👇

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