How agents will change banking forever | E2260

This Week In Startups is made possible by: Northwest Registered Agent - ⁠⁠northwestregisteredagent.com/twist⁠⁠ Quo - ⁠⁠quo.com/TWiST⁠⁠ Gusto - ⁠⁠Gusto.com/twist⁠⁠ Plaud - http://Plaud.ai/twist Athena - https://www.athena.com/jcal Today's show: How long until AI models can improve AI models? Once possible, recursive self-improvement by AI technology could accelerate — forever. Thus far, humans (and their coding agents) are still driving AI progress. But a recent project by AI developer extraordinare Andrej Karpathy, called 'autoresearcher', is turning heads as it shows that it is possible — in certain contexts — to allow AI agents to run successive coding experiments to improve specific elements of LLM performance. Call it an early demonstration of the future. OpenClaw is exploding in China, while here in the United States, AI is polling somewhere underneath the basement. AI in the United States is about as popular as ICE, which could create a political issue for the technology in the coming elections. Next? Three demos. First, NetXD's Suresh Ramamurthi showed off how he has built OpenClaw functionality to move money, Rohan Arun showed off PhoneClaw automation on Android devices from an AR headset, and Eugene Stuckless gave us a taste of what Eir is building. Our takeaway? OpenClaw is still boring its way into our digital lives, one new skill or tool at a time! GUESTS: Suresh Ramamurthi: ⁠⁠https://x.com/sureshr7⁠⁠ Rohan Arun: ⁠⁠https://x.com/Viewforge/⁠⁠ Eugene Stuckless: ⁠⁠https://x.com/eugene_eir_inc⁠⁠ Timestamps: 0:00 — 'Autoresearcher' and the future of AI improvements 6:52 — Why people around the world are flocking to OpenClaw 7:57 — Plaud - If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at Plaud.ai/twist and use code TWIST for 10% off! 9:46 — Gusto - Check out the online payroll and benefits experts with software built specifically for small business and startups. Try Gusto today and get three months FREE at Gusto.com/twist. 12:57 — The changing American social contract 20:15 — Quo - Quo (formerly OpenPhone) gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at quo.com/TWIST 23:50 — Why China is all-in on AI (and Europe isn't) 26:26 — How to keep your job in the AI era 28:05 — Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at www.northwestregisteredagent.com/twist 29:38 — Athena - Get $2,000 off your first EA at https://www.athena.com/jcal 34:42 — Demo: Suresh Ramamurthi of NetXD 42:47 — Demo: Rohan Arun of PhoneClaw 47:35 — Why bringing OpenClaw to your smartphone is what's next 49:49 — Demo: Eugene Stuckless of Eir 56:45 — How can we make smarter, more efficient agents? Subscribe to the TWiST500 newsletter: ⁠⁠https://ticker.thisweekinstartups.com⁠⁠ Check out the TWIST500: ⁠⁠https://www.twist500.com⁠⁠ Subscribe to This Week in Startups on Apple: ⁠⁠https://rb.gy/v19fcp⁠⁠ Follow Lon: X: ⁠⁠https://x.com/lons⁠⁠ Follow Alex: X: ⁠⁠https://x.com/alex⁠⁠ LinkedIn: ⁠⁠⁠https://www.linkedin.com/in/alexwilhelm⁠⁠ Follow Jason: X: ⁠⁠https://twitter.com/Jason⁠⁠ LinkedIn: ⁠⁠https://www.linkedin.com/in/jasoncalacanis⁠⁠ Great TWIST interviews: ⁠⁠Will Guidara,⁠⁠ ⁠⁠Eoghan McCabe⁠⁠, ⁠⁠Steve Huffman⁠⁠, ⁠⁠Brian Chesky⁠⁠, ⁠⁠Bob Moesta,⁠⁠ ⁠⁠Aaron Levie⁠⁠, ⁠⁠Sophia Amoruso⁠⁠, ⁠⁠Reid Hoffman⁠⁠, ⁠⁠Frank Slootman⁠⁠, ⁠⁠Billy McFarland⁠⁠ Check out Jason's suite of newsletters: ⁠⁠https://substack.com/@calacanis⁠⁠ Follow TWiST: Twitter: ⁠⁠https://twitter.com/TWiStartups⁠⁠ YouTube: ⁠⁠https://www.youtube.com/thisweekin⁠⁠ Instagram: ⁠⁠https://www.instagram.com/thisweekinstartups⁠⁠ TikTok: ⁠⁠https://www.tiktok.com/@thisweekinstartups⁠⁠ Substack: ⁠⁠https://twistartups.substack.com

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Jason Calacanis?

  All right, everybody. Welcome back to Twist Monday, March 9th, 2026. Lots going on. Alex, how you doing?

• 0:06Speaker 01

  I am fantastic. The snow's melting. I'm finally coming out of winter. Tank top season's around the corner. So, Jason, I'm happy.

• 0:15Speaker 02

  This Week in Startups is brought to you by Northwest Registered Agent. Get more when you start your business with Northwest. In 10 clicks in 10 minutes, you can form your company and walk away with a real business identity. Learn more at northwestregisteredagent.com/twist. Quo, founders move fast. Their phone systems should too. Quo, formerly OpenPhone, gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at quo.com/twist. And Gusto. Check out the online payroll and benefits experts with software built specifically for small businesses and startups. Try Gusto today and get three months free at gusto.com/twist.

• 1:00Jason Calacanis?

  What's the top story in our world? Startups, venture capital, technology?

• 1:05Speaker 01

  You know, I think it has to be the Andre Karpathy auto research story. We've talked so much as an industry about the future of AI models eventually being able to improve themselves, getting that loop going. And then at that point, we have real takeoff towards superintelligence. But in this case, what Andre has done, and if you don't know him, he's a former AI head over at Tesla. Jason, he's just one of the best and most followed developers, I would say, in the world. Fair?

• 1:30Jason Calacanis?

  Yeah, for AI specifically, obviously worked for Elon for a long time. So, yeah, that he would be, you know, top 20 recognizable names in the space.

• 1:41Speaker 01

  Yeah. So when I see his stuff, I immediately take a look at it. And in this case, he has put a tool called Auto Research over on GitHub. And what this is, it's a really stripped down LLM training loop, and it runs in five-minute increments. So you bring your own AI model to be an agent essentially, and then you give it a prompt. And then what the system does is try to improve its own code over a five-minute training period. Then it retests itself. And then if the code is improved, if the result is Improved, it keeps the changes and it continues to iterate. So it's a very simple loop of AI actually improving itself across certain tasks that you give it. So it's not the full meal deal, Jason. We haven't solved AI recursive self-improvement,

• 2:26Speaker 01

  but we have shown that it's simple and possible in some contexts. Very cool.

• 2:29Jason Calacanis?

  Yeah, and he worked at OpenAI, I think twice. He was like in between stints at Tesla or maybe Tesla was between the two OpenAI stints. So he knows what he's talking about. I think he started, he was one of the founders over at OpenAI in 2015 timeframe. So I think, you know, without being an AI researcher myself, what we're seeing here is as the models get smaller, as people get more comfortable with running a local model. This isn't like an abstraction. There's tons of open source models and then people are building scales. People are running tests and people are interested in playing with this technology. As they become interested in playing with technology, you'll have somebody like Toby from Shopify,

• 3:13Jason Calacanis?

  who on the weekend is like, I'll try. And the next person tries and this is all claw pilling and just having folks, you know, get excited and tinkering with this technology. So it's kind of like the horse has left the barn in my mind. If Toby Lutke, the CEO of Shopify is like, you know what? I'll try using this. I have no experience in this. Let me give it a shot. And as you can see here from the tweet, he had some success.

• 3:45Speaker 01

  Yeah, so he went ahead and gave it a try over the weekend. By the way, all CEOs are dangerous now because they have Claude code and they can tinker. So if you're a developer who elected as the CEO far from the code base, it's going to be a tough couple of years. Anyways, he ran some tests with Auto Research, the tool, and he says, I'll just quote here, woke up to a plus 19% score on a point eight B model. So 800 million parameters, Jason, very small, higher than the previous 1.6 billion parameter models result after eight hours and 37 experiments. So essentially his auto research setup ran 37 different tries of five minutes apiece and over eight hours managed to find. Nearly a one-fifth improvement in results. He says, look, I'm not an ML researcher. I presume people are doing this in the labs at a much, you know, more sophisticated level.

• 4:29Speaker 01

  But he learned so much from doing this because you can watch how the AI thinks as it goes through the process. The other thing to keep in mind is the gains that we see, here is an image from Andre himself showing progress. This is eighty-three experiments, of which fifteen had improvements. The gains, Jason, as measured by declines in this particular axis, do seem to get smaller over time. So there is a diminishing level of return here, but it works. It works.

• 4:54Jason Calacanis?

  I think people are going to keep experimenting with us with this and the idea that there's only three thousand or so PhDs in AI who are fought over for ten million dollars a year, a million dollars a year, a billion dollar package, whatever it happens to be. We've seen these crazy numbers from Meta trying to catch up and people poaching each other back and forth. That three thousand will turn into three hundred thousand people who understand how LLMs work and who can make meaningful progress on them. And that's great. You know, we used to live in a world where only a small cohort of people could make iPhone apps. Only a small cohort of people understood how to

• 5:36Jason Calacanis?

  use at-scale databases. So, you know, it's a, it's a interesting time to be in. And if you are an AI researcher, getting in there and playing with it, just like you have knowledge workers like you and I, Alex, who maybe weren't developers or maybe had toiled a little bit, being able to vibe code, being able to use Claude Co-Work to make a reoccurring job, being able to install OpenClaw, being able to write a skill, maybe publish it to GitHub. This is the dam-cracking from the developers owning the world to everybody building the future. And I'm here for it. It's exciting.

• 6:17Speaker 01

  It's very exciting. It is democratizing. And I hope also that what we're seeing here on the edges of public AI work is happening inside AI Labs at like twice the speed. Because if this simple setup can show, you know, AI-driven improvement of AI. AI outputs, then we must be cooking really, really fast in XAI, OpenAI, Anthropic, etc. So to me, this shows that yes, we can tinker, yes, it is democratizing, but also the pace of improvement in AI this year should be insane. And that's very bullish for startups, for VCs, for everyone who's put money behind a data center. So I think this is one of the most bullish stories that I've seen in in weeks, if not months.

• 6:52Jason Calacanis?

  Yeah, since OpenClaw, I guess.

• 6:54Speaker 01

  Really quickly, I want to talk about the US public, AI, and then China and AI. There was a big boom in OpenClaw over in China. I thought this was just a thing that I saw over on Reddit, people posting pictures of GitHub, sorry, OpenClaw meetups. Here's a screen, an image, Jason, of one of those meetups. In case you're curious what that looks like, here are people outside in Shenzhen teaching each other how to set up OpenClaw. You can even see OpenClaw right over there in English.

• 7:23Speaker 01

  I thought it was kind of crazy. You know, this is so cool. People are really getting into it. It turns out also there are certain governments inside of China that are setting up incentive structures to get more people to use OpenClaw. All of that to one side. Over here in the US, there's a new poll that came out that showed that AI here in the States is incredibly unpopular. So we get kind of a split screen here between people in China, even older folks really diving into OpenClaw, and here in the States, poll numbers that are pretty terrible. According to the NBC poll, Jason, 26% of people in the US are pro-AI and 46% are opposed to it for a negative 20% differential. I was surprised by this.

• 7:57Jason Calacanis?

  All right, I'm going to give my opinion on both of these stories after we talk about Plod.

• 8:03Speaker 01

  Yes, Jason, we've been talking about the Plod note pen tools, essentially a great way to get all your audio from your ambient area into your device or into your personal cloud. You are a big note-taking guy. You absolutely love a checklist. Tell people why Plod has a place in their life.

• 8:17Jason Calacanis?

  Yeah, it's pretty straightforward. I have the Plod pen here. It records what I'm doing. Obviously, you know, you want to do this with disclosing to people you're doing it. And when you're in a meeting, instead of like fumbling with your phone and trying to find a recording app, you put this on the back. See this? This is the pro. And when you press the button, hold it down, it gives you a nice haptic, tells you how many, how much battery life is, it's got a little LED on, how much battery life is available, and you hold it. And now it does a little recording stream. I don't know if you can see that audio stream going there, just to let you know it's working. And that means one click, you're recording, then it syncs it with your device, whether it's the PIN, whether it's the Pro, and you're all set, you're ready

• 9:01Jason Calacanis?

  to then transcribe it, put it in the cloud, and it will do a straight up summary. It will do a mind map. There's a whole library of different ways for you to use your Plaid. And it's a game changer for me, because I frequently forget things, or I get inspired in a flurry because I'm hiking, or doing some ranch work, or, you know, the kids are getting dropped off at school, and then I'm like, oh, I remember, I have an idea for the show. Boom. I just say action item. Boom. I say, hey, book this person for the show. So go to plaud.ai/twist, they'll give you 10% off.

• 9:34Speaker 01

  We do a lot of notes here at Twist, so we live in denial of our ability to keep our information straight. So shout out to Plaid for sponsoring the show. Now, Jason.

• 9:41Jason Calacanis?

  Yes.

• 9:42Speaker 01

  Over in China, open claw.

• 9:43Jason Calacanis?

  Yes.

• 9:43Speaker 01

  Boomy, here in the US.

• 9:45Jason Calacanis?

  Gusto is a musto. You've heard me say it a million times. It's true. Now more than ever, Gusto is a musto. They're going to save you so much time on your HR. Gusto is the essential payroll and benefits software built for your startup or small business. It's all in one, remote friendly, and incredibly easy to use. So you can pay, hire, onboard, and support your team from anywhere. We use it. We love it. My team loves it. Everything in HR settled down when we went to Gusto. No more drama. People want a perfect HR platform, and Gusto is that platform. They make it fast and easy to move your data over. They're an ideal place to get started with basic payroll for your new business. They can also provide more comprehensive services to help you

• 10:29Jason Calacanis?

  scale up. I think we have 22 people on payroll now. And Twist listeners are going to get three months free when they run their first payroll. So try Gusto today at gusto.com/twist and get three months free when you run your first payroll. That's three months of free payroll at gusto.com/twist, G U S T O dot com slash twist. Two separate issues. The claw thing is happening all over America. And it's open source. And what's great about open source is when something trends, everybody embraces it. We've never seen a project get embraced.

• 11:05Jason Calacanis?

  As quickly, as violently, as lovingly, as OpenClaw. It's number one on GitHub. It has the largest number of stars. Why is that happening? I would say it's two reasons. First and foremost, people are getting value from it. Second, it's inspiring for people because if they're starting a company or running a business, or they want to stand out at work, they can use this tool to be a better performer. So, high performers are drawn to this. And there are tons of high performers around the world. Obviously, in China, you've got a lot of aspirational people. If you're aspirational, you're pulled to this. Now, there are normies. There are citizens.

• 11:46Jason Calacanis?

  There are human beings who might not be looking to make a career, and they might not live to work. They may work to have a great life, and there's nothing wrong with that. So, you're not seeing like these OpenClaw things happening in France. I don't think like people are like, you know what? Instead of going to the bistro tonight, I'm gonna go do a Claw meetup. Maybe they are. Who knows? I don't want to give a hard time to the French.

• 12:13Speaker 01

  March 19th, OpenClaw meetup, Paris. It's at 5B Rue de Bois, which is French, apparently.

• 12:19Jason Calacanis?

  We'll see if like six people show up or whatever. But anyway, the second piece to this does dovetail with it nicely, which is, people in China feel like AI is gonna make their lives better. They've recently seen their lives get better. They have an immediate history that they can look back on and say, hey, for 20 or 30 years, we've watched people go from living on a farm without running water or sharing a cold spigot between three or four people. This is literally reality, you know, in China. No electricity or limited electricity in the village, to working in a factory, living in a dormitory. The dormitory has, you know, air conditioning or heat. They have some spending money. They can go to a bar. They can go, you know, have lunch somewhere.

• 13:04Jason Calacanis?

  They can start to build a life for themselves, eventually get an apartment. So, they've seen this, so they're excited about the future. Now, you go compare that to America. People have for the last two generations said, I've gotten 400K in debt, 200K in debt with my degree, etc. And, since I'm in debt, then I can't buy a home. And if I can't buy a home, and my job out of school is paying me 50 grand a year, and I'm 250K in debt, I'll never get out from under. So there is like a resentment that's brewed over 20 or 30 years. And if you pull up the chart of what people don't trust in America, you know, it has gotten really acute for a couple of groups of people.

• 13:46Jason Calacanis?

  Obviously, the government, obviously journalism and media. Both parties seem to have had their reputations just become completely untrustworthy. And obviously, AI.

• 14:00Speaker 01

  So Jason, here is the polling data that we're discussing. This is from NBC, and I've gone ahead and highlighted a couple of things so people can read it. Essentially, here in the lower red box is AI. As you can tell, based on this poll in March of 2026, 5% of people are very positive in the US about AI. 21% somewhat positive, neutral, 27%. More people than I thought were neutral. But on the somewhat negative and very negative, it's 24 and 22%. So many more people on the negative side. And people are pointing out on Twitter and other places that ICE, Immigrations and Customs Enforcement, a very controversial, I think it's fair to say, agency of the government, has a 38% return of people saying very or somewhat positive sentiments about it.

• 14:42Speaker 01

  So AI in the US is somehow less popular than ICE.

• 14:47Jason Calacanis?

  Well, if you, there are some extremes going on here. So let's look at the extremes here. If we put the two numbers together, 24 and 22, somewhat negative, very negative, you get 46% of people are very negative or somewhat negative. They're negative about AI here in the United States. Now, if you look at the ICE ratings at their peak, because you have five dates there, but March 2026. When we go back to this data here and you look at March 26, 47% very negative, 9% somewhat negative. You put those two numbers together, you get to 56. So, you know, the ICE is still, in terms of total negativity, eking out AI. But it should be concerning to people.

• 15:31Jason Calacanis?

  And then if you look at, I'm assuming when they say Iran, they're looking at it negatively. They're talking about either the war or I'm going to guess it's more the government of Iran. I'm not sure.

• 15:42Speaker 01

  I think it's the government. I forget the exact phrasing of the question, but it was, what is your opinion about item? And then it's somewhat positive, very positive, negative.

• 15:50Jason Calacanis?

  Great. So if you put those two numbers together, 61% are negative or somewhat negative better on. So why is AI as unpopular as a brutal dictatorship that murdered tens of thousands of peaceful protesters and ICE agents, an agency that has, you know, had two deaths, whether you consider them murder or not, I'll leave that to the investigations. I have a theory of why AI is so unpopular in this country. And it's that the industry and has done itself no favors in terms of explaining itself. The second is, we have

• 16:31Jason Calacanis?

  seen a social contract in America be broken. In big tech and in large corporations in America, it's just not limited to big tech and some big tech companies are not just tech companies, like Amazon is a e-commerce company, right?

• 16:48Speaker 01

  Sure.

• 16:50Jason Calacanis?

  There was an explicit agreement that if profits were going up, compensation, bonuses, and headcount would go up. These two things were tied to each other for the history of modernity. The company's doing well, raises. The company's not doing well, okay, we're going to freeze raises. Oh, the company did well this year, you get a bonus. Oh, the company lost money this year, hey, the bonus program's on pause. And everybody was like, hey, that's reasonable, right? We're all working together, swimming in the right direction. And they said, hey, you know, if things go well, yeah, your group, oh, you're in the sales group, you're in the customer support group, yeah, we're going to, we're going to get you a couple of extra headcount. You'll have, you, you won't have to work the weekends

• 17:33Jason Calacanis?

  as much or burn the midnight oil. We understand you need more headcount to hit the goals. And hey, why not? The company's growing. For the first time in the history of America, we're seeing that flipped. And it used to be if profits are surging, if profits are surging, bonuses and headcount will increase. Now profits are surging, and now profits are surging because we're lowering comp and moving jobs offshore, or we're cutting headcount.

• 18:06Jason Calacanis?

  This is apparent to Americans now. They see it themselves. And they also, the gig economy is a major contributor to this. Everybody in their family knows somebody who maybe they didn't fit in in corporate America. Maybe they weren't able to get up in time and do the nine to five thing. And this magical little thing, press a button, get a job, came out. It got criticized. Oh, my God, you know, you don't get benefits, whatever. But let's call it what it is, Alex. We all knew somebody. I don't want to call them an F up, but they just didn't fit into the nine to five gig. And when they were able to, or maybe they were a stay at home parent and only had four hours and they wanted to spend time with their kids, which is, that's actually laudable.

• 18:51Jason Calacanis?

  But we have somebody in our life who's like always down on their luck. They get fired, whatever, and all of a sudden they became their own boss. They started doing DoorDash, they started doing Uber. They might have done Winola, all these other services where you get, you can do shift work or make your own hours gig work. They see that going away. So you see two things happening concurrently. Hey, your aunt who worked at Microsoft or Amazon and was in a senior position, was making six figures, just got automated. Oh, your cousin who couldn't keep, who couldn't keep that job. It wasn't as aspirational maybe as Aunt Susan. Waymo's in their town and DoorDash has robots that they made themselves zipping around.

• 19:33Jason Calacanis?

  And there's other bots on the street, writings on the wall for Cousin Sal. So now Aunt Susan and Cousin Sal are hitting it. And by the way, you know, your Uncle Joe, who is the programmer, he's now wondering if he's going to have a job. This social contract's been broken and Americans should not trust AI or the AI industry. Because until that social contract is fixed, They should assume the worst. You can have the most brilliant team members in the world and a great product, but if your team is not communicating well with one another or with your customers, more importantly, it could all be for nothing.

• 20:15Jason Calacanis?

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• 20:58Jason Calacanis?

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• 21:08Speaker 01

  I do not disagree. And I've always struggled to match my AI enthusiasm, my belief in the progress of technology lifting boats over the longer term with what I consider to be the potential for quicker job loss than we can replace with new jobs. And I think the technology industry, if they want to avoid a political crisis in the next four years, maybe a couple of elections, need to start doing more than they are to ameliorate the public's discontent. Because this is not just people saying, "No data centers in my backyard." This is people, potentially voting people into Congress, who want to put relatively strict guards and guardrails around what AI can and cannot do, which could disembowel the industry, which I think you and I both agree

• 21:51Speaker 01

  would be a net negative for the country over the long term. So I don't know what the solution here is, but there appears to be a political cloud forming in the future.

• 22:00Jason Calacanis?

  Oh, it's not forming. It's here. I would argue it's here. There's a group of people who are denying it. There's a group of people saying, hey, it doesn't matter. We'll create new jobs. And then there's a group of people who are being labeled doomers. And you can always tell when people lose an argument because they want to label you. This happens to me all the time at All In.

• 22:21Speaker 01

  I was just about to say, there's a co-host who doesn't like it when you bring up AI job loss.

• 22:25Jason Calacanis?

  Well, yeah, I mean, it's obviously if you're in charge of that, you probably want to try to create jobs. Now, I'm not saying Sacks is wrong or I'm right. I just think the American people should have their guard up. They should assume the worst. Why? Because they got to hit rent, because they got to get groceries, because they have bills to pay. Assume the worst and then be delighted if your job playing the violin at a cafe because everything, because there's no jobs, becomes a reality. Let's hope that this becomes the Star Trek version. It could. There's a third of a chance of that, a third of chance of massive job loss, and a third of something in between. But a lot of good questions coming in.

• 23:10Jason Calacanis?

  I think this is a very emotional issue. And our Noty gang, these are the people who have notifications turned on on YouTube. They get an alert on their phone, hey, Jake, Alan, Alex are talking. Here's the topic. And then they click the link and they come into the chat room. They watch us live, Monday, Wednesday, Fridays, about 12:00 Texas time, 12:00 PM Texas time, 10:00 AM Pacific time, 1:00 PM East Coast time. What questions do our Notys have for us?

• 23:34Speaker 01

  So Niall Roche says, why so negative on open claw adoption in Europe? Don't forget, open claw was started by a European. Fair point, Jason. You now must defend your anti-French agitation law.

• 23:45Jason Calacanis?

  I'm just talking about how delightful the lifestyle is in Europe and how it's turned into a retirement community slash Epcot center. You know, anybody who is in Europe and who wants to build a great company is probably looking at going to another region because you need to have a bunch of people working for you hardcore. Doesn't mean it can't be done. Obviously, the Scandinavians in Berlin stand out as places where interesting things are happening, but I think we all can call it what it is. Europe's a retirement community, full stop.

• 24:17Speaker 01

  I wonder about that because we're seeing, you and I have had this conversation every three months for several years now, but I keep my eyes open. And in scale, the UK-based Neo Kloud just raised $2 billion. The UK government just rolled out, they rolled out a 50 million pound fund, which I made fun of. Then they rolled out a 500 million pound fund. Okay, a little bit of progress.

• 24:39Jason Calacanis?

  Yeah, the fact that the government's doing that tells you everything.

• 24:42Speaker 01

  Well, they have less large companies. So I think using, actually, Jason, I think using public funds to build a sovereign compute is a good idea.

• 24:49Jason Calacanis?

  You know, most people would say that's socialism, or it's putting your thumb on the free market, and you really want more entrepreneurs battling it out and the government having nothing to do with that. Typically, when the government intervenes like that, it's because the private sector's not getting it done. But we'll put that aside. You know, the the state of Europe and, you know, having a couple of, you know, unicorns here or there? Yeah, sure. It just feels to me like with the education level and the resources, they greatly underperform where they should be at. They should be producing much more. And they have, they have work to do in terms of, you know, the taxation there on startups,

• 25:31Jason Calacanis?

  on investors. If you put up too many roadblocks for founders in terms of hiring and, you know, at-will employment, and you put up too much, too high taxes, then people will invest less and they'll move to other places. Europeans have a very unique ability to live in Dubai. Insert, yeah, okay, bombs are going off. But they can move to Singapore, Dubai, and other places and pay no taxes or pay under 10% taxes. Any logical investor in Europe faced with 50, 60, 70% taxes. We'll get out of Dodge and that's what they've done.

• 26:06Speaker 01

  We had another couple of questions about AI driven job loss, Jason. Before we jump into the Jason productivity hack, I'm just curious what your advice is for people out there who are concerned. We talked about, you know, AI won't take your job. People using AI will take your job. I think the agentic world has shown out to be different. So if you're a normie, what's the best way to have armor on your body to keep your job secure? Short version.

• 26:28Jason Calacanis?

  If you're working in corporate America, being the person who knows how to manage, being a maestro who manages AI is the key person. If you're in any other field, moving up the stack to things that a robot can't do and outrunning the robot is the best piece of advice. So what can a robot do? It can deliver a burrito and it can drive full self-driving. It's going to be a decade-long deployment of those technologies. So what's the next thing up from there? Being a carpenter, being a handyman, being a plumber, being an electrician. And if you look at that generation tool belt, if you were Cousin Sal, who is not a nine-to-fiver

• 27:09Jason Calacanis?

  and loves his Uber, DoorDash, Winolo Draw, you know, on-demand economy, you might need to buckle down and say, you know what? I'm going to learn a trade. I'm going to take out YouTube. I'm going to take out ChatGPT. I'm going to learn how to be a carpenter. I'm going to learn how to build a fence because the robot ain't building no fence. I can tell you, I just built a fence. It cost me like six grand to build a tiny little fence. It was a two-day job. You know, do you know what handyman who can build a fence get paid?

• 27:35Speaker 01

  Yes.

• 27:36Jason Calacanis?

  A hundred bucks an hour.

• 27:38Speaker 01

  I, I've done fencing. Yes, I paid a lot of money.

• 27:41Jason Calacanis?

  You know what Uber driver gets paid? Thirty bucks an hour, you know, in a city or a DoorDash or 20 bucks, 30 bucks. Sometimes they hit it, make 40 bucks on the weekend. It's easier than ever to build a great new product and launching a startup, even as a solopreneur, is getting easier and easier. But as my experienced founders already know, there's a lot more to starting a company than just putting up a website or even building a product. If you're serious about going into business, you need a Delaware C corp. That's going to give you a serious leg up on your competition and you can be taken seriously by investors. That's where. Northwest Registered Agent comes in just a few clicks. They're going to give you the perfect start to your new enterprise. A real identity, a domain, a custom website, a business email, all the public filings done,

• 28:26Jason Calacanis?

  and even a phone number, and you'll complete this process in under 10 minutes. Plus, you're going to get all sorts of free tools and resources from step to step guides, compliance reminders, and an online account that's going to keep everything organized, even as your business grows. So you get all the advantages of a Delaware C corp, regardless of where in the U.S. you're operating out of. NorthwestRegisteredAgent.com/twist. You could just build a fence, and that's not going away. And that's a hundred bucks an hour, 75 bucks an hour. So you're going to have to outrun the outrun the robot. The robot will build a fence in five years, seven years.

• 29:04Speaker 01

  Yeah.

• 29:05Jason Calacanis?

  Then you're going to need to learn how to make the beautiful desk and carve it that the robot can't. And then at 10 years, forget it, it's over anyway. You'll have your own robot, and then you'll just be managing robots.

• 29:15Speaker 01

  I'm just gonna, I'm gonna be on the moon in 10 years, so don't call me. It's not my problem. Uh, Jason, one thing that you do is a lot. You do a lot of stuff. You keep us all on our toes here, and I was curious if you could drop some gems on us of knowledge about how you are productive.

• 29:28Jason Calacanis?

  Oh, I have a productivity hack?

• 29:30Speaker 01

  You do.

• 29:31Jason Calacanis?

  Um, this is a really easy one. Uh, you know, I work with my Athena assistant on this. I call it super distribution. Okay, there's a ton of platforms out there. When you have a great piece of content for your company, for yourself, what people do is they're like, oh, I had a great piece of content. What you need to do is take that piece of content and then go super distributed. What does it mean to super distributed? It means you post it two or three times in two or three different versions across all platforms.

• 30:00Speaker 01

  Yes.

• 30:01Jason Calacanis?

  So if you have an EA like I do from Athena, I will tell them, hey, take this, put it on to my Twitter, put it on to my, uh, you know, put it in the drafts, maybe, put it on to LinkedIn, put it in all these different places. Hey, we have these different accounts and go find me. Other pieces of content that people in my network, like say, in my case, portfolio company founders are doing, and give me a list of that so I can engage them. This social media 101 work, if you were to hire a social media person, would be, again, 50 bucks an hour, 75 bucks an hour for a freelancer. But you can do it with an Athena assistant. If you want to get into these hacks, just go to athena.com/jcal and you will get $2,000 off your Athena assistant.

• 30:44Jason Calacanis?

  They're also learning how to use, I don't want to tip anybody's cards here, but they know how to use agents at Athena. So Athena plus agents, plus your agent, put them all in the same Slack instance, and you will get incredibly productive. You have a human in the loop with your Athena assistant who can make phone calls. You'll have your agent who is OpenClaw, or, you know, your Google agent, your Microsoft-launched agents, your Notion agent, your Slack agent. There's all kinds of different agents out there that you can use, multiple ones, but having a human in a loop is going to make you even more productive.

• 31:19Speaker 01

  Can I tell you my recent Athena brainwave?

• 31:22Jason Calacanis?

  Oh, go ahead.

• 31:23Speaker 01

  All right, so, right now, we have a nanny, which is, given what we pay, top of market, because we care about our children.

• 31:30Jason Calacanis?

  Yeah.

• 31:31Speaker 01

  The moment, the moment we don't have a nanny, I'm hiring an assistant. And I was like, we can just get into the assistant. Because, because it's so much cheaper than a nanny, and it's going to be so helpful. We have so many things now going on constantly. I can't wait. This is my weekend, juggling children's diapers, chaos zoo.

• 31:50Jason Calacanis?

  You know, also, it's a, it's a luxury item, I'll give you that, but it's also a productivity hack for mom. Here's another one. I like a certain bakery in the Austin area. It's called Abby Jane. They make incredible bread, they use the whole grains, that artisanal grains, so it's just, this is literally the best bakery in Texas, and one of the 10 best in the country. Problem is they're open Thursday to Sunday and they sell out and they don't deliver. They don't need to, they're the best, right? But they do take orders and they do open at 8 a.m. Athena assistant calls at 7:59, 8 a.m. There it is, Abby Jane, oh man.

• 32:31Speaker 01

  These are their, their bagels getting ready to go.

• 32:33Jason Calacanis?

  I mean, and it's just unbelievable. The chocolate croissant is like literally from France. So, you know, I was talking to the woman there and I was like, hey, you know, you should open up like other days of the week. Maybe you should get an investor, you know, hint and she's not interested. She's got her thing, it's dialed in. And I was like, why aren't you on Uber Eats? She's like, I don't want to be on Uber Eats. I sell out. Okay, great, fair enough. Uber has a courier service. The courier service is like 10 bucks, but you have to coordinate. So what do we do? My Athena assistant looks at their menu at 7 a.m. Finds out what's new on the menu because they change it every week. Sends me it with a number list. I say four of these, two of these, three of these. I would forget to do this. Then he puts the order in, puts it on the credit card, tells them he's coming to pick it up.

• 33:19Jason Calacanis?

  Tells them the name of the Uber driver who's coming to pick it up. This is for Jason, the person picking it up is Joe. They pick it up, then they call the ranch, tell the ranch, hey, this person's coming. Here's the link to the Uber courier. Boom, all done, all done every week. But you know, there's like 10 steps to this. It's not going to be done by an agent anytime soon, but it is done by my Athena assistant. My girls eat healthy. We stopped ordering schlocky croissant from HEB, schlocky bread. And now they have chef's kiss, the best in Texas. Little hack there for you. There's another product, I got it. It's a double productivity hack. People don't know about the courier service. Do you know about the courier service?

• 33:58Speaker 01

  I, I read about it and then it had fallen immediately out of the back of my head, just instant forgetting.

• 34:03Jason Calacanis?

  The best thing that you want to get for your wife, for your family? It's not available on DoorDash, Uber Eats. But they are available for pickup.

• 34:12Speaker 01

  Yeah.

• 34:13Jason Calacanis?

  So there you have it, folks.

• 34:14Speaker 01

  All right, let's do some demos. Let's do some stuff in action. All right, so first up, I'm going to bring up Suresh Ramamurthy. He's from NetXD. Hey, man. Suresh is going to show us moving money and interacting with bank accounts securely using OpenClaw and a skill from his company, NetXD. So Suresh, talk us through it and let us enjoy.

• 34:34Speaker 03

  Hi, Alex. Hi, Jason. I hope you guys can hear me.

• 34:37Speaker 01

  Yes, sir.

• 34:38Speaker 03

  So we have a full stack for banks and we decided that we will connect it to OpenClaw. And we built cryptographic security for that so that obviously I can't let OpenClaw run away with my money. So we integrated right into a bank mobile app. So whatever OpenClaw does, finally I approve it from my bank app and my bank runs on a blockchain.

• 35:04Jason Calacanis?

  You were one of the lunatics brave enough to give OpenClaw access to your bank?

• 35:11Speaker 03

  Yes.

• 35:12Jason Calacanis?

  Which means you gave it your password and two-factor?

• 35:16Speaker 03

  No.

• 35:16Jason Calacanis?

  And authenticated it? Or you used a password manager? Explain that step in plain English.

• 35:22Speaker 03

  I built a banking platform myself. I have 20 plus banks using my platform and I built a special open banking API so agents can access, read only, as well as set up transactions that I, as a user, can use my secure banking app, which has my private keys, ECDSA keys, to approve it.

• 35:42Jason Calacanis?

  Got it. So what's the name of your private company that does this, the platform?

• 35:48Speaker 03

  NetXD, N-E-T-X-D.

• 35:50Jason Calacanis?

  This existed pre-OpenClaw because today is open, today's AO 44. It's been 44 days since we started talking about OpenClaw here on the program.

• 35:59Speaker 03

  Of course.

• 36:00Jason Calacanis?

  Yes, and so.

• 36:01Speaker 03

  And I built it to handle 100 billion machine IDs about six years ago. I'm ex-Google. I've always been thinking about machine-to-machine commerce. So when I built this ledger, I planned for 100 billion machine IDs, which seems kind of small right now.

• 36:16Jason Calacanis?

  Okay, so NetXD existed before OpenClaw and it's a banking ledger. Now, OpenClaw users can open an account on NextXD.

• 36:27Speaker 03

  No, no, on a bank that supports NetXD platform.

• 36:30Jason Calacanis?

  Ah, got it. Then the queries go from your OpenClaw to XD, correct?

• 36:37Speaker 03

  Yes.

• 36:38Jason Calacanis?

  Got it, got it. So that will only allow it read-only access. But if I want to pay somebody, like, you know, I often will get, you know, here's the gardener, here's the pool cleaner, you know, here's the garbage service, whatever it happens to be. Here's the, you know, septic tank. You've got a ranch, you probably have 20 different vendors to maintain a ranch. I could have, when their email comes in with their bill, sometimes they just send an email with a document assigned to it. I could have my OpenClaw file that, queue up the payment through Zelle or whatever, and then not let my OpenClaw pay it, but queue it up for me to then approve it.

• 37:21Speaker 03

  Yes, it will pop up in your bank mobile app for approval. And your bank mobile app has a, you know, secret element with a private key if you approves it. What the bank sees is a signed transaction from you, Jason, to the bank, which is the only thing they would approve, which is the only thing they would accept.

• 37:36Jason Calacanis?

  I mean, this is, Alex, the productivity we need. This is the power of an open source. You would not have been able to do this if this wasn't open source, right? You would have had to do all this manually. And the fact that there's an open source agent makes it so easy, right?

• 37:50Speaker 03

  We had to build so many other plugins. We first did it on Claude a year and a half ago. We did it, we tried to build all the intention discovery ourselves. Then we stopped and said, I know where the logs are going. Instead, we built agentic memory, because you may want to pay your bills in a certain way. And you want the memory to remember, hey, I want to pay this only on the last day of the due date. This one I want to pay early so that he doesn't stop me from, doesn't supply, you know. So you can have your own long-term memory on how to do things. And we have a memory that goes along with this as well.

• 38:23Speaker 01

  So, can you show us how it works?

• 38:25Speaker 03

  Sure. I just, OpenClaw's gotten a little jealous of bricks and rimes. Every time I ask it to list capabilities, it says how much per identity. So I'm going to ask three questions at the same time. I'm going to say, check my bank balances, check my memory for any rules I have to optimize my savings in checking, and check, have I paid the light edge invoice, which is what Jason was asking, kind of. So now that I've sent that message. This through Telegram to OpenClaw. I'm also keeping my mobile app handy. As you can see, I have two controls, Jason. One to control OpenClaw anyway. You can see the request coming.

• 38:58Jason Calacanis?

  Okay, so we see that happening on the right side. You've got thirty seven hundred bucks in your checking. You've got almost ten K in your savings. You're doing okay, kid. You've... Oh, no, wait. That's nine million. You've almost got ten million in the bank.

• 39:10Speaker 03

  It's a startup that just got a Series A. Let's think of it that way. It's a hypothetical startup. Okay. So now it says, hey, you're off by thirteen hundred dollars on your checking because you plan to keep five thousand there for optimization. So I'm gonna say, go ahead, do it. Optimize it, move the money.

• 39:25Jason Calacanis?

  Ah, this is something everybody's got to deal with because you might, if you dip below a certain amount, the banks... The scumbags at the banks may give you a fee for going under five thousand.

• 39:36Speaker 03

  Yes.

• 39:38Jason Calacanis?

  I mean, why do they do that? Like, this should be something they do automatically.

• 39:41Speaker 03

  You can see that it's moving thirteen hundred dollars to optimize. I choose it. I approve it with my private key, which is linked to my biometrics. And only then the bank knows it will process the transaction.

• 39:51Jason Calacanis?

  You have given it optimization rules in memory. Keep a five thousand buffer in checking, sweep excess into savings. We all want that. Weekly auto-transfer a hundred dollars to savings. Let's say if you were on the savings tip. Windfall capture, fifty percent of large inflows, savings buckets, emergency fifty, investments thirty, yada, yada. Monthly go, twenty percent income saved, triggers, paycheck, large inflows, end of the month, boom. So this is something everybody has. You might say, hey, every month I want to move anything above this amount in savings into a five twenty-nine for my kids, into my 401K. But I... My 401K could only accept, Alex, this amount. So this is where these things can get super powerful. Then, you know what I really want?

• 40:35Jason Calacanis?

  I wanted to go find better deals from other banks for my savings. Or for my deposits, right? You put a deposit into Robinhood, you get like some bonus or something. So I love the idea of it checking my deals with my bank against other best offers. And then I would give it permission to queue up an Email in my drafts folders to send to my bankers. Because this is when I have operations people like Heidi who does operations.

• 41:04Speaker 01

  Shout out Heidi.

• 41:05Jason Calacanis?

  Shout out to Heidi. Like, I'm like, are we getting the best deal here? And like, I realized I had like a million dollars in some accounts not getting interest. I'm like, why aren't these an interest account? Oh, we're supposed to have an interest account. I'm like, what's the interest rate? It's like, oh, four, three percent. I'm like, well, why don't we have 5%? Other places have 5%. Okay, we got it up to 4.25. I'm like, you realize that's like $45,000 a year? Over three years, we've left 150K. Like, why do I have accountants and all this operations people? If we can't get this right, it's like, oh, it's tedious. It's a chore. People forget. That's the key to OpenClaw is humans forget. Humans are fallible, especially when it comes to chores. I forget to do my chores. You think the dishwasher's clean here? I may have forgot to put stuff in the dishwasher. I may have forgot to bring my dry cleaning to the dry cleaner. That's where AI shines, isn't it?

• 41:50Speaker 01

  Are you going to take into the underlying NetXD tech that was used? And open source it or make it available for other folks to play with and tinker?

• 41:56Speaker 03

  We're gonna make XT control available to anybody using OpenClaw. There is a one that is right on the right hand side. That is the XT control app, which you can use to control XT. So that it doesn't use to control OpenClaw. The banking platform, we are opening one bank. It's gonna announce in three months, they're gonna have an open banking API. They'll connect to any AI, not only OpenClaw, Cloud, whatever it is. At which point anybody can open an account at that bank and connect all these things on their own.

• 42:21Jason Calacanis?

  All right, well done.

• 42:22Speaker 01

  NetXD.com. Suresh, thank you so much for your time. And I really appreciate it. That was fricking awesome. Next up, we're gonna talk to the guy behind PhoneClaw. This is Rohan Arun. It's an OpenClaw extension, if you will, that allows agents to operate smartphones like humans, which is incredibly cool. And he's gonna show us a demo of multi-step phone automation, essentially doing some video work and posting it to multiple phones at once. And Rohan, are you gonna show us with the glasses on or the glasses off?

• 42:48Speaker 04

  I wanna show you with the glasses on, because we've been focusing on wearables and mobile devices. So I think they'll be exciting.

• 42:54Speaker 01

  All right, so we're gonna do this from your first person view through your Android AR glasses, right?

• 43:00Speaker 04

  Yes, yeah.

• 43:01Speaker 01

  Okay.

• 43:01Speaker 04

  We also have this app that was just launched, but we're focusing on mobile and AR devices.

• 43:05Speaker 01

  All right, let's do it.

• 43:07Speaker 04

  The window on the left-hand side of the screen is our app. You can go to getsupers.com to try it right now. You can essentially connect Android devices. You can also connect to Mac and you can connect multiple different agents. And you can see that I've connected three different Android devices here in parallel that I'll automate in a second. On top of it, we have a real-time assistant. Pete Steinbarger said that OpenClaw is not intended for non-technical people. So we've been trying to approach it from the angle of mobile devices and wearables. And so our assistant allows you to basically, you can connect it in maybe 30 seconds. You can start automating entirely with voice.

• 43:41Jason Calacanis?

  So what's happening with your hands there? I see when you show your hand in front of the glasses, it's putting some notes on each finger and it's, you know, it understands what each, what your thumb is and your index finger, et cetera. What's the point of all that? Is that just it?

• 43:58Speaker 04

  Yeah, good question. So basically, I suspect the reason Amazon, Alexa and other devices, AI devices previously failed is because voice alone doesn't solve the problem. Because you can't, it doesn't solve discovery and navigation. So what I'm seeing here in my hand is actually all the different options that I have for voice commands. So we see prowers, browsers, we can automate the Android device, we can automate the chat interface.

• 44:19Jason Calacanis?

  Those are buttons you can press with your hand?

• 44:21Speaker 04

  These are actually voice commands. So we're going to be automating four different Androids and they're going to be posting to social, posting to Twitter. We can automate all your social apps and things like that.

• 44:30Jason Calacanis?

  Okay, so you're a social media manager and you're going to, with these four different phones, post to your Twitter, Instagram, whatever.

• 44:38Speaker 04

  Yes, correct.

• 44:39Jason Calacanis?

  This is an exciting demo we've got ready to go here. He's going to tell his agent across three virtual phones what to do. So this is particularly important. We have an election coming up in 2026 and Putin and Xi, they need more phones, Alex, more phones and more social accounts to cause chaos in our elections in 2026. So here we're going to see how Putin's going to do this next version of election, where Xi's going to do election interference here in the United States.

• 45:14Speaker 01

  That's the worst pitch I've ever heard. Hey, hey, do you want to take down democracy?

• 45:18Jason Calacanis?

  You're thinking it.

• 45:19Speaker 01

  BoomClaw!

• 45:20Jason Calacanis?

  You're thinking it. I'm just saying it out loud.

• 45:22Speaker 04

  Hey, Super, can you hear me?

• 45:24Speaker 05

  Yes, I can hear you loud and clear.

• 45:26Speaker 04

  Can you go to device two? And can you open Twitter? And can you post to Twitter about this week's in startups podcast? Okay, so what it's doing is it's I just it went to my second Android. It posted and it made a post. Check out the latest episode of this week's in startups podcast. Always insightful, inspiring.

• 45:45Jason Calacanis?

  So you basically take an old Android phone. And then you give your assistant, you know, the keys to that kingdom and let them rock and roll on apps and they can do things. Now, if I had my Mac mini,

• 46:00Jason Calacanis?

  it does have native iPhone mirroring, so I can mirror my phone.

• 46:06Jason Calacanis?

  But I wonder if I have mirrored my phone, if my open claw could then take over my desktop and do things in my phone.

• 46:16Speaker 04

  So you can click things on your phone. So that's also one of the things we solved is we're using the moon dream API. We figured out how to solve this kind of computer use problem with really free models. So you can go to getsupers.com and connect your phone or a Mac. And you don't have to pay $200 a month, for example. And so there are other tools that allow you to kind of hack your way to this. We allow to go directly to the phone. And the problem with like automating certain things on the phone, that's that's screen sharing. If iOS actually prevents you from automating certain things like calls and for security reasons.

• 46:48Jason Calacanis?

  This is absolutely the future, being able to use AR. You really have two startups here. One is using AR, which is, you know, years in the future. But then actually giving your, you know, open claw, your assistant, its own phone to do things because of the app ecosystem. Kind of interesting, kind of compelling, very cool. And I'll look forward to see where you're taking this next. All right, let's keep moving.

• 47:13Speaker 04

  Well, thank you so much. Appreciate it, man.

• 47:15Jason Calacanis?

  But I was joking about the Putin stuff. But if you were actually trying to.

• 47:21Jason Calacanis?

  Do research on apps, let's say, being able to have Open Claw or another agenting technology provision 10 different Android phones, download the apps, install them, play with them, authenticate with them, like even just for research as a firm to understand the changes happening, competitive intelligence. I mean, I could see a lot of interesting use cases here. I didn't, I never thought, what if the agents had unlimited access to app stores and apps? It's a pretty interesting idea.

• 47:53Speaker 01

  Go back to the top of the show, Andrej Karpathy's idea of auto research and letting LLMs train themselves. Now, take that, build an app, put it on your dummy device, use Phone Claw to let the agents interact with it, run tests. I mean, you could build a self-reinforcing like mobile development loop here with just a couple of pieces kind of duct taped together. And I wonder if that's going to do away with certain testing, because then you don't need to have a human in the loop at all. You can just run it autonomously and

• 48:21Jason Calacanis?

  It'll certainly accelerate tests, right? So if you were com.com and you wanted to test different aspects of the app, you need to have humans testing it, but you might also want to test responsiveness and speed and other things. And yeah, you could create a test flight and just say, go, here's your metric. And that was the key to Andrew's innovation this weekend is you need to have a metric that the recursive loop can key off of. So you'd have to really set a north star. I want the app to be faster. I want the app to be, gosh, I don't know, less buggy. I want the app to work better. Like if you said, I want it to work better on iPhone 12s and earlier. So make me a light version

• 49:06Jason Calacanis?

  of the app that detects you're on an iPhone 12 and just downgrades everything to make it as fast as an iPhone 17. Like that kind of benchmarking and instruction would work. But if you don't have a good benchmark, you don't have a north star, it's not going to work. So that's, I think that's a key to the innovation.

• 49:22Speaker 01

  Off the rails. All right. We have one last demo for us, and that is from someone that you know, Jason. We're going to talk to Eugene Stuckless of Air Inc. Air is a founder, you ex Japan company. You met him in Tokyo.

• 49:37Speaker 01

  And he's going to show us an AI native testing tool that helps agents test. It's a little complicated. We spent a lot of time talking about it before the show. So Eugene, maybe we should just start with, explain this to Jason.

• 49:49Speaker 06

  Why don't I show you?

• 49:50Speaker 01

  Even better, much better.

• 49:52Speaker 06

  So Air Inc. is an AI native automation platform. Our first product is Air Tests. It's using agents to test websites, right? So you provide a URL. And then with this URL, about 15 minutes later, you get a link. And this link is in, or you get an email and this email is a deep, deep dive into your website. Analyzing it from 10 different criteria, SEO, performance, trust, UX friction, security, right? This happens in about 15, 20 minutes. This is a free report. This is what it looks like when you go to the site, you see and you drill down the evidence about what went wrong, how you fall short. This is free, right?

• 50:35Speaker 06

  So you pay 20 bucks to buy 150 credits and then you can run this report maybe four or five more times. What's pretty cool about this is that you see there's, it's very, very in-depth. You'll see you drill down into one specific area, let's say SEO. This particular founder has been focused on SEO. So he has put a lot of effort in and you can see that this test report has tracked his changes over time. Translating, translates into business impact that he can understand. This is AI testing top to bottom, right? So this generating of a site readiness report is one workflow we have, right? So agents run workflows.

• 51:17Speaker 06

  So I would like to show you what it looks like to run and train agents running workflows. This is how I deal with the workload that I have around agent testing. I have built a Proprietary piece of software that self-trains at maybe four or five different levels. And you see here a dashboard that tracks a particular workflow and its evolution over time. How many tokens it reduced each loop? What kind of change was made to allow for that to happen? You could see as well, a graph that shows me the workflow

• 51:59Speaker 06

  distribution of which models got which tasks within that workflow and how we learned how to feather more expensive tasks to the expensive models and the cheap stuff to the cheap ones. So, and importantly, you'll see here on the governance page, this is my AI asking me for permission to evolve for high-risk tools that are, let's say, adding a new tool. It asks me if it can evolve, because that's a very important thing, adding a new tool, right? Okay. So, and then one more, I think you'll like this one, Jason. So this is the workflow view.

• 52:38Speaker 06

  On this workflow view, you see the phases broken down. My favorite part is that it has a blast radius. So if you have to... Blast radius. Yes. So if you consider, when you get signal from the outside world that goes into your open claw, that agent is compromised. Prompt injection is impossible to prevent. So instead of focusing on trying to, let's say, secure the whole system or secure on prompt injection, you focus on isolating the blast radius of that bad actor. So you see here in this workflow, it flagged that this phase is potential for bad actors. So it's flagging it to me, say, hey, maybe this should have less tools. Hey, maybe this agent should

• 53:23Speaker 06

  have not had the ability to do this thing because it's getting signal from an outside source. So this is what... It looks like to build internal tooling to manage and train agents to improve efficiency for the workloads that they provide to the customer.

• 53:40Jason Calacanis?

  Okay, so just to separate this out and explain to the audience, you are building a startup that helps people optimize their websites. You have to build tools for those website owners and those tools need to get better over time. So you built agents to make each tool get better and be recursive. So if one of those might be SEO advice. So when you run the SEO advice tool, you want to make sure that it doesn't cause damage and that it is actually getting better and that you're controlling the costs.

• 54:16Speaker 06

  Right, so there's a couple of cool things that are feathered in here. At the top of the news, the guy said his recursive loop, this is applying this at scale. So that recursive loop is happening across many, many agents that you see in here. Not only agents, the workflows, the tools they have, it's multi-layered, right? So my job is more like helping it learn how to run my business. That's the point at which this is now peak efficiency. I no longer have a job. Crazy.

• 54:45Jason Calacanis?

  Yeah, so it's being like a product manager, but it's got to go get intelligence from the open web. So you're using

• 54:53Speaker 06

  Yes.

• 54:54Jason Calacanis?

  Some protocol to get better at SEO.

• 54:57Speaker 06

  So.

• 54:58Jason Calacanis?

  You have to make sure that it's not garbage in, garbage out. So how do you do that step? That the LMLM agent you have

• 55:05Speaker 06

  Sure.

• 55:06Jason Calacanis?

  Specifically for SEO or maybe for, I don't know if you have like call to actions on the website or copy.

• 55:13Speaker 06

  Really good question. So how do you ground data in reality? There's two ways. One, deep research is really, really effective.

• 55:22Speaker 06

  To allow the AI to model its research in a way that it can understand, so that it understands the context better, it's a better data model, easier to talk to. The focus that I was going for, the reason why I put all this engineering effort into get this self-training, is because my mind has been blown since Open Claw dropped. Like you, I've been listening to jazz non-stop. I can't do anything else because my mind is so expansive. So this, this codex that I invented to allow myself to encode this learning, this is called Coltrain.

• 55:52Speaker 01

  Okay.

• 55:53Speaker 06

  Because it's the only thing I can use to express myself as, as, as he can. Because the way the agents learn, the way I can talk to the system, it learns so fast. So the way it models domains, it learns better how to build something in its language, rather than relying on me to do it. It's very interesting.

• 56:10Speaker 01

  Yeah.

• 56:10Speaker 06

  So buying this, this infrastructure to, you know, dominate the QA testing market, and maybe something else later on.

• 56:18Speaker 01

  Oh, I was just thinking about taking the idea of self-improving agents that have a stricter kind of permission structure around them so they're safer to other areas, Eugene. So if you could just throw some ideas out, like what are the top four or five areas where you think this is going to go next? I think all the founders would like to know.

• 56:33Speaker 06

  Sure.

• 56:33Speaker 01

  Where agents are going to get better faster.

• 56:35Speaker 06

  So I think this is something, there's two things. One, inference efficiency. So LM's magic thing is they can do inference really well, right? So the well-trained frontier models, they have the ability to reason through deep stuff and come with very good insights, right? But we are burning 95, maybe 98% of our tokens on stuff that doesn't require reasoning, right? So what we'll find is that people will start to encode their knowledge about how to be more efficient with these things. What's cool about my system, the way it's coded, is that if someone makes a contribution to an agent on my system, if that agent is invoked elsewhere on another customer's, let's say, platform,

• 57:20Speaker 06

  they get attribution for that because they participated in the encoding of their knowledge into the AI, right? So it creates attribution. It allows for you to pay somebody for knowledge work as they transfer it into. The AI, right?

• 57:38Speaker 01

  I see. Well, it's it's it's super cool, man. And if people want to learn more, EIR Inc., but it's spelled E-I-R. Thank you very much.

• 57:46Speaker 06

  Correct, E-I-R dot I-N-C.

• 57:48Speaker 01

  All right, we appreciate it. Thanks, Jim.

• 57:49Jason Calacanis?

  All right. Well done. And Alex, as you know, all jobs are being replaced with AI. There'll be no more employment. I've said this over and over again. That being said, we have three open job requests. So take that for what it's worth. We're doing pretty well over here and we're adding headcount. If you want to be the community manager and you love founders and you love Discord and X communities and Slack and Circle and all these different platforms, but most of all, you love founders, you love angel investors, you love venture capitalists, you want and tech enthusiasts, you want to build that community and help us figure out, hey, of these millions of users, who are the top one or 2% who engage with the content the most?

• 58:33Jason Calacanis?

  Email us what you're good at and what you've done. [email protected]. [email protected]. Just tell us. We don't care about your resume. We don't. We do care about your experience, but tell us what you've done in plain English. Just email us, [email protected]. We're also hiring two researchers. Researchers at our venture firm are looking for, they're hunting for great companies to invest in or have on the podcasts. That's one job function. Then they're writing coverage of those companies. That's another job function. And then eventually, after they're a researcher, they become an analyst and they get to get on the phone and maybe do some calls. So there's two different aspects to this job.

• 59:16Jason Calacanis?

  One is hunting for companies and finding them out there. And then two is sorting through the ones we already have, writing coverage. And this is the onboarding. This is the year that will tell you if you're qualified. To eventually get that seat at a venture capital firm. So instead of hiring venture capitalists from the existing pool of them, we said, let's make our own venture capitalists. Let's invest three, four, or five years in professional development. Wrong one on the ladder. Researchers at launch.co. The email, just tell us about yourself, your analytical ability, why you're passionate about this, what you think you bring to the table. Researchers at launch.co. We're hiring people out of school for that position. Entry level 50, 60, 70 hours a week, seven days a week.

• 1:00:00Jason Calacanis?

  You're going to try to crush it and fight to get that job in venture capital. Finally, we have a producer role here at This Week in Startups. The shows are doing so well. We launched This Week in AI. We're going to bring three other podcasts into the fold shortly. And we need a producer. [email protected]. [email protected]. If you have produced podcasts before and you have experience, [email protected]. This is not an out of school one, like researchers at launch. This is a, we need you to have experience and bring something to the table. We'll see you all next time on This Week in Startups. Bye bye.

• 1:00:38Speaker 01

  Bye bye.