Technology, Connected - AI Agents Are Taking Over The Internet

Episode Date: November 15, 2025

AI agents can read feeds, make decisions, coordinate with other agents, and speak on your behalf, without you in the loop.Andrew Hill explains what agents actually are, why every company is racing to build them, and how close we are to personal agents that manage schedules, explain our thinking, and negotiate with other people's agents.We talk about:- What an AI agent actually is (beyond chatbots)- Why agents coordinate with each other (multi-agent systems)- How personal agents could represent you online- What happens when your agent negotiates with someone else's agent- Why people already share intimate details with AI (and what that means)- The hard question: Could AI become better relationship partners than humans?The shift that's already happening: People tell AI things they won't tell friends. They trust agents with calendars, emails, thoughts. The AI knows them better than anyone.So if agents represent us online—if they speak for us, decide for us, negotiate for us—who are we really talking to anymore?This gets into trust, privacy, and what changes when the agentic web replaces direct human interaction.If your agent knows you better than your partner does, what does that make it?---Guest: Andrew HillTopics: AI agents, agentic web, multi-agent systems, personal AI, trust, privacy, human-AI relationships, coordination--Other ways to connect with us:⁠Listen to every podcast⁠Follow us on ⁠Instagram⁠Follow us on ⁠X⁠Follow Mark on ⁠LinkedIn⁠Follow Jeremy on ⁠LinkedIn⁠Read our ⁠Substack⁠Email: [e-mail]

What is an AI agent first? Agent is a very hard to pin down word right now in AI. I think of it as actually very broad. Some people probably narrow it down and they think chat GPT is a model. And then there are agents, which are these things that you might deploy on N8N or on Google Cloud or like in some of our arenas, you might see trading agents, which are kind of software with models embedded in them. But I think of agents is actually.

kind of a broader umbrella where, well, you actually have our models, which are much more like databases. There's some kind of fixed thing. And then you build software around that. And so GPT5 to me is actually an agent. It's more than just the database. It's more than just the model. If you go to GPT5, it has capabilities like memory or web search or things like that. That's very agentic. So it's the model plus a lot of software harnessing that allows the model to do things in the world and react to different kinds of information and make choices based on real-time feeds that are beyond just a query to a database. And so we see that spectrum really broadened up. You have chat interfaces that are very much like models. And then you have agents that live on Twitter that are

reading Twitter feeds and reacting and posting kind of their opinions or thoughts live. And there's lots of things in between. And there are agents that create value. There are agents that are experiments, their agents all over the place. So agents is just a very broad term. I think probably we start to differentiate things as it goes forward, but that's just where it is right now. Who's making them? Everybody is right now.

And I think like this idea, if you can kind of broaden the thinking about what an agent is, is just software that has models that make, you know, use models or intelligence to make decisions inside of them, you see agents kind of proliferating very quickly. Obviously, like, the coding agent is a huge one right now, but it's pretty clear to me why the race for coding dominance from the primary model builders right now is the main race going on. The chat interface that we all interact with has a lot of value. It may have like a lot of value in governments or health care or things like that. But the ability to actually code agents to immediately solve needs. So I have to do this thing. And the model actually knows how to write itself into doing the thing. So models will be creating agents on the fly to solve problems. It's going to make it so that agents are just what solve things in the future. And so right now I think everybody is trying to build agents. We're building agents internally to solve organizational problems like how do we move information around the teams. How do we write better issues than GitHub? We're writing a lot of agents. And I think everybody that's kind of mid-sized startup for a

example is like racing hard at how can I get the leverage out of AI and it largely comes from orchestrating agents. So just lots of people rebuilding agents right now. Yeah, a lot of like the general public belief system about where the future is headed. I know in a lot of minds, they're turning around like, hey, I'm going to have this digital replication of myself that can jump through the internet and handle all the shit that I don't want to mess with. Like how far off are we from that that coherent story that the general public may or may not have in their head about agents and in personal use. I don't think we're very far off. I think I think it takes like a kind of killer use case or a killer product and a lot of people are trying to build it. My co-founder

and I were speaking just yesterday actually about an idea. I don't think it's the killer product, but it would give you kind of a sense of how close the technology could do this. So there's a protocol called A to A.A. It allows agents to just kind of list themselves on the internet and say, here's how you talk to me so that they're kind of open for business. And it hasn't blown up yet, but it's a really interesting opportunity. That got us thinking, what if I had an agent that was me? And I gave it all the public things I want. Like back, you know, maybe you might imagine your Facebook profile, but only things that you wish had been public back in the day. So I say, okay, I put maybe my reading lists. Maybe I put my event.

that are coming up. I put this podcast, like this thing, I'm going to record this. Hey, you should, you can know about this thing coming up. But maybe I don't put my like personal calendar, things like that. So, and then in my Twitter profile, maybe it has a link, or not a link, it just has an ID for that thing. And if you go to my profile and you see me tweet something, you might say, oh, Andrew, tell me more about that. And it's not like you text me or give me a phone call or anything. It just goes to my personal agent and it goes, you know, I was reading these five things and it looks like I kind of co-opted that idea from this blog post. Here's the source blog post and tells you kind of where my thinking might have come from. And I think you can expand

that. Then I start having groups of people like maybe my teen. I do want if they talk to my agent to just give you my full calendar and say, well, Andrew is open on Friday, but he was talking about going on a run or something. So maybe we should check with him if he really is open on Friday. That sort of advanced thing. I don't think that's the killer product. It was just kind of a thought experiment about where we could open this personal agent up, that is a possible scenario tomorrow. So somebody's going to solve that where you could be having agents working on your behalf as you and differentially working together. So then Carson's not even finding my agent. He's just asking his agent to coordinate with my agent, things like that. I think the more, I think the more sticky

question, honestly, is like that stuff is coming, no doubt. I don't know the exact configuration of what that product space looks like, but that stuff is coming, no doubt. The thing that's more sticky is like, I don't think people are thinking about it. Right now, people are having conversations with AI that are incredibly deep and revealing and intimate. Set aside all the privacy. And it's so funny that Cambridge Analytica happened half a decade ago. And now this technology has come about, which I guess is just so valuable that we've all gone. I get so much value out of this. I don't care anymore. I'll tell it everything. But we're in this word. We're doing. We're doing it. that, and I think the really tricky, sticky question is to say, at what point do humans,

I guess, like a reasonable proportion of them, recognize that AI might be better at relationships for many humans than other humans? All right. So what did we just watch right there? We watched Thinking on Paper, bite-sized, a shot of technological tequila to your prefrontal cortex. It's just a taste at a smorgasbord of what awaits you with the full Thinking on Paper interview. There really is nothing to like it out there at the moment connecting the dots of all these technologies. So subscribe while you're listening.

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