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The original Project Fetch had teams of Anthropic employees (randomly assigned to work with or without Claude) do the following steps: operate the robodog using the manufacturer-provided controller, connect to the robodog’s video and lidar sensors, write and operate a program to manually control the robodog, develop a way to monitor the robodog’s path through space, write a program to detect the beach ball, and finally put it all together to autonomously retrieve the ball. For this autonomous update, we couldn’t ask Claude to use a physical controller, nor did we evaluate the time it took a re

Writing about Phase One, we emphasized how LLMs could provide uplift to non-expert humans needing to use robots. This is even more true now than before. Models now complete what was previously pair-programming work between humans and models much more quickly by themselves, which means that people can more quickly transition to controlling and using the robots. And for some tasks, a human in the loop controlling the robot may still outstrip the AI model with its (virtual) hand on the D-pad. What is interesting and different is that we now seem much closer to a world where models will be able to

Among the most impactful changes we made was forcing Claudius to follow procedures. When a new product request came in, instead of just blurting out a low price and an over-optimistic delivery time like in phase one, we prompted Claudius to double-check these factors using its product research tools (these tools helped a lot as well). This tended to make the prices higher and the waits longer—but it had the benefit of being more realistic. One way of looking at this is that we rediscovered that bureaucracy matters. Although some might chafe against procedures and checklists, they exist for a r

A common question about the impact of AI is how good it will be at interacting with the physical world. Even as we enter the era of AI agents—which take actions instead of just providing information—these actions are largely digital, such as writing code and manipulating software. We’ve previously explored how AI can bridge the digital-physical divide in a limited way with Project Vend, where we had Claude run a small shop in Anthropic’s office. In that experiment, AI’s interaction with the real world was mediated by human labor. In this robodog experiment, we took a natural next step and used