How to win with AI Agents in 2026

22:27Howie Liu:Which I think this will actually work. Like, where do you farm? Like, here's my report style.

22:35Greg Isenberg:It also looks really clean.

22:37Howie Liu:What's that? Yeah, I mean, and honestly, a lot of this is just like, if you have a good frontier agent running a frontier model, i.e. like Opus, you know, 4.7 or GPD 5.4, like it just does a lot of this really well out of the box. So any frontier agent powered by a frontier model should be able to create an app of this quality. What's unique about Hyperagent is that it can do that perfectly well, but then kind of do that in the workflow of like, it's not just an app builder. app building is just a feature now it's a commoditized feature and what it can actually do is like go and research the end-to-end of like here's actually the business context of what i'm trying to do and then build the app informed by it right so it's more like hyper agent is the founder in this case it's not just the developer it's the founder um one of the cool thing i like about hyper agent is like it just comes out of the box with like really powerful tools so it has like you know google maps as a tool and it can actually go and like let's say i think i already did this, but like I wanted it to go and actually find like real street view imagery of billboard locations.

23:41Howie Liu:So it knows how to use street view to like find actual points of interest. And then to take that image and use that as a reference seed image for like a AI image generation or video generation. Right. So like, I mean, another cool thing you can do with hyper agent is you could tell it, like, take this house and like, I want you to redesign the house using interior photos from Zillow or like the exterior shots. And it will do that like really, really well. Right. So that's hyper agent in a nutshell. I can walk through some of the other stuff here. You know, once you actually build like a lot of agents, then you get like this, this ability to start looking at like, well, what if I wanted to see, you know not just my one agent, sorry, but but an overview of all of my agents, right?

24:29Howie Liu:So this is not like a very built out account. This would be like your first week of hyper agent use, but like literally that command center view that we talked about, like, you know, we want you to be able to create many different agents that each play a role. Here's the content marketer. Here's the market researcher. Here's like the customer email responder and like just manage and oversee an entire fleet of agents, constantly improve them because we actually have this ability to go and like, you know, curate memory and skill improvements from every run that you do. And then finally, to be able to deploy them into a team setting as well.

25:04Howie Liu:So if you wanted to take any of these agents and actually give it the ability to talk in Slack, right? So I can actually say like, let me put this into Slack. Let me have it always on, always listening, in fact. And, you know, just sit there in my channels, listening to everything I'm talking about, my team's talking about. And when I have something relevant to add, to automatically chime in and then people can interact with me truly like I'm a virtual coworker, right? And I think that's kind of part of the open clock experience I've seen some of the power users achieve. That's really quite magical.

25:36Howie Liu:Like your Slack coworkers are now agents in addition to humans. And they're really smart and they have their own expertise and context. Like you get that with a single click out of any agent that you build in hyperagent.

25:48Greg Isenberg:So you mentioned skills. You know, how does skills work on hyper agent and how should people think about it?

25:55Howie Liu:Yeah. So skills are, I think, like the most important concept or primitive in the frontier agents world, meaning the models are generally intelligent enough. It's like find like Albert Einstein, who's like obviously super smart in a general sense. And he may not know like how to solve problems in real estate. But if you gave him like just the right like kind of briefing on like, here's a playbook, here's a manual to learn everything you need to do to know to do this job in real estate. Like he's going to go and like figure it out pretty well. Right. And so what's really powerful about skills is like they're a really, really composable concept.

26:30Howie Liu:Like you can interactively create skills. So let's say I'm actually going to create like a new thread here. Just keep this super clean. But like, help me create a skill that posts Greg Eisenberg like AI content. Okay. And so what's really powerful about this is like.

26:51Greg Isenberg:No, don't create this. Don't create this.

26:53Howie Liu:No, no, no. Okay. But worse enough that, you know, we don't take Greg's business. Exactly. But what's really cool about this is like, it's not going to just like go and like, like say, okay, like, you know, I'm just going to have a prompt that, you know, pretends to be Greg Eisenberg. It could actually go and like, you know, research how you actually do content. So it's coming up with a plan. The plan is like, I'm going to first go and like research your style, figure out like what platform I care about, like look at some of your actual posts and then distill all that into a skill that I can then pin to an agent or like just use on demand at any point.

27:30Howie Liu:Right. So let's say just for fun, like what what platforms do you want to post to? Let's just say X for now. We're going to have the skill only generate drafts. So it's not going to auto post for you. Is there any kind of content you want your agent Eisenberg to be focused on?

27:49Greg Isenberg:Yeah, let's do contrarian AI takes.

27:52Howie Liu:Okay, cool. And then any topics beyond that?

27:57Greg Isenberg:Solopreneur, Bootstrap, Lifestyle.

27:59Howie Liu:And then how do you want to use this agent if you end up using this agent? Do you want to start with an idea? Do you want it to just come up with ideas for you? like we'll go full on this right like someday we're gonna have to see if like real greg is actually just sitting at the pool all day it's just created the the uh greg avatar version of you uh and is doing everything on its own but okay so now it's like gonna go and like do some research about you and figure out like how to distill distill the perfect skill for for greg into this skill.

28:38Greg Isenberg:How should people think about HyperAgent versus Perplexity Computer versus Manus versus OpenClaw itself? Codex?

28:50Howie Liu:How do you see it? I think against Codex, it's quite simple. HyperAgent is a more general purpose agent platform. I think against OpenClaw, this is much more turnkey, ready to go, safe and secure by default cloud native like you know and and i think just much more focus on like great ux right open claw like we actually have to go to configuration or like you're trying to edit memories or do any kind of curation or like kind of configuration it's you know it's it's quite raw right it's like a very you know kind of raw product kind of feels like it's more for like very technical people who become like expert at it um i think perplexity and manis or perplexity computer and Manus are like the closest comps for Hyperagent.

29:35Howie Liu:The key difference is like one, you know, Hyperagent has more powerful tools out of the box. And, and also is, it has more focus on UX out of the box, right? Like, you know, I've spent some time playing with both of those products. I think they're great products and like, you know, at their time and, you know, or at least when Manus first came out, it's truly groundbreaking, right? Like it was the first kind of real like holy crap like YOLO agent like look at everything it did kind of like before even OpenClaw right long before OpenClaw and so I think they were really kind of pioneers in this space with HyperAgent like we've just taken a very UX focused approach so for people who like you know seeing visually and be able to like interact with the outputs and see more visually like what the agent is doing and have a more visual way of you know defining skills deploying skills, creating agents, et cetera, hyper agent is just much more of like the Macintosh experience, right?

30:31Howie Liu:Versus the Linux. I think secondarily, we've also kind of done a lot more to make hyper agent immediately ready to run, not just like one like agent. Like I think the nominal experience for Manus and Perplexity Computer is still like you use those products and you kind of have this like agent that's pretty awesome. And you know, you use it directly, right? You can do that with hyper agent. That's exactly what we're doing here. But it's also designed from day one with much more of like the scalability and deployability story in mind. So meaning like once I have an agent that kind of works for me, I can now deploy it one click into my Slack channel.

31:06Howie Liu:And now everyone in my company can benefit from this agent just always on like kind of chiming into conversations. You know, they can ask it questions. It will respond. You have the command center, that fleet view where it's not just one agent. You can oversee your entire fleet of multiple agents. And we even have things like, you know, the ability to oversee and curate like the learnings that keep making each agent better. So like they kind of have this automatic self-improvement loop where over time they're accumulating not just new memories, but also like suggesting to you, hey, maybe you should add this additional skill or update or tweak the skill.

31:39Howie Liu:Or even like maybe you should go and actually try changing my agent system prompt or give me access to different tools so I can do this type of job better. And best yet, like we actually have this concept of what we call rubrics, which is exactly what it sounds like. It's like an eval rubric. And what you can do with rubrics that's really powerful is actually like define what does good look like for a certain type of task, right? So I could create one here that's like, what is a rubric for great Greg Eisenberg content? And what it basically does is I can then have a full eval loop where every time my agent runs, like once the Greg Eisenberg skill is ready, I could say like, I'm creating the virtual Greg agent, and I'm going to pin a rubric to that agent that then says, every time Greg creates a piece of content, I want to score that content along the dimensions that you care about using a separate LLM as judge that fires off.

32:31Howie Liu:And then I can literally oversee like how well is my agent doing over time. Right. And if I want to double click in and inspect any one task run to see like, how did it get scored? I can do so. So we basically, you know, have this complete full loop of, it's not just like you get a day one agent or thread experience that works really well out of the box. And it's not just like you can curate agents and deploy them and like improve them over time, but it's that you have this complete observability layer and kind of this orchestration story where you can actually just like look at all of your agents running all the time and see how they're doing.

33:08Howie Liu:And so if I pinned the eval rubric to any one of these agents, I would see like the trend line of how it's scoring. I could then automatically like suggest, hey, maybe I can reduce the model quality. So I drop from opus to sonnet, get a five times reduction in cost and the score didn't go much down. So just once people actually start running agents at scale, these kind of secondary capabilities become really critical because it's not just about can I get one agent to do one thing, but how do I oversee and run an entire business with many different agents and ensure consistent quality.

33:45Greg Isenberg:Which is a big deal because, for example, if you're using Manus, who is the judge around the output? The judge is you, a human being. It's not Opus 4.6. It's a human being. So if you're trying to actually create what we were talking about before, which is an agent-first business, managing a ton of agents, realistically, you're not going to have the bandwidth to be looking at every single output at all stages, right?

34:12Howie Liu:Yeah. It's kind of like management 101, right? But applied to agents now, where it's like, as you scale up, if you're the CEO of a business, Like you just literally don't have time to go and like look at every single thing that every single person in the company has done. And so you need to create like better automated checks and balances to oversee what the agents are doing. Right. And like inspect quality of work. Right. Like this would be like if you actually had like a giant army of human content creators, like you would want some way of like, you know, in a scalable way, like to detect like if they're posting good or bad content or not.

34:47Howie Liu:right and then know like okay we got to tweak like the guidelines for each of these people okay so now we have the greg eisenberg contrarian draft skill um and i'm gonna go ahead and save this skill and i'm gonna try seeing like okay let's do a dry run it's gonna scan today's ai and uh news and trends and then create some contrarian drafts right and the whole idea here is like look like it's probably gonna do an okay job on like the the first effort here like it did some research about you. It kind of like, you know, it has a lot of like, um, context about how you work. Right. And if I wanted to see more about this skill, I could actually open it up.

35:24Howie Liu:Here's a, when it should be used for, here's the actual kind of skill contents. Um, Greg's voice is a smart friend at dinner saying the quiet part out loud, uh, not a corporate communicator. I would agree with that. Um, you know, you've been inside all these companies, uh, blah, blah, blah, like doesn't mean be a jerk. I, I, I, I think it's very astute. Like you're loud, but like not annoying or like kind of rude. And then actually I'm curious if you agree with some of these stylistic things, right? Like you got a hook in the first seven words. You know, you don't want like long blocks of text, which I'm guilty of.

36:01Howie Liu:So I, I should take some of this Greg, Greg skill and apply it to myself. You love ordered lists. Never end with what do you think, which is super generic. So let's just say like, this is a pretty good V1. Like maybe it's like 50 % of the way there. But the idea is that like these skills should be evergreen, right? Like it's not like you do one and done. The whole point is like every time I use a skill, like either automatically using, you know, kind of the LLM generating learnings and like suggestions to improve itself, or because I am looking at the content and saying, oh, that's not quite right.

36:38Howie Liu:Like, here's why you got that wrong. Like you can interactively tweak and improve the skills and performance of the agent over time. So like, I think this is the, the, the like challenge that a lot of people face is like, they one shot something. It's not quite like as profound as what they hoped for. And they kind of give up. Right. And I think like my, you know, kind of, um, strong guiding and urgency to folks, and I think this is very aligned to how you've thought about it, like, is don't give up after the first shot, right? Like, because it's very, very clear that the agents are powerful enough to do almost anything you want it to do.

37:12Howie Liu:And the issue is not whether it's capable of and whether you should like give up on it. It's whether you are able to invest the kind of time and coaching and like curation to get it there. And I think that like, it is well worth it, right? Like, if you get it there, it's obviously going to be so much leverage for you that like what's the value of like having an always on now employee that just like does the things that you care about like behind the scenes at all times and like you know runs for trivial costs relative to like the the cost of hiring a new employee well it's like real life too which

37:48Greg Isenberg:is like you know when i first started playing tennis i was bad at playing tennis and when i you know would go to play tennis i i almost didn't want to go because i was like i'm bad at this but you go through the messy middle and you get better and better and over time then you end up, wow, this is a lot of fun. I think that once you get to the point where it's a lot of fun and it does feel like the outputs are really good, the truth is 99 % of people are not putting in the work to get the great outputs. This is the arbitrage. It's for people to actually invest in spending time to optimize and get it to a place where it's high quality.

38:32Howie Liu:Absolutely. Yeah, it's funny. One of the benchmark partners sent out this memo about, it was basically a wake-up call to all of the portfolio companies to get with the program and really radically rethink how you operate your business immediately with AI. And the assumption is you think you're doing some things for AI. You have an AI, like, you know, kind of like, you know, center of excellence. You have like this AI feature, but it's not enough. Right. And the kind of parable that they ended with was like, imagine like there's two friends back in like, call it, you know, like 2003. And they're both going door to door selling like, you know, kind of knives.

39:18Howie Liu:Right. Like or some other like, you know, kind of in-person, you know, kind of offline product. and one of them decides, you know, like every night and weekend, I'm going to spend like 30 minutes, like trying this new Google, like AdWords thing and trying to like get some extra leads for my business as supplementary. And, you know, like one month, like they grow a little bit of revenue, like from, from the SEO or the SEM thing next month, they get a little bit more. And the other person is like, this thing is awesome. Like SEM is awesome and it's early, but I need to figure it out. And so they stopped going door to door and selling knives at all.

39:52Howie Liu:And they just spend like the next few months, like just focus on like, how do I get this entirely internet business to work right in the early days of it. And like, you know, two months, like they have zero revenue. They're like living off like their savings. But they slowly start to get this thing to start get humming, right? And they get like really versed in the best of SEO and SEM techniques. And how do I create an e-commerce, you know, kind of, you know, a website that like allows people to transact directly there versus like just giving them a number to call me. And, you know, the end of the story is like, okay, like project forward like five years.

40:29Howie Liu:Where do you think each of those people is? Right. And like the obvious answer is the second person has probably built like one of the early multi-billion dollar e-commerce businesses and just like carved off like the next Amazon. Right. And the other person's like probably still selling door to door, which is getting harder and harder. and like, you know, kind of that, that market shrinking. And so I think it is one of those things where it's like, you kind of have to like hit a reset moment. And what feels like, you know, maybe experimentation and not actually bringing home the bacon actually is the most profound thing you can do to create like real business leverage in the, like, not even like two year timeframe, but like maybe even like the six month timeframe.

41:07Howie Liu:And I'm curious, like in your experience, or when you see like a solopreneurs doing this, like, where do you see, or like how often, what is the average break-even point? Literally either in terms of you get to the point where you can self-sustain a full-time business, and that becomes your paycheck, or just even where it even feels like it's starting to pan out.

41:31Greg Isenberg:I think that there's multiple milestones that people hit. It's a game of confidence. When you make your first internet dollar, no matter what it is, it rewires your brain. So if you can take an idea and make$1 a stranger, just$1, it's going to rewire your brain. Then I think once you get to 10K a month, just something about that number, for the most part, once you hit that, you're probably quitting your job, you're probably going all in, you're probably like, okay, there's something here and there's a path to something bigger. I think that with respect to agent products and products like this, the mistake I think a lot of people make is they try it too sporadically.

42:19Greg Isenberg:So what I encourage people to do is to actually try the product every single day for a certain amount of time. So commit to 30 days, 60 days, 90 days, some amount of time so that every single day, it's like in your calendar. Literally I have in my calendar 30 minutes here, 30 minutes there. That's what gets you to be a top 1 % agent builder. You make it a part of your workflow and then you end up seeing outsized returns because it compounds.

42:54Howie Liu:That makes sense. I'm not a writer, but I've heard from writer friends the most important thing is not to wait for the one weekend where you're going to have the spurt of brilliance and write the whole screenplay or the whole book all in one get-go, but it's like you have to force yourself to write like some pages every single day. Like no stopping. Like some of them are going to be crappy pages, but like the forced habit like just gets you better and better and better. And then it becomes like natural. And so I could see that being very applicable and kind of like analogous here for the world of like getting agent savvy.

43:27Greg Isenberg:So do we have some tweets?

43:29Howie Liu:So, okay, let's look at this. Let's see. The consensus narratives are getting louder. Every Medium post reads the last one. Okay, so here's one. The 10K month AI solopreneur boom is mostly content farm fiction. They say 82 % of US businesses have zero employees. What do you think about this one?

43:54Greg Isenberg:I mean, what I like about it is when I do tweets, because I'm a human being, largely there's no data. It's just like, I have a hot take. So what's cool about this is there's research. And the truth is, people obviously want data associated with their tweets.

44:13Howie Liu:Yeah, maybe with a team of hyper agents doing all the research for you and coming up with content ideas, now you have time. Oh, this is kind of cool. Is this true that Medvi is actually not a legitimate business? I actually, I hadn't, I'd followed like the first arc of that story, which is, oh my God, this thing is like so massive. But I mean, it's a little letdown for like the billion dollar startup story. But like, you know, maybe there's a take on it that says like, no, but like, it's still possible for real. This guy just kind of gave us all a bad reputation. Your AI agents didn't replace your VA, blah, blah, blah.

44:55Howie Liu:It's kind of interesting.

44:57Greg Isenberg:These are all what I would call kernels for really great tweets.

45:04Howie Liu:Yeah, B-Y-O-K. And the cool thing is I could give it feedback. So as an example, let's say I want to give you feedback on your skill. What's one thing that you want to give it some feedback on? I would say the tweets that tend to do well

45:27Greg Isenberg:sound very friend to friend.

45:30Howie Liu:And do these all just feel a little too, like they're not colloquial. Exactly. These feel a little too formal or stiff or something. Exactly.

45:45Greg Isenberg:Yeah, and that's something I would notice that. Yeah. And so what we can do, like we would put this in the eval right yeah you could do both so one is like you could

45:58Howie Liu:immediately go and turn this like or update the skill based on this feedback you could also have it immediately just like turn around like a new draft of these tweets right to sound more colloquial and then finally to your point i could go and create a rubric that actually says like okay like here's the five dimensions i care about and then auto evaluate every future output right um so So you kind of have a number of different options, like depending on how far you want to go right now. Like if you just want to get your job done right now, you don't want to bother with Rubik. You don't have to, right?

46:29Howie Liu:But eventually, like you get to the point where you want to set up a scalable system for this to just constantly work and get better and better. And that's the point at which you would do a Rubik, which is not that hard, actually. Like, you know, you can either go in through the UI and build one or you can actually in this chat, like, say, help me build a Rubik to score great Greg style content, which I'll queue up for after. it updates the skill and then it will go and help me create that rubric save it, pin it to this agent or to this skill and then automatically run every future time I create content.

47:05Greg Isenberg:And is it possible to, for example, get an email every single day at 8am with some ideas? Yeah, you absolutely can.

47:17Howie Liu:So the way to do that would be, in fact, you could just tell it in the thread Like, can you turn this into a recurring daily email at 8 a.m.? And so then what it's going to do is, like, say, like, I want to now save this thread into an agent. And the agent is going to be given a run schedule of, like, every day, 8 a.m., go and do this thing. We're actually about to ship something that we're calling a live mode, which is kind of inspired by, like, the open claw, like, kind of heartbeat behavior, where you could already have configured an agent to do this just by saying, like, I want it to pull every 30 minutes.

47:48Howie Liu:but we're making it much more of a first class thing within hyper agent where you can literally just click a button, turn any agent or any thread alive. And then the feeling is going to be that like, wow, this thing is just like constantly on and looking at all of the like new tweets out there coming up with new ideas and then pushing them to me either via telegram or over email or in Slack, whenever it comes up with new stuff. So like the, the, um, the UX or the mental model is meant to be like, wow, this just becomes like a always on like 24 seven agent that, that pushes ideas to me or even like can go and like preemptively draft and post content.

48:27Howie Liu:Like if you wanted it to go full YOLO, you could actually have it just go and like tweet the content itself. Right.

48:33Greg Isenberg:Good old full YOLO mode.

48:35Howie Liu:Yeah. Yeah.

48:37Greg Isenberg:I don't recommend full YOLO mode just because

48:45Greg Isenberg:there's no need for something like this. For X specifically, in order to win, if you can get one good tweet out every single day, that's all it is.

49:00Greg Isenberg:You can schedule it out, but just look at it and make sure that it's high quality. It meets your bar. I think it's definitely worth it for this specifically.

49:14Howie Liu:Yeah, that's fair. I think that content is a very hits-driven business. And so fewer high-quality hits is what matters. But there are tons of use cases where maybe for my own emails, there are a subset of emails that are low stakes that I just want HyperAgent to just automatically not only draft a reply, but if it feels confident, it's like not a sensitive kind of situation, like, you know, then just go ahead and like respond to it, right? Like, you know, it could be simple, like inbound inquiries from like internal folks saying like, hey, when you have time to meet, it could just preemptively go ahead and like suggest a time, right?

49:55Howie Liu:Or even like pre-book it on my calendar or customer emails that are like innocuous or like asking for like, or trying to give input on a feature. It could just compile all that feedback for me as a report, but then respond with a smart, personalized acknowledgement to the user, or even ask for clarification.

50:15Greg Isenberg:And I think you all have a ton of connectors built into Hyperagent, right?

50:21Howie Liu:Yeah, so what's really cool, actually, is that not only do we have a ton of connectors that just work out of the box, you click a button OAuth in the thread, right? So maybe starting a new one, I could say what's a tool that you want to use with Hyperagent? It could be like Winola.

50:37Greg Isenberg:Notion maybe?

50:38Howie Liu:Okay, yeah. Connect, can I connect to Notion and pull in all my notes? And so it will just in the thread, like say, hey, here's an OAuth link, like connect to your Notion. But arguably one of the most powerful parts is like even for things that we don't have a connector to, like let's say there's some like very obscure API that you're trying to work with, right? you could basically have HyperAgent go and learn that API. So I'll say, actually, never mind on this. Can you instead help me build an API integration to what's some fairly new tool that you know of that has an API?

51:21Greg Isenberg:I'm assuming, well, do you have linear built in here?

51:25Howie Liu:We do have a connection to linear, but actually maybe Twilio could be a good example, right? I don't think you can OAuth into Twilio, So it has to be an API skill. And we may have a pre-built connector, but I'm going to have it like build a custom skill regardless. So can you still help me build a custom skill to integrate with Twilio via API, right? And so now what's going to happen is like, it can go and like research the Twilio API docs, create a skill for itself to use the API, and then actually ask me to enter my credentials in a safe way. and then be able to like use the Twilio API fully, right?

52:06So I think like the powerful thing now

52:09Howie Liu:is a frontier agent should be able to like literally do anything, right? Like, but it's just a matter of like, you have to give it access to the right context and you have to like, you know, tell it like, hey, like, yeah, you should build a skill for this. So then it can do it every single future time effortlessly. Okay, let's say what we want to do, SMS voice for now, maybe phone numbers. We'll do an API key off and any specific workflows. Think like maybe actually I want to build a voice and SMS service that can call restaurants for reservations or something, right?

52:53Greg Isenberg:If you're listening to this and you're not fired up about building a business right now, The fact that you can do this is crazy. This is the first time they're hearing about Hyperagent. They want to get started. What's a plan for them? What should they do? How do they get started? How do they get the most out of Hyperagent?

53:18Howie Liu:I think often the hardest thing to get over is not how to use the product. Like I think, you know, our users have said like, wow, this product is like super intuitive. Like I can usually just like ask the agent to figure something out and it goes and does it. So it's not like I have to learn like a ton of new like configuration or UI or anything. I think the hardest part is actually like picking like the right problem or like the right business opportunity you want to try to attack with hyper agent, which like hyper agent actually can help you brainstorm that. In fact, we just shipped a new, better onboarding flow where instead of just like landing you into a generic, you know, kind of like empty canvas where you have to like just pick like a new thread and, you know, we have some like templates and so on.

54:03Howie Liu:Like now when you first land in, it's going to suggest like, hey, do you want to like connect me to all of your contacts? So like connect me to your Gmail, to your Slack, and to like your Notion and Granola. and what I'll offer to do is actually go and like research you like in your context. So I want to read through a bunch of your like past weeks emails and slacks and like look at your past Grinilla meetings and you know of course all that context is private to you but like now Hyperagent is going to be able to like suggest to you like hey based on everything I've learned about you like here's some use cases that might be relevant to you.

54:37Howie Liu:So it seems like you're a VC, maybe you're like doing a lot of deal flow, I could create an agent to just go and automatically like, you know, kind of summarize and do research on every investment pitch that you get. Right. So like you can turn me on all the time, like I'll just run in the background and then like ping you every single time you get a inbound pitch or you can even have it learn the behavior to thread a private reply to any email that you get inbound from a founder. Right. So you get an inbound pitch, Hyperagent on behalf of you sends you and only you a just threaded reply within that email chain saying, Hey, I researched this company.

55:15Howie Liu:I also summarize all the materials. Here's what you, you should know about them. Right. But the whole idea is that like Hyperagent itself can help you identify use cases, or you could come in just with a really broad prompt, like kind of interested in billing, building a solopreneur business. I don't know. I'm kind of interested in like real estate. I want to pick one of Greg's, uh, you know, kind of ideas that are open stores, like help me plan this out. Right. And it will do a very good job of like going and running with you on that. So I think the main thing is like, don't get stuck in the blank slate starting point problem.

55:45Howie Liu:Like just come in and like, you know, figure out some place to start. Maybe it's your personal, like, you know, contacts. Maybe it's like you come in with an idea, but like, once you start getting into it, like it's, it just sucks you in even more because like you realize all of what you can do. And it's just so powerful. Like you won't help, but to get better and better at it.

56:06Greg Isenberg:Last question before we head out. I was just talking to someone on this podcast talking about Hermes Agent. One of the things we were talking about is when you're picking one of these platforms, be it OpenClaw, HyperAgent, Codex, whatever, you're sort of investing in an ecosystem. My question for you, Howie, is why should someone invest in the hyper-agent ecosystem? Where do you see hyper-agent going over the next few years?

56:43Howie Liu:We have a lot of experience building great PLG products. Obviously, Airtable itself is a PLG product that also scaled up into real serious businesses. There are companies that still run their major operations, whether it's like really, really large, like, you know, kind of Walmart scale companies, like, you know, the opening eyes of the world, but also like, you know, we have like, like really innovative, fast moving SMBs, some of the like fastest growing companies like Record run a lot of like stuff on Airtable. And, you know, I think like the, the, the experience that we have of building a product that's both extremely low floor and intuitive, but then also has a very high ceiling and scales up even as you need to scale up the number of agents you have, how you deploy them, how you oversee them.

57:33Howie Liu:Like that's our commitment is that we are going to be the best at giving you both a low floor and a high ceiling, especially as you want to actually run a serious business or operations with hyper agent, right? So I think that's going to be kind of unique where I see the landscape fragmenting into like, there's going to be really easy, fun kind of prototyping tools and products that are kind of like easy to get started with, but then ultimately don't scale with you as you want to become like a real serious enterprise built around these agents. And then conversely, there's going to be more like heavy kind of agent builder products, right?

58:09Howie Liu:With like configuration and like controls and all that stuff that are going to be better from like a control plane standpoint from being able to like oversee a fleet of agents standpoint, but make the initial experience and the graduation path like a lot more clunky, right? Or just like a really sharp wall to overcome. So I think our commitment is this product is going to be the best combination of low floor and high ceiling. And we're always going to have this obsession with great UX. Like that's our DNA. That's like what I obsess over. And the only kind of company that I want to build is one that wins in a product category where the value of the software or the technology is very, very high, but the accessibility is really kind of the key differentiator that we went on, right?

58:56Howie Liu:So agents are going to be powerful. We're not going to be the only powerful agent product out there. Like I think frontier agents are all going to get better and smarter and faster and so on. But what we can do is use really great product design, just like Apple did with computing to make the powerful experience also really accessible.

59:16Greg Isenberg:Yeah, it really is the most, Hyperagent's the most visual agent builder I've ever seen. It reminds me of a desk. I'm looking at my desk, it's a wood desk right now, and I have a paper over here and some scribbles over here and my iPad over there. To me, that's what Hyperagent feels and looks like. It feels like a desk that I'm visualizing it. So I think for people who connect like that, and I'm certainly one of those people. I think a lot of people are just going to be like, sign me up.

59:51Howie Liu:Totally. For people who don't like UI and want to just use their computer through the terminal all day, every day.

1:00:01Greg Isenberg:Howie, some people are like,

1:00:06Greg Isenberg:what they love doing is obsessing over tuning every single detail and stuff like that. And those people, you know, that an open claw might be for them, right? But if you want more.

1:00:20Howie Liu:Like, yeah. But I believe that, like, you don't have to sacrifice the tunability, right? Or, like, the power. And so, you know, one of our strong design philosophies here is that, like, hyperagent still does give you a lot of control. Like, you can go and tweak, you know, kind of, like, agent configuration if you want to. If you want to choose the exact model and system prompt and tools and give it a lot of refinement, you can. And you can go quite far in terms of curating memories. We actually just shipped yesterday a kind of like a defrag tool for your memory so that as you accumulate more and more memories across all these different agents, you have this really elegant way of defragging them.

1:00:58Howie Liu:where we can auto-suggest hero-related memories clustered by both keyword as well as embeddings similarities so that we're actually understanding the content of the memories and you can consolidate them. But we want to really serve both people who are power users who want control over how the agent is set up so they can get maximum bleeding edge performance, but then also you shouldn't have to do all that to get value out of the product. So it really is about the range. I think it's more Or just that if you are truly happy just doing it all yourself through a very low-level command line interface kind of experience, and you're okay not having the control plane, the ability to oversee many agents and deploy them at scale and manage across a team, then maybe those people aren't going to appreciate HyperAgent as much.

1:01:53Greg Isenberg:Totally. I'm stoked to see how it evolves. Thanks for doing a little show and tell. You got me fired up. I'll include links, where to follow you, but also where to sign up to HyperAgent in the description, in the show notes.

1:02:11Howie Liu:And we're going to do a really generous credits giveaway for your listeners. One of the benefits of launching HyperAgent within Airtable, which is a half billion revenue business, we're going to generate 100 million of free cash flow. you know, this year, like we have over a billion dollars on our balance sheet. That's not to like, you know, just be pretentious about it. But is that like, you know, we've built a good and growing and like, you know, kind of profitable business with Airtable that allows us to be even more generous and liberal with like, we just want to get people to really adopt hyper agent, get value out of it.

1:02:49Howie Liu:And we want it to become the standard, right? Like we want it to become like the iPhone. And so, you know, we're willing to be very, very generous. Like we're not trying to make money and nickel and dime people on, you know, on pricing. In fact, like we're giving away multipliers to, you know, your audience and early adopters for both like just straight up cash that gets applied towards real model costs, including like Opus, which now, you know, as a lot of the OpenClaw community has gotten kind of sad about, like you can't get subsidized credit for use in OpenClaw. but you can use Opus, you can get the Frontier models, and you can get it much more cheaply because we're willing to subsidize it through HyperAgent.

1:03:32Greg Isenberg:Well, this is a group of people listening to this who appreciate that because this is a group of people who actually listen and actually go and build stuff. So thanks for the love, Howie.

1:03:47Howie Liu:I love the solopreneur and like, you know, small early stage, like startup and small business owner, you know, audience. I think, you know, it is where more AI innovation is going to happen far faster than frankly within many large kind of incumbent companies, right? You just have the agility and like the only thing keeping you from going and deploying agents everywhere is like just your willingness and like putting in a little bit of time, right? But, you know, we're already seeing in our early adoption base with hyper agent, like, you know, some of these like Like small shops have become super sophisticated really, really fast and are running their operations in a kind of game changing way that, frankly, like a 50 ,000 person company would not be able to do for a much, much, much longer time.

1:04:34Howie Liu:Right. And just has all kinds of like, you know, kind of reasons why they wouldn't be able to go and pivot on a dime. So I think this is a really, really awesome audience. And, you know, I kind of live to see, you know, entrepreneurs like do awesome stuff. Right. So super exciting to be plugged into the community. And I want to see your listener base generate$100 billion legit companies with less than five employees.

1:05:04Greg Isenberg:Your lips to God's ears, baby. Thanks a lot, Howie. I'll see you next time.

1:05:09Howie Liu:Awesome. See you.