Robert Ta and Jonathan examine Instinct, a $2.5 billion AI agent that promises to handle shopping, reservations, and email across your devices. It's saved users $550 but also cost one person $64, and its memory works like a Git-backed wiki that learns your preferences. They map the competitive landscape: Meta's Muse leads app stores, but Amazon blocks agents from buying, while Shopify and Expedia let them in.
Instinct is a personal assistant that understands what you're working on and what's important to you, connects to your applications and devices, email, messaging, screen, audio, location, and more. The interface is simple. There are no interfaces. It's trained to use a phone and a computer. You could text or call it. It uses its device in the same way that humans do. Instinct's core model is trained to understand and handle the deeply personal nuances of everyday life, following up on threads you've dropped, proactively calling or texting you, Arranging a ride to the airport, booking a handyman for your apartment, and much more. Get started. This is pretty cool. Like a pretty cool way to onboard people is just text them, like text the model or the product. So Instinct, hang on, is this really their website?
Yeah, dude. $10 billion landing page.
This is insane. This is their landing page. Are you serious? That's wild. So real quick, Instinct's founder says the viral AI agent's hallucination could spit out what it looks like a stranger's data.
There was a security issue.
Yeah. Lots of personal AI agent horror stories. I'm just like going off of the top on here. I think I found an AI agent worth the risk. Instinct saved me $550, booked my restaurant reservation, and warned me about a phishing scam. It also wasted $64 and might be a security nightmare. This is from Wired. You could read more about it here, but it looks like a $2.5 billion valuation company. And it more speaks to this thing I wanted Jonathan's take on, which is we're seeing Muse come out from Meta. That's number 1 on the app stores last I checked this week. We're seeing GrokBot come out. That was just most recently, I think, top 3 on the app store before Muse came out. And now we're seeing these other startups kind of fighting for wedges and beachheads. Such as Instinct for the personalized AI agent game. We're also seeing incumbents in this market, if we can call it that, where it's such an emerging market that started with OpenCLAW and then fast followed by, you know, like IronCLAW or Hermes agents that tried to solve for this form factor. And now we're seeing some of these bigger companies and more well-funded startups like Instinct go after this personalized agent beachhead. So I'm kind of curious, Jonathan, from your founder lens, what are your thoughts on personalized agents and this like B2C focus that we're seeing come out of Facebook, come out of SpaceX AI and companies like Instinct?
Yeah, I think another name to lump in there is Town. Town's also an AI agent. It's got a ton of traction alongside Instinct, Town AI. Yeah, so like there's been like kind of a renaissance of consumer personal agents. I think that's the first thing is that these are consumer products. And so the success that we're seeing, um, with Claude Code and with Codex, which is eating up most of the tokens historically, now there's user experience coming to consumers. The Meta Muse was purposely like modeled off of OpenCLAW. And I think Meta Muse has the biggest distribution platform. It popped up Meta's stock price when it went out because it was so efficacious and good. And I think like, if you think that Meta's got a strong, you know, advertising business, they have one of the best advertising businesses in the world, them and Google. Now you can have a shopping assistant just buy what you want. And you like, so instead of an ad that's contextually relevant to you, it's just like, you know, here, I'll just buy this thing for you. Right. And I think the big news this week was that Amazon blocked Metamuse and they said like, well, per our terms of service, you can't have an agent buy anything on our platform. And they seem like they're going to Hold up that line. So whereas like Shopify did the opposite, Expedia did the opposite, and they said like, we're on the Metamuse, like, yeah, buy shit from our sites. And I think there's a question of like whether Walmart will join on to Metamuse also, and whether they'll have like an adequate like shopping inventory. So I think, yeah, AI-assisted shopping is a big use case. I think people are using this for calendars, for email assistant, for generally managing like anything in your personal data. They all have like different capabilities. If we jump over to Instinct for a second, I think one of the things they did really well that I hear, I haven't really used it a lot myself, is the memory structure. And we had a nice article about like how Instinct built the memory structure and it kind of looks like this, like the wiki system that Andres Carpathi described where like it was a bunch of Markdown files being managed by a Git system. So a version set of Markdown files.
Real quick, if people want to know what a $2.5 billion valuation startup memory architecture looks like, this is what it looks like. Conversation messages come in, current conversation context, background processing. That's slightly a black box. That's the secret sauce IP. Accessible markdown files, just like OpenCLaw. One-pager generation, mechanism unknown, also black box, probably secret sauce IP. Search and reads. So your normal CRUDs and stuff like that with indices on demand. Those probably solve problems. Identity profile plus to-do index plus compassion recap. And that all feeds into the while loop that is the agent's answer.
Yeah, it's a great article. You can go through the specifics of the type of memory that it stores. But I think this is what it all comes down to, you know, like whether if you, if you're on Meta's platform, they have access to the data that you have on Meta and then in other places you're giving access to, how are they going to shape the memory to bring in-context judgment, you know, the in-context information that you need to make judgments that are actually helpful to you? And Um, so Meta's got kind of an advantage there. If, if Google makes something like this, they're going to have the Google set of data and they're not going to share that with anybody else. Right. And then, like, on your device, I think, you know, maybe use something like Instinct. You can probably integrate as many sources as the APIs allow. And I think, like, you know, if you're building something, this is the lens that you want to use to understand, like, what brings a great user experience is like, how do, how is context engineering done? How is the memory shaped? And how is relevant information brought into context when the user needs it, right? So I think that all these products that consumers are using are really like good learning lessons. This is just first generation, by the way. So these things are going to continue to evolve. And as an AI builder, you can build your own, you can build them for other people, you know, you can keep evolving the field and evolving like, you know, how memory and context might be delivered.
