The Rise of Always-On Assistants
The always-on AI personal assistant, which keeps working in the background even when you aren’t asking it to, is this year’s answer to the question of how people will actually use deep learning models.
OpenAI released dots, its assistant offering, at its developer day. Alexander Embiricos, who leads OpenAI’s enterprise product team, explained where the product came from—starting with the question of why so many companies are turning to cutesy mascots as avatars for complex models.
“There’s kind of this convergent evolution happening,” Embiricos said of the efforts to build AI assistants. “As we were working on the product, we realized if we could frame this as, it’s an entity and it’s a single conversation, not many different conversations….it starts to become intuitive.”
The assistant is available in the ChatGPT desktop and mobile apps to subscribers on the Pro tier or higher, with plans starting at $100 a month. Once it is connected to your calendar, email, computer and other tools, the agent tries to help you get your work done.
Embiricos points out that you could achieve much of dots’ functionality with OpenAI’s coding tools, but that requires more work and hand-holding. He recalled celebrating when his wife started leaving her computer on all night so that her agents could keep working.
“On the product team, what I think about is, how do we make this intuitive and useful to people?” he told attendees. “A lot of that isn’t building some new piece of tech into the product; it’s how you frame it to the user and how it feels.”
Evolution of the Agent
Making the technology feel intuitive meant repackaging the functionality of the company’s models into something more accessible, a path it was already on as it spun out features from the agentic coding tools it had built for software engineers.
The idea of a persistent agent is that it doesn’t need prompting. For OpenAI, this means more token usage, and for users, a more proactive assistant that anticipates needs and thinks about how to help.
Testing shows the assistant’s ability to think ahead is apparent and often useful, though timing can sometimes be an issue when flagging conflicts or deadlines.
“The first time it told me about one of those conflicts, it told me three minutes before the thing,” Embiricos says of his dot. “It’s like, ‘Hey, this thing is coming up. You might want to do something about it.’ I only have three minutes!”
Embiricos expects the timing to improve over time, noting instances where agents successfully detected and analyzed outages or issues before human engineers noticed them.
Privacy and Data Access
As with most AI agent use cases, there is a tension between the personal information an AI model needs to be useful and the exact amount of personal data exposed to a software company.
“Yes, we have a thing that we built into dots, which we call proactive research,” Embiricos said. “On a cadence, it will think about what it knows about you, what is the conversation that it’s had, and then what have you given it access to that it can think about, and then it will go and research, ‘What could I do to be more helpful to you?’ And then, basically, it will propose that.”
Other market entrants differentiate themselves by explicitly stating they do not collect data to fuel advertising businesses.
With dots, OpenAI says the agent shares the same privacy controls as ChatGPT, allowing users to turn off model training. However, some controls lack granularity, and the application requires careful permission management.
“What I think we need to do is basically build out super, super, super granular controls,” Embiricos said, pointing to the model’s intelligence and discretion as balancing factors.
“We had really conservative defaults over what the agent would do, and it would ask for permission a lot. I remember knowing that we were going to see that feedback, but thinking, ‘This is okay, we can tune that over time.’”
Scaling and Infrastructure
Another major question surrounding AI agents is whether they can successfully scale across businesses and general communication channels without friction.
If the AI industry is right that agents represent the future, the integration must occur without overwhelming existing infrastructure across businesses, websites, and payment networks.
“At OpenAI…we’re not always moving the fastest in terms of shipping the next ability for the agent to work with the world,” Embiricos said. “When we do, we’re doing it really closely in collaboration with the rest of the ecosystem. We’re deep in lots of conversations with payment processors.”
Allowing an AI assistant to spend money through payment partnerships would mark a significant shift, requiring robust consumer trust alongside existing inbox and scheduling access.
