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My Decoder guest today is Hayden Field, The Verge’s senior AI reporter, and we’re discussing the new wave of consumer-friendly AI agents. If you’ve been paying attention to this space, you know AI enthusiasts have been using agents for a minute now — homebrew OpenClaw setups led to a surge in Mac Mini sales earlier this year. But the launch of Meta’s Muse, OpenAI’s Dots, and xAI’s Grok bot has brought easy to use agents to millions. Muse and Dots have had the highest-profile product launches, and they’re fascinating to pit against each other. Both Meta and OpenAI have decided to pitch these agents to mainstream users and businesses in the form of cute, animated mascots. Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get your podcasts. Head here. Not a subscriber? You can sign up here. These can do everything from the boring — restaurant reservations and inbox triage — to more sophisticated tasks. In OpenAI’s cases, the company is even offering “specialist” Dots for marketing, legal work, and accounting. Muse, notably, is free, while Dots are not. So you’ll hear Hayden and me get into why Meta, which still doesn’t have a frontier model of its own, might have a meaningful edge here because it’s so much better at making and distributing consumer products. There’s also a huge Decoder-style tension wrapped up in the agent race: a conversation about what AI is good at today, what it still can’t do, and then the privacy and security implications of handing over your credit card information, your email inbox, and other sensitive hard drive data to an AI that might be able to do things for you without every requiring an app or a phone in your hand. That might be the future of all computing, but it’s not at all clear if most people want to hand over the data to make it happen. Okay: The Verge’s Hayden Field on Muse, Dots, and trusting AI agents. Here we go. This interview has been lightly edited for length and clarity. Hayden Field, you’re the senior AI reporter here at The Verge. Welcome back to Decoder. Thanks so much. I’m excited to talk to you. This time there isn’t any wild interpersonal drama. No one’s feelings have been hurt. I would say Elon Musk tried to hurt some feelings and didn’t get there. Alexandr Wang from Meta has maybe been taking some shots, but none of the Real Housewives stuff we usually end up talking about when you’re on the show. It’s been a bit of a pause in the soap opera antics for now, which I’m really grateful for. Yeah, just some good old-fashioned product competition in the marketplace. Let’s see who wins and loses, and maybe everything will kill us all in the end. But, for now, cute mascots. There’s a lot going on. Let’s start at the start. Hayden, you were at OpenAI DevDay in San Francisco. The company announced Dots, which is their new agent platform with a cute mascot. That happened just a few weeks after Meta Connect, at which the company was all in on Muse, their agent platform with an adorable mascot. Tell us about the state of the industry right now. Everyone’s very excited about agents. What’s going on? It’s funny to me because I’ve been covering agents for so long. I remember that in 2022, it was the year of ideation — that’s what tech leaders called it, referring to agents. They were just ideating. They were thinking about what it could look like. There were a lot of references to Jarvis from the Marvel Universe. They called 2023 the year of deployment: “Let’s try things, let’s deploy and learn more about what’s failing.” Which meant pretty much all of them were failing at the time. Then we had 2024 and 2025. They didn’t have any names for those years, but agents were still pretty bad, as we saw. 2026 seems, to me, like the year of the beginnings of actually useful AI agents for the consumer, like always-on autonomous agents. Obviously, OpenAI was the start of all of this. But what’s interesting to me is that one man, Peter Steinberger, was able to create an actually useful AI agent for the consumer with OpenClaw — an always-on tool, despite its privacy flaws. It had a lot of privacy and security issues. But it was an agent that was useful enough that people still wanted to use it anyway and try to find ways around these privacy issues that it was having. That inspired these companies to say, “If one man can do this over the course of one weekend, we’ve really been slacking. We have to get it together.” OpenAI hired that guy, and now we have Dots. Meta, of course, was working on its own version of this and put it out sooner with Muse. They’re basically both always-on, autonomous AI agents that these companies are peddling as a way to be your personal assistant in a lot of ways. The idea is to use them for booking flights, booking dinner reservations, buying gifts for people, but not only that. Some of them, Dots in particular, are kind of going further to be your work personal assistant and we’ll get into that in a minute. But this is where OpenAI and Meta are warring right now. They’re trying to present these two AI agents as a little bit different from each other, even though they’re essentially the same. Just broadly speaking, to define some terms, we’re gonna keep saying “agent,” and what we mean here is an AI model wrapped in a harness that lets it use a computer. Right. The way that I describe AI agents usually is an AI tool that can complete multi-step complex tasks on your behalf without you hand-holding it the whole time. I was a personal assistant in one of my first jobs in New York, so I would’ve gotten fired if every time my boss asked me to book a flight for her, I said, “What time? Also, what’s your SkyMiles number? Also, what’s your loyalty number again, for this other thing? Oh, do you want me to try to get you first class?” They want you to have common sense and just book the flight. This is what they’re pitching these AI agents as — things that can work on their own mental kind of scratchpad in the background and not ask you every single time there’s a step. They can complete multi-step processes in the background, doing their own reasoning, and then present you with a completed task. That’s the big idea. Just to say it clearly, both Muse and Dots come out of the OpenClaw lineage, which is a technical approach to building an agent, right? There are a lot of different ways you might be able to accomplish “It’ll remember your SkyMiles number and book you a flight.” But the way everyone’s going at it now is the idea of a harness around a model. That was the big innovation in OpenClaw, and the computer OpenClaw was using was often your own Mac Mini on your own network using a wide-open browser with your own data, which is where a lot of their security problems came from. It’s the same model with Muse, only it’s a little Linux computer that Meta’s giving you in the cloud. It’s the same model with Dots, although the way ChatGPT is set up with Codex is very complicated, and that computer could be in a lot of different places. But this notion that what you really need is a computer with a browser and some harness is gonna direct a model to do a bunch of stuff for you using that computer, that’s what we’ve landed on today, and it just seems to be the default winning model. Right. Are all of these things just riffs on OpenClaw? Are they the same as OpenClaw? You could say that. They’re different technically. Meta keeps saying, “We did build this from scratch, but it was inspired by OpenClaw.” There are a lot of similarities there, but they did say that they built it from scratch. Then, of course, OpenAI hired the creator of OpenClaw, so there’s probably a lot of similarities there as well for Dots. The reason I wanted to stay there for one second is that I think it’s important to identify the fundamental technical approach that is happening with these agents, because there’s a lot of different ways it could have gone, and the whole industry has picked this approach. What you need is a web browser, a harness, and a model that can go use that web browser. What’s really interesting to me is that Meta has done a really good job on top of that fundamental model of making a cute consumer product. Meta is good at consumer products. Obviously, Instagram and Facebook and the rest are undeniably good consumer products. People really like them. For all of Meta’s failings in VR, I always thought the Meta Quest has been a great consumer product. You take it out of the box, it helps you use it, you can have fun with it right away. Whereas Dots seems like it’s kind of made for software engineers, but you can also plan a wedding in it. I’m wondering if that’s how you see it. That one is an enterprise product with a little consumer gloss on it, and then Meta obviously is just a dead-ahead consumer product. What’s different here is that OpenAI needs money a lot more than Meta needs money. The products are honestly pretty similar, it seems like. The difference is that OpenAI is marketing it to be an enterprise-friendly product a lot more than Meta is. Muse is just a consumer-facing product. Meta is happy with that. The goal is to make Muse as easy to use as humanly possible. One-tap downloading, just putting it in your face literally everywhere. Even when I went to my Instagram profile the other day, there was a pop-up for using Muse. They’re trying to make it free, accessible, and super easy to broaden the audience. They want anyone to be able to just use it with one click and get used to it. They’re trying to flood the market with AI agents and make it normal and have their own ChatGPT moment, if you will, for AI agents. They want Muse to be that. Now, with OpenAI, they’re still marketing it as a consumer-facing product. When you’re using ChatGPT, if you have the right subscription, it’s right there. It says, “Use your Dot to do this, that, and the other.” They really want you to go for it as a consumer, as long as you’re paying. This is for their $100 to $200 a month subscription tier, unlike Meta. That’s why there’s a huge difference here. For OpenAI, it seems like they don’t have the money to just front-load all of this and say, “Use it for free. No problem. We’ll catch up with you later.” OpenAI wants this to be a money-making product, and that’s why they’re marketing it to the enterprise. They talked a lot about privacy to try to set it apart from Meta’s Muse. They talked a lot about what you could do with this as a knowledge worker, whether you worked in marketing, graphic design, software engineering, product, and tons of different industries. They gave examples of how you could use this as an assistant, as a coworker. Sam Altman even referred to it as like a “chief of staff.” He didn’t want it to be just an assistant. He wanted it to be your chief of staff. Something else that I thought was interesting is that Sam Altman seemed to subtly dig at Meta on stage a few times during DevDay. One of the times he said, “Look, I don’t want this to be just something that’s used to book flights or plan things with friends and look at your calendar. I want this to go beyond that and to really do knowledge worker tasks, things that you in your industry would need a niche assistant to perform.” That’s why they also introduced specialist Dots that are good at marketing, legal analysis, and things like that. They’re really going for the enterprise angle here, but I think it’s also because they need money ahead of their IPO, obviously. Yeah, the revenue piece — that it’s only for paid customers at their higher tiers — is really interesting. OpenAI’s tiers are very confusing, but it’s $100 and up, and that’s just going to keep a lot of people from using Dots at first. The flip side of that is OpenAI does have a lot of customers who are paying them a lot of money, and if they can get those customers to start using Dots, then those customers [truncated for AI cost control]