Google's robotic AI agent breakthrough

Edition 123 | September 29, 2025

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Welcome back to Building AI Agents, your biweekly guide to everything new in the field of agentic AI!

Google just made a huge step towards a robotic future with its release of two state-of-the-art visual models for controlling real-world agents.

In today’s issue…

• Google launches cutting-edge models for robots

• OpenAI teases the release of powerful new agents

• How to deploy agents in real businesses

• Google’s guide to building production-ready agents

• A free agent-powered app builder

…and more

🔍 SPOTLIGHT

The image people get in their head when they first hear the phrase “AI agent” is often a robot like C-3PO or the Terminator, but that impression is misleading. That might be about to change.

One question I occasionally get from Building AI Agents readers is why our graphics sometimes show AI agents as humanoid robots—typing at a computer, being yelled at by a boss, or something like that. The truth is that I don’t like illustrating agents that way, because it’s a bit deceptive: the agents this newsletter is about are virtual ones that run entirely on a computer and perform tasks in the digital world, without having a physical form.

Why do I do it then? Basically, because it’s hard to convey the image of virtual agents doing work or screwing up without giving them a physical embodiment. I assume our readers are a smart bunch who figure out pretty easily that the “robots” I show are metaphorical. Until recently, actual robots have lagged far behind virtual agents in their ability to do economically useful tasks.

Which brings me to the big news. Google closed this gap significantly with a breakthrough in robotic agents: the release of the Gemini Robotics 1.5 and Gemini Robotics-ER 1.5 models last Thursday.

The (somewhat confusingly named) pair are, respectively, a vision-language-action (VLA) model and a vision-language model (VLM). Robotics-ER 1.5, the VLM, acts as a high-level reasoner, figuring out how a robot should break down a given task, like deciding which of a given set of items the it should put in a compost or trash bin. Then, it gives the resulting set of instructions to Robotics 1.5, the VLA, which decides and carries out the sequence of actions necessary to complete the task. On an aggregate of 15 academic benchmarks for robotic reasoning, ER 1.5 achieves state-of-the-art performance, beating OpenAI’s cutting-edge GPT-5.

Currently, the models are open only to selected “trusted testers” picked from a waitlist, but if there’s one thing that the last few years of AI advances have shown us, it’s that capabilities which are closed-source today will be open-source very soon. It may not be long before the situation with robotics is similar to that with large language models and the virtual AI agents they power—rapid advances, widely-available open-source technology letting anyone build their own, and capabilities that were previously limited to science fiction quickly becoming a reality.

For now, the most advanced agents still exist only in the digital world, but those days are looking to be numbered. If you see me having to put [metaphorical] and [real] on the heads of the robots in this newsletter, you’ll know robotic AI agents’ time has come.

Always keep learning and building!

—Michael

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