Airtable CEO: This Is What the Top 1% Do With AI | Howie Liu

I'm the bottleneck because all the content goes through me. What if I have an agent that already knows my taste and I say like, you just let it give the feedback?

If you could hire as many people as you wanted for almost zero cost, like what other roles would you hire people into?

Howie Liu built one of the biggest software companies on the planet. Airtable is used by more than 80% of the Fortune 100.

The people who are able to do that most effectively will become like almost superhuman, right? You're able to give good judgment and feedback to just like a really effective CEO of humans. You could Imagine building a company that you never would've dreamed of without any employees or with minimal employees. So the tinker mindset is most important first and foremost. And then I think the second is really—

My goal is that anyone who has been consuming content about AI but was not like scared to try it, but thought it was too complicated. Yeah. I want them to actually deploy a few agents after watching this video.

Okay.

To realize how powerful the technology has become compared to like 2 years ago when they maybe tried one prompt in ChatGPT and were like, oh, this is nothing. All the hype, I don't understand it. When you work with this technology correctly, it's actually really transformative. Can you talk to me about the current state of AI?

Sure.

So we've been in an era of chatbots. You had to initiate the process, correct them, and then the output, you wouldn't really trust an agent to post for you on LinkedIn. I feel like right now we're trying to close the loop with these agents.

Yeah.

Like, teach them our taste, teach them how we give feedback, and make them more autonomous.

Yeah.

Is that what you're seeing too?

I do think like there's been this, you know, kind of step function change in the experience that you can create with AI from pre-ChatGPT. But then I think we entered like a mature era of even AI chatbots where the models got smarter. So even thinking about like, you know, the, the year after GPT-4 came out, you know, we could actually do really interesting things with chatbots. So, chatbot maturation. And then I think we started to hype agents a little too early. So there was a year, like last year, people were, you know, they were saying this is the year of the agents. And I think that was when, uh, Salesforce Marc Benioff went up and was talking about like, you know, in the future every CEO is gonna have thousands of agents, like, you know, agent employees and human employees. And I think it was correct, but just early.

Mm-hmm.

And so what we finally hit now, I think, and some would say like really it was like around end of last year with like the Anthropic like Opus, uh, 4.5 and beyond generation of models. But now And now, you know, you have GPT-5.5 and KIMI 2.6, like these open source and, you know, alternative models that I think have all reached this level of intelligence that actually enable agents to be like almost human-like, right? And autonomous.

Do you, when you see a post on X where somebody says, I sleep at night and my company's being run by 50 agents, do you believe that? 'Cause I, I don't know, like I've deployed a lot of agents, but I can't sleep. It's still in my head.

Yeah.

Like I'm responsible for that agent.

Yeah.

I'd rather have more humans to just, control those agents. But do you think we're moving towards that reality?

You know, I think, um, I think that as the models get better and better, we do need to rethink the entire paradigm and like the, the product form factor to reflect it. So I'll use a parallel here, which is in the development agents world, you know, you had Copilot, GitHub Copilot, that was kind of the first, you know, kind of chatbot for developers, right? And It really was that, like, you couldn't have it go and develop, like, really complex programs. It was more like you could autocomplete a few lines of code at a time. And so it was a convenience. Then you had Cursor, which introduced its own AI agent called Composer, uh, which is different from, like, the, the now what they're using that name for is the, the model they've, uh, fine-tuned. But at the time, it was a much more autonomous agent. You could tell it, go and, like, build me this file, write me this, this simple, like, you know, kind of script or, or, uh, or function, and it would do something a lot more autonomously than, you know, the original Copilot experience. I think now yet we've entered into a new era where the agents do enable, you know, kind of you to go and execute on parallel in parallel with multiple agents. And so in the development world, the best developers are already, you know, they're not using necessarily Cursor. They're actually now using many different agents. Maybe it's Claude Code, for instance, running in parallel. And it almost does feel like they have their own company or team running, including overnight, right? I actually, when I'm developing, I use agents that, you know, I try to have them do something substantial before I go to sleep so that, you know, for hours at least, like, I'm not wasting bandwidth cycles, um, and they're, they're doing something useful. And so when I wake up, they've already completed, right?

Yeah.

So I, you know, I think we are moving to a world where the form factor will start to look more like managing a fleet of agents or almost managing, like, you know, people. Um, you know, like everybody, when they transition from being an individual contributor to becoming a team manager, it's kind of a different role, right?

Yeah.

You still need some of the same techniques, but also it's quite different. So, I think we are moving in that direction, but to your point, I think it's, it's also not yet a, you know, at a point where you literally just have the agents do everything, right? Like, I don't think agents can effectively run an entire company or any substantial company autonomously.

When do you think this flip is gonna happen? Do you think by the end of this year we're gonna see more output that's actually deployed right away by agents? Picture this. You have something clear in your head, how a banner, a logo, a thumbnail should look, and you're building a personal brand and you need fast execution. Design.com is a perfect tool for that. You describe you want, the AI builds it. You refine in chat, it adjusts on the spot. Logo, website banners, social graphics, business cards, presentations— you can use the same tool for all of this. Say if you're growing on LinkedIn and a lot of people, uh, say that video banners actually work best right now, design.com can help you with that. I'm seeing more and more people who post graphics and it's kind of hard to stay consistent if you have to redesign everything from scratch every time. Or maybe you need a logo for your personal brand. Design.com is a perfect tool for all of that. You describe what you want, you get something usable in a couple of minutes. If you want to change the layout, swap a color, try a different font, you just ask in chat, it updates. No revision cycles, no delay. Same flow for Instagram posts, stories, YouTube thumbnails, anything you're posting that week. Set your brand once, the platform carries it across every new asset. Over 400,000 logos built so far, a million designs total. And what you make is yours to use commercially. If design has been the thing you've always wanted to work on but just couldn't, try design.com yourself. Link is in the description. It's free to start.

I think that to your point, like on analytics, you know, the, the fact that agents can help close the loop with, you know, maybe drafting some content, there's still a human review step, you're posting it, and then maybe the agents are helping to analyze what's working, what's not working, and seeing what's, you know, kind of um, catching fire out there from other people on, uh, in the content world, you know, I think it does create this like really high leverage, uh, circuit for people who know how to effectively deploy agents. So even if humans are still in the loop at points, I think that the amount of the loop or the, the, uh, percentage of the loop that is more agent driven is going to increase and increase and increase until at some point it's almost like, yeah, there's a human, but like that human is extremely leveraged.

Yeah.

And You could imagine building a company that you never would've dreamed of without any employees or with minimal employees. Now you can do that with agents.

Absolutely. And I see it with my content. We haven't really expanded the team. We're still hiring, but we are producing, I think, 3 times more content just because it's so much easier to generate that content. Of course, we have to check and everything, but one person can now handle like GEO and newsletter and also Threads. And another person can do 3 other outlets.

And maybe even like researching ideas. So like, You know, all the substantive work that goes into like going deep on a topic, like a lot of that can be enabled by agents.

So for someone who's excited about all of this, but also they don't know, like I am also confused. Every week there's something new. There's Claude with Cohere, Codex. Oh my God. Perplexity Computer. Amazing. HyperAgent. How do you choose? And I saw you use Claude as well. It's not like you're just choosing one tool.

What's the best Yeah, so I think maybe going back to our generational metaphor, you know, there was like the chatbot era and there were a lot of products that were built as chatbots. And, you know, now we have agents that are much more fully autonomous. So I first, you know, would separate products that kind of fall into the chatbot era from the agent era. Um, even within the same company like Anthropic, they have Claude, like the vanilla version, which is much more close to a chatbot. I mean, it is actually a weakly agentic, uh, product, so it can do a few turns at once, but you're not using Claude to go and go and, you know, work on something for 5 hours without human intervention, right? And this is Claude, like the end user product. Confusingly, they also use that name for their models and as a prefix to their other products like Claude Code and Claude Cowork. But the plain kind of end user Claude experience I think of as more of a chatbot. Um, likewise with ChatGPT, and that can still be very valuable. But, you know, when you think about like frontier agents that are actually able to perform, you know, maybe hours of human equivalent work autonomously. You know, you put into that category OpenClaw. You know, everybody kind of got excited about OpenClaw on Twitter because of what it could do. Um, I would put into that category Claude Cowork. Um, and then, you know, products like Perplexity Computer and of course HyperAgent. And then within that bucket, there's kind of, um, there's, you know, I think different, uh, options for, you know, depending on what you want. So what HyperAgent gives you and what we focused on is both The fact that you can do this in a much more team-enabled setting as you kind of refine their skills and memory. So we put a lot of emphasis into this, like closing of the loop for self-improvement, which I think is key because even though agents are out of the box very smart and they're only getting smarter as the models underneath them get better and better.

Most people use Claude like a search engine. They type in a question, they get an answer. Most times they're not really satisfied with it and they close the tab. I did the same thing for months and I was looking at people who were saying AI is changing their life and I'm like, Then I spent one afternoon setting it up properly, uploaded a few files about how I think and how I work, and it completely changed. I wrote the whole process up step by step. You get it when you subscribe to my newsletter Future Proof. It's free. The link is in the description. This is what I'm very excited to try. When you mentioned the team collaboration, we don't use Slack, we use Telegram. But I saw you have this Telegram integration. And the thing is, and it's so funny, like, I feel like the industry is moving At the same phase and think about the same problems. Because last week I was talking to my COO and I'm like, I'm giving so much feedback to my team in Telegram, which is inaccessible to like any bot really. So I have to download the conversations like, how do we close this?

Yeah.

How does the agent learn my taste? So what we're going to do, we're going to download the conversation, train the agent, but then we're going to add the bot to all the team chats that I have. So it learns my feedback and can give feedback. To me, instead of instead of me to my team.

Exactly. Yeah, and I think I mean one by the way as an aside, I think Telegram has a really interesting opportunity to become maybe the dominant platform in messaging for agents because they just have the best ergonomics of all these messaging platforms to be able to deploy bots. Right? You know, HyperAgent has a really first-class Telegram integration. Right? And even if you're not a current Telegram user, I might recommend for people to go and like. Set up a Telegram account because it's such an easy and free way to create both individual and group chats with your agents. And it's very cool actually to see in a group chat setting, you can add even multiple agents that you've created through HyperAgent and have them jump into the conversation as relevant and even start to talk to each other, which is very cool.

Yeah. Like even, even like give feedback because what I realize in my company, I'm the bottleneck because all the content goes through me and sometimes I'm doing this right and I can't get back to my team. What if I have an agent that already knows my taste and I say like on busy days, you just let it give the feedback.

Absolutely.

Yeah.

Yeah. I think that is one of the interesting emergent phenomena here, which is, you know, as people have gotten really into their agent building, like OpenClaw, uh, you know, you see all these OpenClaw fans who have created like a virtual twin of themselves in their OpenClaw instance, right? This is my like virtual Howie agent that has really learned so much about me and actually does have real-time access to the same context that I do. So it knows what my schedule is. Yeah.

It's crazy.

Yeah, it's like, you know, they talked about the singularity and like how we're gonna put ourselves into like a, a computer. And like, I mean, it's kind of actually happening with agents.

Yeah. What's the most unique use case with HyperAgent that you've experienced?

I personally like, um, you know, kind of these multimedia-related use cases. So what I mean by that is, you know, sometimes for fun and sometimes for like actual kind of, you know, functional marketing purposes, I like to have Uh, HyperAgent go and create like marketing ideas. So, uh, at one point, uh, we actually did do a billboard, a small billboard campaign for HyperAgent announcing the launch of it. And I had it go end to end sourcing the actual billboard location. So we worked with a, um, a vendor that had like, uh, basically a list of all the billboards that were available.

One-on-one or are you doing it here?

What's that?

Are you doing it on one-on-one?

Uh, it was in New York, LA, and SF. And, uh, and so we grabbed all the inventory. And then it had all the specific locations, like what street it was on. And then HyperAgent was able to process all of those locations, cross-reference them with Google Street View and Google Maps. So it can literally put them on a map and then even show like the Street View point of view of like, here's what that billboard looks like, um, on the street. And then best yet, because it, it, it's very versatile in terms of being able to chain together different tools, um, it was able to take those Street View images and then pass that into leading image models like Nano Banana, and then use that to generate a really high fidelity mockup of what our billboards would actually look like. Um, you know, so it took real-world location shots, mashed that up with like our actual kind of campaign, uh, imagery, which it created based on the concept, and then could help us visualize like, here's literally what that, um, that billboard on Sunset will look like.

That's amazing.

Um, I thought that was very cool. And then, you know, I think like, um, we ended up not, you know, like we weren't around, uh, long enough to do a Super Bowl ad. We just started HyperAgent basically around the, uh, the holidays. you know, had we done a Super Bowl ad or maybe for next year, you know, I, uh, used HyperAgent, uh, to, to go and generate some like actual video concepts, right? So again, it's able to like come up with concepts combining, you know, real product marketing understanding of like, what does this product do? We fed it or gave it access to our documentation for HyperAgent. So very, um, meta, but like HyperAgent was then able to learn about all of the capabilities and differentiation of HyperAgent. Oh, that's cool. And then to be able to go and come up with really good marketing concepts that it could cut up into different scenes, like a script. Screenwriter or like a director of an, uh, you know, a Super Bowl ad script and then actually generate really high-quality production-grade videos using, uh, Veo in this case, uh, from, from, uh, Google. Um, so that it actually looked like a real Super Bowl ad. So I think, um, you know, I like the creative, uh, creative use cases because they're just so immediate and, uh, and visceral. Um, but of course I also have like many functional use cases, chief of staff, uh, use case where it's reading my emails and Slack all the time and pushing me anything that needs my attention. So saying, hey, you just got this really important email. from somebody, a customer or a partner or an investor, you should probably respond to this. And here's even a drafted reply.

Can you show me some of your productivity use cases? Because this is where I see a lot of my time being saved when I optimize stuff with agents.

Okay, so this is a, this is actually a demo account of mine that's realistically recreated based on my actual usage. Um, my actual usage has everything of mine, like all of my, uh, uh, you know, like calendar, my emails, everything. So it's a little sensitive. Either you can have it go on a recurring schedule or like similar to OpenClock and have a heartbeat mode where it's always, you know, waking up and checking new stuff and then pushing you messages either via Telegram, it could be via Slack, it could be via email.

Yeah.

But you can kind of set it up how you want. Um, I like Telegram because then it just feels like it's almost like a personal assistant, like messaging you all the time. You can respond to it. I mean, especially Telegram, if you have the bot living in your group channels already with your team, then you could just @mention the bot and say, hey, you know, go research this thing on behalf of the team.

Go create caption for this post.

Exactly. Okay, so here's one that, uh, is one of my personal favorites. So obviously you have to be on top of Twitter or X like 24/7 now to like keep up with all the latest news. It's all happening so fast. It's kind of overwhelming. And sometimes I feel like I just like, I forget to check X and I miss some really important stuff. So I have one agent whose entire job is just to constantly watch X. Mm-hmm. And literally it's like doing this like all the time, 24/7. And then it's making a judgment call. It knows enough about me and what I care about and Airtable and HyperAgent that it can push to me messages alerting me, you know, when there's something interesting, only when it's actually relevant to me. Mm-hmm. Right. And it can even like frame this around like, why is this relevant to you, to Howie? Um, but I—

Interesting how social media's, uh, transforming. 'Cause I see a lot of people doing this. Yeah. 'Cause once you enter X, you Forget your life.

Totally. So you can go down a long rabbit hole.

Now it's your agent consuming content for you.

Exactly. Yeah.

It's an interesting shift for social media in general.

Well, and you know, it's like agents consuming the content, but then, you know, also probably agents helping to create the content. And so, you know, there's, uh, it's, it's this funny loop of like what happens when it's really just like our agents posting and consuming all the content on our behalf, right?

Exactly.

Um, so this is a favorite one of mine. And one thing you can do here is like if you want to set up, a live mode agent, you can actually click that dialogue button, um, or just ask it in the feed or in the, uh, in the thread, turn this into an, an always-on agent and push me messages via Telegram when you see something interesting for me. Right. And then it will set it up. It will walk you through the flow. You can set up like a Telegram bot.

You're doing this now and I'm realizing a few months ago we built this system that pushes us notifications about videos that are underperforming.

Okay.

Took us a few days. Yeah.

Yeah. And by the way, even a few days is far better than a few months or a few years, right? Like it would've before.

But it's still, this is such a, like how technology progresses these days. Yeah. You have to be always on.

Yeah.

Always testing.

Yeah.

'Cause there's new, this new product's coming out.

Yeah. And I think, I mean, one of the cool things, if I take a step back and think about the state of tech right now, like I've always believed that you can choose to make tech like an enabling tool, right? Mm-hmm. In fact, like when we founded Airtable, we spent a lot of time studying the history of like personal computing, the Macintosh, Microsoft. And it's quite interesting because like at one point, you know, all of the major like previous era computing companies scoffed at the idea of a personal computer, right? Like they literally laughed at it. They were like, oh, nobody would need a personal computer on their own desk, let alone like they didn't even think about smartphones.

Mm-hmm.

Um, and you know, the idea that obviously Apple and Microsoft had was like, wow, like these processors are getting cheaper and faster. And in fact, like instead of using that to do even more arcane and like specialized work, what if we made this even more accessible? What if we chewed up all of that computing power to make computers something that anyone can use and get value out of them? And I think there's a very strong parallel to models and like as the models get smarter, yeah, you could apply them towards very, you know, kind of complicated use cases, like hire Palantir for like $300 million to do like a very complex, like like, you know, government deployment of AI. But also the alternate point of view is you can use it to enable people to do even more broad and interesting and ubiquitous things, right?

Absolutely.

So I'm personally a fan of like the, you know, kind of democratization angle. That's the entire founding premise of Airtable was democratizing app creation. And I think now we have a very similar opportunity to do that for agents. And like, you know, I really think like there's gonna be 2 paths of agents that are more and more powerful but inaccessible.

Mm-hmm.

And then agents that are actually more and more friendly and accessible and useful to as many people as possible.

Yeah. I just saw you speak on stage.

Yeah.

And you said builders, yeah, are gonna win.

Yeah.

In the next, yeah, few years. How do you adopt the builder mindset?

Yeah, I mean, I think what really being a builder comes down to is one, like having the appetite to tinker. Like that's the most important thing, right? Because I think it's a humility to say like nobody knows all the answers. Like if somebody tells you like, Here's exactly how to build the perfect agent for every single use case and every single company out there. Like they're full of it because there's no way to prescribe that so perfectly. Like it's constantly changing. And what's really cool about the builder community out there already, uh, on X, for instance, or like on Reddit, et cetera, is you're finding that people are like almost accidentally discovering the best ways to use agents, right? Like, you know, they're learning, hey, you know, it turns out like one way to make the agents very, very good at content production is to Give it this kind of a skill with this kind of guidance, right? Or maybe create a skill from, you know, the MrBeast leaked handbook on like how to create content. Like, you know, it turns out when you feed that into the agent, have it develop its own skill informed by that, it does really well, right? Um, and so, you know, there's all of these emergent practices that actually make these agents work better and better. And the only way to go and kind of like really, you know, get good at it is to try it out, right? And the great thing is like, you know, there's no, you know, kind of masterclass, there's no PhD that you need for it. I mean, I'm sure you could take some great classes out there, but you don't really have to, right?

Yeah.

And like, you know, if you have nights and weekend time even to go and just play around with the agents, and it's quite fun to use, I think that's the best way to actually get into it. So the tinker mindset is most important first and foremost. And then I think the second is really just a willingness to really distill down like what is the, work in order to generate the output you want, right? I think some people, um, you know, have an easier time imagining, you know, what is the ultimate purpose of, let's say, software engineering or sales or marketing or, you know, content creation. And if you are stuck in, in, in terms of thinking about it as like the activities that you currently do, so software engineering, the activity of writing code by hand, line by line, is now gonna be obsolete, right? So—

Same as scriptwriting.

Exactly.

Yeah.

Yeah. But if you can rethink the, the work as being, how do I generate great software? How do I output great code and great applications and get to go up in the abstraction to like have a team of agents that actually do that work for me? Or, you know, same for scriptwriting or content. Like, I think then you're able to really effectively leverage agents because you're thinking about the outcome first.

Mm-hmm.

And then how do you use these awesome you know, capabilities to generate that output versus being stuck in the activities of before? You know, I think like a lot of it is just like getting that starting point, right? Like, you know, it feels sometimes very daunting to get started. Like I personally, every time I try a new generation of AI or products, you know, it, it always feels like it, you know, a little intimidating. Yeah. Like how do I get started? Like, you know, over the holidays I personally got back into, uh, software development, uh, in a really big way. Like I had done some tinkering before, but, um, with the latest family of models, like I actually started building like with code again, right? And using development agents. And at first it was like, you know, like I just picked some low stakes projects to, to do like for fun and got so immersed into it that by the time I personally started working on HyperAgent in code, like, you know, it was already very like exciting. And, you know, I had built up some confidence around like what I could do with the agent.

Yeah.

So I think, you know, the, the, um, the really empowering thing is like you can start with anything like low stakes, personal use cases, but that helps you develop the confidence and the fluency to then go and bite off something even bigger. Yeah. You could have a whole agent just dedicated to helping you prepare for that. And you could even have a meta agent that itself is running 24/7 to discover new opportunities for additional agents, right?

Oh, that's amazing. So like, this is, do you have that agent? No, I think it's, it's genius.

You know, it's, I, I don't have one right now other than my chief of staff, which is constantly like looking through all my stuff and suggesting like follow-ups. And sometimes it will suggest additional agent use cases, but I should, um, you know, I wanna have like a weekly Yeah. Weekly review, look at everything I did, and then come up with additional agents that you should hire basically onto your team to automate even more of what happened over the week. So this one, I'm just setting up like the final parts of the, um, the Telegram flow. But, you know, in short, like it will help me walk through the configuration to actually turn this agent into an always-on Telegram agent that will then push me messages.

When something's happening on X. Exactly. Yeah.

So I gave it some, some feedback on, um, On what I wanted to do.

You should set up an agent for kids' school emails.

Yes.

Yeah. Now that I'm thinking.

Well, I mean, now that we're talking about personal use cases, like I have some fun ones which are, um, you know, I'm in the market for a used car right now. And so it actually, uh, I have an agent that's monitoring all of the used car listing sites and then finding cars of my spec. I want a convertible, uh, here, you know, we're here in LA. It's a great place to have a convertible. And it will go and do extensive research on the price point I want and And like, do the cars have the specs that I want? And even like, you know, what, um, what are the, uh, you know, locations? Like, let me click through and like see where it is and more details. Um, but you know, just like fun personal use cases that I wouldn't have otherwise hired like a person to go and monitor.

Now I'm thinking I need to book my flights to Cannes. I could basically build an agent that goes through all my points that I have on different credit cards and find the right—

Oh yeah. Yeah. For a points optimizer, like use the points effectively. Even help you like plan out like with a map, like all the different places you want to go. So yeah, it's a very fun time.

Yeah.

One, you know, I, I saw this, uh, term referenced in a, um, like one of the AI forums I'm in. But, you know, one way to think about agents is like, I mean, obviously you can use it in your core job, but it also enables you to go and make all these luxury hires that you otherwise wouldn't go. Like maybe you wouldn't hire a full-time travel concierge, right? For your team. Right. Like it just, that would be like too, it wouldn't be worth like a full-time hire. But now with an agent, you can literally have an agent whose full-time job, even running 24/7, is to find ways to optimize your points, find like new, you know, itineraries that are surfacing from your email. Like it knows, oh, maybe you need to go out and do this kind of a, you know, this kind of a promotion or this kind of like an interview. And it will, you know, automatically go and propose, here's the flight itinerary, here's even like the way that you can optimize your points for this trip. Exactly.

Yeah. Yeah.

So, you know, it kind of allows you to just imagine all these, like, if you could hire as many people as you wanted for almost zero cost, right? Like, what other roles would you hire people into? I think that's a very cool thing too, is, you know, a lot of people are worried rightfully about, you know, what jobs will look like in the coming years. But I think that actually, like, some of the most interesting use cases of agents are going to be not necessarily replacing existing human jobs outright, but actually enabling completely new jobs that weren't being done because, you know, it just wasn't worth it to have like a full-time hire to do something.

Yeah.

So, you know, you're able to like go and do incrementally so much more that puts you ahead, right? Personally and as a business.

If I'm running all these agents, I'm getting all that information, like learning how to live in that environment where, yes, they source a lot of stuff for you, but then you're still the end decision maker.

Yes.

So it's a lot of decisions now.

Totally.

Which actually is founder's job, right? You're not, you don't have to be building. You have to be making those big decisions for everybody.

It's like the judgment, right? Like that's the thing I think like a common thread is like, like, you know, the thing that scales the most and gives you the most leverage in the agent world, and, you know, it was true in the human world as well, is good judgment, right? And how do you apply good judgment as efficiently and to as many different threads as possible?

Mm-hmm.

And I think the people who are able to do that most effectively will become like almost superhuman, right?

Yeah.

Like, you know, you will have this team of agents that you're able to give good judgment and feedback to, just like a really effective CEO of humans, right? Like, that's what discerns a good CEO of humans versus not is ability to scale good judgment.

Yeah. Yeah. And you scale it by making more decisions, I guess, and seeing how they work for you, right?

Yeah, absolutely. And maybe like iterating, experimenting more, having agents try things that you otherwise wouldn't have tried. Like maybe you can do new content experiments, right? Or new business model experiments. Like, hey, what if we built our own, you know, kind of brand, uh, and or microsites around these different kind of opportunities? Uh, for Airtable or for HyperAgent, you know, like we can actually go and execute on way more like marketing programs or even like product, um, you know, features than we would have before. And not all of them will work, but like we just get way more at-bats.

Okay. My last question for anyone who wants to start with agents today, first 3 steps.

Um, one is obviously sign up for HyperAgent and, um, you know, we, uh, you know, we try to make HyperAgent Really, really in non-intimidating, right? So it's got a very great GUI experience. You don't have to go in and like do technical setup. It's kind of like using the Mac, right? As opposed to like setting up Linux. And the second is like just come up with like a few personal use cases or low stakes work use cases. I think problem hunting, like figuring out like what are the problems you want to solve is like 80% of the battle, right? Because it turns out the actual building of the solution is no longer so hard. Like compare this to the prior era where like Let's say you wanted to build custom software even before no-code, and you wanted to solve a problem with like a custom app. Okay, well, you could pick the right problem. You need to track, let's say, all your brand deals, but then actually writing the code to build the app is like all of the effort.

It's not worth it. Easier to hire someone. Yeah.

And so now I think really it's kind of inverted where the, the most interesting part, and actually the part that you should spend the most time on upfront, is just coming up with a list of like, what are all the problems that I wanna solve? And then third is like, have fun with it. I think that's the most important part too, or that's a really important part too, is, you know, this has to become like a passion. I think like the best agent users and builders I see really kind of enjoy it, right? Just like, you know, if you were an early internet user, you had to kind of enjoy it, right? Like there's a functional purpose to it, but also like, you know, it was just fun to go online and like, you know, see what else was out there, shopping sites and like news sites and games and, and so on. And so there is this like interactive and like just kind of very dynamic nature agents that I think to become truly fluent, you have to have passion, you know, technology fit, right? So like try to enjoy it. And that's why I think like also picking the lower stakes, you know, kind of fun use cases where you get to really experiment rather than putting all this pressure on yourself up, upfront to like deliver some kind of ROI.

Mm-hmm.

Like it's just like any other new and disruptive tech, computers, the internet, the iPhone, like to really understand how to apply it in a very efficient and effective business way, you have to first Really kind of, I think, immersed as a consumer of it.

Yeah. And 2 skills everyone should be working on from what you're saying, the skill to figure out the problem to solve.

Yeah.

And the skill to make the right call, the right judgment.

Yeah, absolutely.

Yeah.

I think those will be the 2 most important things and effectively mastering them, I think, makes you into superhuman in this era. Exactly.

Exactly. And we're living in an age where everyone has the potential to become a superhuman in less than, I think, a couple Yeah, yeah.

I mean, seriously.

It's a very, very speedy process.

Yeah, I think we'll see a lot more entrepreneurship too. I think like, you know, the era of like one person building a great company, you know, whether it's like the literal billion-dollar revenue company that was forecasted with AI, or, you know, it could just be, it doesn't have to be a billion in revenue to still be successful. But I think a lot more people are gonna be able to get off the ground with their own ideas and build a business, whether it's an online retail business that, you know, before they couldn't have afforded to hire the team to market it, to source the inventory, to build a site. Now you can do that all yourself. with agents, right? Or it could be a content, you know, kind of business, or it could be like a software business. Like all of these businesses, I think, are now much more possible for anyone out there who just has the idea and sees an opportunity.

Yeah, it's amazing time to be alive. Thank you so much, Howie. And thank you so much for the product.

Of course.

Yeah.

Thank you.