Stanford CS146S: How always-on agents work

So, as mentioned, I'm Lee. We're going to talk a little bit today about how this new category of always-on, proactive, persistent agents work and kind of give you some of the understandings of the building blocks for how these are made. Um just as a, you know, fun statement up here, some of the things we'll talk about are in

progress we're working on at SpaceX. Um and in week one, you all built this very kind of simple harness that helps you understand the core idea, which is that you have a model, it can call tools in a loop, and that's actually very powerful. It unlocks a lot of new capabilities for the models.

Um but, it does come with some drawbacks. Notably, you close your laptop and the process stops. It's no longer running. Uh and I want to talk about how you can take this simple idea, it's very powerful for how to get more out of models, and extend it to this new type of agent, which is an always-on agent.

So, rather than just running in your terminal, this can run on server. It can run in the cloud. You can close your computer. Uh it can restart. It can survive crashes, for example. This agent has its own computer. So, not just your laptop, but a Linux machine in the cloud where it has its own desktop,

files, browser, and more. Maybe some 3D apps. Um it can save files on the machine. It can understand more about your progress over time and build up a memory of how you work with it. Um unlike a harness in the terminal that is responding to every message that you send, this type of always-on agent is

more like a colleague where it doesn't always immediately send you a message. It knows when to be quiet. Sometimes it might just want to work in the background a little bit and only come back to you when there's an important update. Uh and it can be triggered more than just you typing. So, it's not just