Space is another dev day feature from OpenAI, where the company is creating its own ecosystem for workflows, combining its Dots agentic system with a digital drive where documents and projects can live.

“Space is a home for your pages, uploaded files, and other work in ChatGPT,” spokespersons write. “You can create and edit pages with ChatGPT, organize related content in spaces, and share your work to collaborate with other people.”

Space, which is available in Pro, Business, and Enterprise editions, replaces “Library” in prior models; it also competes with Google drive. In addition, OpenAI has engineered “Pages” which are editable documents that humans or agents can take and change. These would be the equivalent of Google docs.

That’s interesting, to me at least, in that lots of people use Google docs now. So presumably, you’ll be able to use some kind of API process to port a Google doc into Pages and vice versa.

Here’s the thing: if humans are going to be managing swarms of their own Dots, as I wrote about yesterday, Space will be the corral where everybody coordinates, where the human orchestrates, and where all of the “stuff” is. OpenAI has said they are planning to add functionality for items like PowerPoint-style presentations later.

In other words, Space will be the digital real estate for the Dots, which are their own autonomous little actors. Dots are built with their own operating systems, browsers, etc. as each one is the sole inhabitant of its own virtual machine. Space will be their greater home, their neighborhood, if you will. That is, if it’s this branded ecosystem that takes off, as opposed to some other one.

So how good is Space, compared to some other shared human/agent workspaces?

Well, it’s brand new, so it’s hard to say. But I did find this input from Evan Brooks at Ones.com , which included recommendations for Github, Replit, and others.

“A shared agent workspace should not force you to choose between fast implementation and disciplined delivery,” Brooks writes. “It should connect agents with requirements, tasks, knowledge, repositories, reviews, and approval points, while keeping people in control. In this guide, I compare the leading options by shared project context, developer workflow fit, human-agent collaboration, visibility, and governance. You will see which platform suits coordinated software delivery, which works best for individual coding help, and where autonomous implementation needs stronger boundaries.”

The longer terms here, “shared project context” and “developer workflow fit,” seem made of what precedes them, and what follows. “Shared project context” basically just means co-locating the relevant files. “Developer workflow fit” just sounds like techspeak par excellence.

Anyway, there’s also Buzz, pioneered by block.xyz in June.

“Over the past two years, we’ve built and open sourced a series of AI tools at Block,” spokespersons wrote . “Through all of it, we’ve come to the realization that the most productive work doesn’t happen when someone asks AI for help. It happens when humans and agents are in the same room, working on the same thing, with shared context. There was no one platform designed for that, so we built one.”

Maybe then there wasn’t. But this idea is now part of the fabric of our tech world, as we see the agents ascendant, at work and elsewhere.

And then there was this from Google , in May:

“At Google I/O, we introduced a unified development toolkit featuring Antigravity 2.0 and the Managed Agents API, giving developers better ways to build locally and deploy securely to the cloud on a shared protocol layer,” wrote Addy Osmani, Director at Google Cloud AI, and Alan Blount, Product Manager at Google Cloud. “In this blog, we’re going to show you how Gemini Enterprise Agent Platform and the new developer tools shared at I/O fit together, unpack the spectrum of choice for building, and share what we’d actually try first.”

There’s that API approach, and an appeal to whether the platform will deliver a good developer workflow fit.

The bottom line is that the agents are coming, and the companies are rolling out the red carpet, partly by building these havens for seamless human/AI collabs. We ain’t seen nothin yet.