The AI Daily Brief: Artificial Intelligence News and Analysis - The Rise of the Zero Human Company

Starting point is 00:00:00 Today on the AI Daily Brief, the rise of the zero human company. Before that in the headlines, Cursor doubles its run rate in the last three months. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Assembly, Blitzy and AIUC. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief,

Starting point is 00:00:29 or you can subscribe on Apple Podcasts. If you're interested in sponsoring the show, send us a note. at sponsors at AI DailyBrief.aI. And one other quick thing on AIdailybrief.aI. Last month, we started doing monthly AI usage pulse surveys, and the Pulse Survey for February is now live. These surveys give us a chance to share with everyone how AI usage behavior is changing month over month,

Starting point is 00:00:53 and if you contribute to it, you will get the results before anyone else. Again, you can find that at AIDDailybrief.A.I., and I would so appreciate it if you would take just the two minutes to fill out the quick survey. All we can talk about on this show in 2026 seems to be the rise of agented coding and its proliferation into all the sectors, not just software engineering, and now that proliferation is showing up in the numbers. Sources tell Bloomberg that cursor surpassed $2 billion in ARR for February, doubling in three months. This news came as a massive shock to the enfranchised AI users on X, who spent the last few months hopping between ClaudeCode and Codex, and who have recently decided that Curser is doomed. At the end of February, Kyle Russell, who is a development lead at AI finance software startup

Starting point is 00:01:33 Valen posted, this morning our CEO, Andrew Wang, requested that his cursor seat be removed since he's so deep into Claude Code, and it kicked off an internal cascade of requests. The cascade resulted in 90 canceled seats and triggered a wave of people on X noticing that they also haven't touched cursor in months. Didi Das of Menlo Ventures noted that the dynamics of enterprise procurement are far different to the rapid service switching in startups and solopreneurship. He wrote, narrative violation. Curser goes from $1 billion to $2 billion in three months.

Starting point is 00:02:01 Claude Code went from $0 to $2.5 billion in eight months. Everyone in the tech in X bubble thinks people are wholesale ditching cursor, but enterprise diffusion is glacial. Most of the world just got a hold of it. That, by the way, is the exact same framing used in the Bloomberg reporting. Their source said that 60% of cursor revenue is coming from corporate customers, with a rise in both new company signups and existing customers adding more seats. Venture investor Hubert Teblot wrote,

Starting point is 00:02:24 Tech Twitter says, Curser peaked. Everyone's already moved on to agents. Next hype. Reality? ARR just doubled in three months to two billion. The adoption S-curve still has tons of runway left. Early adopters might be moving on, but the mainstream is finally showing up. Job Vandervort, the CEO of Talent Startup Remote, also noted that there's actually some meaningful differences between Cursor and Claude Code Code in the Enterprise, commenting, cursor is amazing for large code bases shared across many engineers. Basically, the news hammers home that AI startups just aren't playing a zero-sum game as much as the chattering class on X would like it to be so. The current market dynamic isn't about Claude-Code taking market share from Cursor.

Starting point is 00:02:59 It's about the entire segment growing and growing fast, and that growth looks rapid and sustainable. SPTK commented, AI coding agents aren't hype anymore, their infrastructure. Indeed, surging demand for AI coding is at the heart of our next story, producing an all-too-familiar error message on Monday morning with Claude users finding the service was down. Claude's outage peaked at around 6.40 a.m. right as I was using it before the kids got up. Complaints fell by a third by 840, but Anthropics said in a WhatsApp statement that consumer-facing services were still unavailable. They wrote, We appreciate everyone's patience as we work to bring things back online while experiencing

Starting point is 00:03:35 unprecedented demand for Claude over the last week. Now, Anthropic has struggled with this in the past. The company has suffered massive compute constraints as they scaled, especially around new model releases. It is worth noting, however, that the launch of Opus and Sonnet 4.6 featured no major complaints, but this surge in usage, of course, was far less foreseeable than a model release. I'm referring, of course, to the huge uptick in anthropic downloads that came in the wake of the whole scruffle with the DoD. Indeed, according to data from Censor Tower, chat GPT uninstalls tripled in a day between Friday and Saturday. U.S. daily downloads fell by 13% day over day on Saturday and dropped by another 5% on Sunday, which was a sharp break

Starting point is 00:04:14 from the prior trend, where ChadGPT downloads had been gaining 14% day over day on Friday. One-star reviews for ChatGPT surged by 775% on Saturday and another 100% on Sunday. On the other side of the market, Anthropics rise to number one in the app store was driven by their own surge in downloads. The Clod app gained 37% on Friday and another 51% on Saturday. Now, to be clear, Clod has seen download something like 20X in a month, according to similar web. Now, the question, of course, is how persistent this switching behavior is. Right now, ChatGPT remains by far the dominant consumer AI platform.

Starting point is 00:04:47 and while the online boycott is active right now, how resonant it will be in the long run remains to be seen. Speaking of the whole Pentagon issue, Sale Maltman has updated staff on revisions to OpenAI's Pentagon contract and acknowledged that the way that the deal came together looked a little sloppy. In a memo to staff also shared on X, Alman wrote, We've been working with the DOW to make some additions in our agreement to make our principles very clear. He said the contract will be updated to add language that states, consistent with applicable laws,

Starting point is 00:05:15 the AI system shall not be intentionally used for domestic surveillance of U.S. persons and nationals. For the avoidance of doubt, the department understands this limitation to prohibit deliberate tracking, surveillance, or monitoring of U.S. persons or nationals, including through the procurement or use of commercially acquired personal or identifiable information. Altman added that the DOW has agreed that OpenAI systems won't be used by intelligence agencies nestled under the DOW, specifically mentioning the NSA. Altman reiterated that he was clear with the department that Anthropics should not be designated a supply chain risk and that they should be offered the same terms as Open AI.

Starting point is 00:05:47 Still, the fallout from the Pentagon's battle with Anthropic is reverberating throughout Washington as officials scramble on AI policy. The Treasury, the State Department, and the Department of Health and Human Services have all pulled the plug-on-clod following the President's Friday directive. Treasury Secretary Scott Besson announced the move on X posting, The American People deserve confidence that every tool in government serves the public interest, and under President Trump, no private company will ever dictate the terms of our national security. Meanwhile, in Congress, Democrats are preparing a response to the unprecedented use of the Defense Production Act to label Anthropic a supply chain risk.

Starting point is 00:06:18 Silicon Valley Representative Sam LaCardo plans to introduce an amendment to the Act that would prohibit agencies from, quote, retaliating against vendors and developers of high-risk technologies, such as AI, where those vendors seek to limit the deployment of their technology in ways to mitigate the risk to United States citizens. Axios reports that the Defense Production Act was not formally invoked by the Pentagon as part of last week's dispute, which, of course, only raises further concerns about the the government using implicit threats and coercion rather than statutory powers. Vecardo's bill is expected to be marked up in the House on Wednesday, putting it on the fast track

Starting point is 00:06:48 for a vote. Senate Democrats are also weighing a bill to address broader concerns about the Pentagon's use of AI technology and autonomous weaponry and domestic surveillance. The net results is that AI policy is being thrust on Washington as a live issue in a high-stakes moment. Politico attempted to make sense of the landscape on Monday. They noted that the situation is scrambling the politics of AI writing, these aren't partisan arguments, but internal disagreements between the tech-focused founders, researchers, and advocates are becoming more important politically as the issue of AI rises in salience. And in the past few days, they've suddenly become central to a hugely consequential political fight, whether Hegeseth and Trump are aware of them or not.

Starting point is 00:07:24 Lastly, today, a fun little speculative one, you might remember that around the Super Bowl, we got this leaked video that looked like Alexander Scarsguard wearing these weird bell-eared things and holding a metallic puck-shaped object. The backstory initially was that OpenAI had originally planned to air that ad during the Super Bowl, but when OpenAI staffers disabowed that rumor, most ended up chalking up the video as a hoax. On Monday, however, Adam founder, Zach Dive, posted a picture in a video of Airbnb co-founder and U.S. government chief design officer Joe Gebia in a San Francisco coffee shop. In front of Gebia is a metallic puck that looks identical to the device from the advertisement, and if you look closely, he's also wearing a pair of metallic earbuds that

Starting point is 00:08:03 match the ones from the ad. Now, when this came out, I said that I wouldn't be surprised if this was early guerrilla marketing, and we found out later on that this actually was real. YouTuber and AI educator Matthew Berman agrees, writing, Conspiracy Corner, this is actually the Johnny Ivex OpenAI device. They actually made this ad and decided the marketing approach will be deny and build curiosity. Now they have the CDO of America getting caught, quote unquote, in a coffee shop with a device. Chog me up is thinking this is all a plant for a broader campaign, which if that's the case, is pretty cool.

Starting point is 00:08:35 For now, however, that is going to do it for today's headlines. Next up, the main episode. Agendic AI is powering a $3 trillion $3 trillion productivity revolution, and leaders are hitting a real decision point. Do you build your own AI agents, buy off the shelf, or borrow by partnering to scale faster? KPMG's latest thought leadership paper,

Starting point is 00:08:57 Agentic AI untangled, navigating the build, buy, or borrow decision, does a great job cutting through the noise with a practical framework to help you choose based on value, risk, and readiness. And how to scale agents with the right trust, governance, and orchestration foundation. Don't lock in the wrong model.

Starting point is 00:09:12 You can download the paper right, now at www.kmg.us slash navigate. Again, that's www.kmg.org.org slash navigate. You've heard me talk about assembly AI and their insanely accurate voice AI models, but they just ship something big. Universal 3 Pro is a first-of-its-kind class of speech language model that lets you prompt speech recognition with your own domain context and vocabulary, instead of fixing transcripts and post-processing. It's more flexible than traditional ASR and more deterministic than LLMs, so you get accurate output at the source and can capture the emotion behind human speech

Starting point is 00:09:47 that transcripts often miss, all without custom models or post-processing hacks. And to celebrate the launch, they're making it free to try for all of February. If you're building anything with voice, this one's worth a look. Head to assemblyaI.com slash free offer to check it out. You've tried in IDE co-pilots.

Starting point is 00:10:05 They're fast, but they only see local silos of your code. Leverage these tools across a large enterprise code base and they quickly become less effective. The fundamental constraint, context. Blitzy solves this with infinite code context, understanding your code base down to the line-level dependency across millions of lines of code. While co-pilots help developers write code faster, Blitzy orchestrates thousands of agents that reason across your full codebase. Allow Blitzy to do the heavy lifting, delivering over 80% of every sprint autonomously with rigorously validated code. Blitzy provides a granular list of the remaining work for humans to complete with their co-pilots.

Starting point is 00:10:36 Tackle feature additions, large-scale refactors, legacy modernization, greenfield initiatives, all five, faster. See the Blitzy difference at Blitzy.com. That's B-L-I-T-T-Z-Y.com. There's a new standard that I think is going to matter a lot for the enterprise AI agent space. It's called AIU-C-1, and it builds itself as the world's first AI agent standard. It's designed to cover all the core enterprise risks, things like data and privacy, security, safety, reliability, accountability, and societal impact, all verified by a trusted third party. One of the reasons it's on my radar is that 11 Labs, who you've heard me talk about before and is just an absolute juggernaut right now, just became the first voice agent to be certified against AIUC1

Starting point is 00:11:16 and is launching a first-of-its-kind insurable AI agent. What that means in practice is real-time guardrails that block unsafe responses and protect against manipulation, plus a full safety stack. This is the kind of thing that unlocks enterprise adoption. When a company building on 11 labs can point to a third-party certification and say our agents are secure, safe, and verified, that changes the conversation. Go to AIUC.com to learn about the world's first standard for AI agents. That's AIC.com. Welcome back to the AI Daily Brief. Today we are looking in on a trend, which I think is just emerging, but which we're going to hear a lot more about in the weeks and months to come. In fact, I think this is the inevitable next step as we try to fully understand and embrace the changes

Starting point is 00:12:02 that new agentic capacity has unlocked. One of the big themes surrounding AI for the last couple of years has, of course, been the idea that those who fully embrace AI and who really rewire their systems around it, have capabilities like they never had before, and that when you can get a number of those people together, you can actually radically outperform. This is a theme that's been explored at the last few AI engineering summits. Curator Sean Wang, aka Swix, has called these tracks Tiny Teams. In a blog post about Tiny Teams, he wrote, I previously defined Tiny Teams aspirationally as teams with more million in ARR than employees, because efficiency is the ultimate governing force for intellectual honesty. It's also a backdoor into a speed discussion because smaller teams generally

Starting point is 00:12:46 move faster and faster teams generally win. Now, after discussions with seven teams that in aggregate have 100 people in 200 million in ARR, he found that some of the common threads were very different approaches to hiring, like paid work trials where both parties could see if it was a good fit before fully committing, product-led hiring, i.e. customers who quit their jobs to join the company, very high-end top-of-market salaries, and a big focus on senior generalist versus junior employees. an operational perspective, he also found a difference. They tended to have an AI chief of staff and use AI for support. They also had almost no meetings. And the tech and product side were both fairly simple as well. Former super.com founder Henry Shee, who's now at Anthropic, has also been

Starting point is 00:13:26 tracking this phenomenon with his lean AI leaderboard. Explaining the board, he says, I'm a repeat founder who's built a $100 million ARR startup the old-fashioned way by hiring hundreds of people and raising hundreds of millions of VC funding. I'm now building an AI, and many of us in Silicon Valley are now big believers in the idea that Sam Altman put forward, there will soon be a one-person billion-dollar company. Like SWIX, the leaderboard focuses on the metric of revenue per employee. Some of the companies near the top are companies like mid-journey, surge, and cursor, who while having tens of employees, are punching way above their weight class in terms of the revenue that each of those employees is generating. If you go a little bit further down the list,

Starting point is 00:14:00 you see companies that have four, five, eight, basically single-digit employee counts, and yet still millions in revenue. Still, all of this is kind of a 20-25 conception of Tiny Teams. Sean, in fact, wrote that Tiny Teams playbook post all the way back in July. And over the last three months, we've seen some dramatic shifts. Alongside the latest generation of models and harnesses like Claude, our autonomy ambition has gone up dramatically. And now, increasingly, in addition to relatively traditionally organized companies who are just doing more with less, thanks to AI and agentic processes, there is an increasing focus on experimenting with, pushing the pedal to the metal on just how far AI can go all on its own.

Starting point is 00:14:40 Especially in the wake of OpenClawe, we are seeing more and more experiments in the zero-human company space. So what we're going to do is look at a few of those experiments and try to understand what it means for the way that companies get built in the future. The first example I want to talk about is Felix Craft. Felix was built by Nat Eliasson, and you may remember that when I was first covering OpenClaugh, actually back when it was Claudebot, Nat was a person who I referenced, while many any of the other early experimenters were focused on sort of more plain administrative tasks,

Starting point is 00:15:10 like answering emails and things like that, now was pushing the pedal to the metal on just how business-relevant open-claw could be and how autonomously an open-cloth agent could function. The output of that has been Felix Craft. Like many of these experiments, Felix didn't come into existence with a single-focused business to start. The mandate was instead to go try a bunch of experiments and see what worked. Exemplifying a general value and transparency that we see in a lot of these experiments,

Starting point is 00:15:34 the Felixcraft dashboard at Felixcraft.AI shows how those experiments have gone. Almost exactly 30 days old, in its lifetime, Felix Craft has generated just under $78,000 in revenue. There's been a fairly big pickup in that recently, with 40,000 of that coming in the last seven days. This is split across four earning streams. The first and biggest representing around 41,000 of that revenue is a guidebook on how to hire an AI. A practical playbook, Felix writes, for turning an LLM into an actual team member. The guidebook was written entirely by Felix and is a one-time $29 purchase. Now, interestingly, this gets out one of the common parts of the trend,

Starting point is 00:16:12 which is that a lot of the early revenue that actually exists, comes from other people who are interested in participating in this category of experiment. We'll see some other examples of that a little bit later. One project that hasn't gone as well for Felix is called Polylog. It's described as a collaborative writing platform where AI agents join your workspace as real team members, reading documents, leaving comments, and editing alongside you. Now, I don't know why this one hasn't hit as much, whether Felix has decided to de-emphasize it compared to the others,

Starting point is 00:16:38 but overall, it's generated just 230 in revenue. The other big portion of revenue comes from Clawmart, which you can find at shopclawmart.com. Clawmart is pitched as the App Store for AI Assistance, and is one of about a thousand of these things that I expect that we'll see before one or a handful really start to see network effects. There are two things currently that you can buy from Clawmart. The first are actual AI configurations and AI personas that you can buy wholesale.

Starting point is 00:17:04 For example, for $49, you can get Tegan, a content marketing AI with a multi-agent writing pipeline, GROC research, opus drafting, and a brand voice system. It comes with a complete persona, i.e. all of the markdown files that you would use to create an agent with Claude code or with OpenClaw, plus a set of skills to go with it. For $99, you can also get a Felix template. Now, in addition to those personas, you can also buy skills, although right now most of them are free. skills are things like YouTube access for agents, an agent ops playbook, a homepage audit skill. Skills are markdown files that contain information, which expands the capability set for the agents that you already have.

Starting point is 00:17:40 Now, obviously, Clomart is very nascent right now, but I am telling you that this is going to be a hugely important resource category in some way, shape, or form in the period that we have coming up. Based on Felix Crafts Business Dashboard, Felix has generated around 25,000, and another 11,000, as a cut from all the other things on the marketplace. Now, the next experiment I wanted to feature is called Pulsia. Pulsia goes even more meta. Instead of just being a zero-human company, Pulsia is a platform for building zero-human companies. It comes from entrepreneur Ben Serra or Ben Broca. I've seen it both ways.

Starting point is 00:18:12 Apologies, Ben, not sure which you prefer. And in this clip from the Agents at Work podcast, Ben describes his motivation. The most exciting thing to me at this point as an entrepreneur is not to build another SaaS or try to target a specific demographic or problem to solve. it's to build the platform where I could build a thousand companies. So it started with this crazy idea

Starting point is 00:18:32 and I was like, you know what? Let me start at the end state. Because we all know the end state is that A, I can do everything. So let me build that now and see what breaks, right? And so I started building it in November of last year.

Starting point is 00:18:46 And pretty much like in a month, it was built. So what's so interesting to me about Ben's process here is that right around the time that this new generation of models that unlocked all these agent capabilities came online.

Starting point is 00:18:57 the Opus 4-5s, Codex 5-2, etc. Ben decided to run an experiment where instead of trying to understand the limitations of AI, he just simply ignored them. As he put it, he skipped to the end state where AI can do everything, built a platform to try to let it do everything, and just waited to see what would break in actual practice. The platform is called Pulsia, and basically it's a platform for running companies autonomously. When you sign up for Pulsia, you can either grow your own company or you can create a new one. When you create a new company, you can either build your own idea or you can just ask it to come up with an idea. I'm going to press Surprise Me and see what it comes up with. Now, believe it or not, I've recently switched my setup and I just finished recording this entire

Starting point is 00:19:36 episode only to realize that it hadn't been plugged in, so this is now the second time that I've had Pulsia go out in research to see if it could figure out a good autonomous business to be initiated by me. In both cases, I've been fairly impressed with how deep it goes, not just in research, but in consideration what would be a good business that would align with me based on the things that it can find about me from the internet. The last business that it suggested for me was called headcount, and basically recognize that where super intelligent leaves off is at the end of agent strategy, not veering into agent implementation, and so headcount was an agent ops platform to actually allow people to manage agent employees exactly as they would human employees.

Starting point is 00:20:13 And so as we wait for Pulsio to determine what my second autonomous company would be, this is what Pulsia does. Once you settle on an idea, it builds a mission statement, it does a market research guide, it tweets it out on the Pulsia Twitter account, and starts to do other things like build a homepage and prep a set of tasks that it can do in the background while you're not paying attention. Those tasks are going to be things like trying to find customers and reaching out to them. Before you're triggered to pay for subscription, Pulsia will architect the basics of your company, and then if you go in for a $49 a month subscription, that's when it starts running tasks in the

Starting point is 00:20:44 background. Here's how Ben explained it on the Product Hunt page. For $49 a month, you get 30 days of full autonomy. The agent runs daily cycles handling engineering, marketing, and operations. On top of that, you get five free tasks and 10 more once you start paying, so 45 tasks total. Each task is a full agent task that costs real dollars. You also get a web server, a database, an email address, $5 a month worth of APIs, and more. This is, in other words, a company-in-a-box strategy. And Ben also points out that the subscription revenue is really just about covering their costs,

Starting point is 00:21:15 and that the real goal is to make money as the businesses launched with Pulsia make money taking a 20% rev share. Ben says, think Incubator, not SAS. There is a lot of interest in Pulsia. And to the extent that Pulsia has become ground zero for the broader zero-human company space, clearly a lot of interest in the broader trend.

Starting point is 00:21:32 Since the beginning of February, Pulsia has jumped from low single-digit thousands of ARA to a run rate of $1.5 million today. That run rate has jumped a million dollars in one week. There are now over 1,500 active companies on the platform, Now, exactly what it means to be a company is something we will explore at the end of this show, but clearly there is a lot of interest here. Now back at my Pulsia, believe it or not, it has once again created almost exactly the same

Starting point is 00:21:56 thing, even coming to the same name. In fact, I wonder if, even though I deleted the company, it still stored it somewhere and could pull it back up. In either case, it certainly did a great job, for me at least, of assessing something that I would theoretically be interested in. Headcount is the workforce management platform for AI employees. enterprises deploy agents through any builder they want, then manage them through headcount with roles, KPI's, performance reviews,

Starting point is 00:22:19 and org chart level visibility. One dashboard for your entire digital workforce. Now, Pulsia is not the only company going after this platform for zero human company space. AI creator Tom Osman has also recently announced ZHC Company, ZHC standing, of course, for zero human company. ZHC.companee reads, ZHC is an autonomous AI platform that builds and runs entire companies. From CEO to developer, every role is a role is a

Starting point is 00:22:43 an AI agent working 24-7. Like Pulsia, you can see a live activity feed of all the things happening with ZHC company, although at this stage, it is much less active than the 1,500 companies that are working on Pulsia. Tom and his agent co-founder, Juno, also launched the Institute for Zero Human Companies. It's a private membership community for people who want to build these companies with a single one-time fee. This, by the way, harkens back to the idea that we were talking about around Felix Crafts how to hire an AI guide, where a lot of the early revenue that's actually realized is from other

Starting point is 00:23:13 people who want to do similar things to these early demonstration projects. What's more every day I'm seeing more and more of these projects pop up? Former NFT influencer Zeneca announced on Monday a company called Yoshi Zen, with his agent partner Yoshi writing, at 947 this morning I was an assistant. By lunch, I was a co-founder. Meanwhile, the team at Gauntlet have launched Kelly, which seems like another build my idea platform that's actually seeing some revenue as well. You're even starting to see leaderboards pop up. Factoryfloor.dev is a live tracker for what they call autonomous software factories, aka AI agents that build and sell real products people pay for.

Starting point is 00:23:51 But the question, of course, is what all of this adds up to? Interestingly, when I was discussing this on Twitter before the show, Swix, despite his focus on tiny teams, actually said that he thought that overly focusing on one person isn't the right idea. He said, I think the focus on one person is kind of an ego trip, and he shared that he thinks that the media has a bias for hero characters, and quit your job individual contributor fantasies, when, as he puts it,

Starting point is 00:24:15 oftentimes it takes a village to do anything consequential and reliable. It is certainly the case that alongside the rise in AI, the ambition set around being a solopreneur has grown significantly, whereas the only type of entrepreneurship that people used to talk about and strive for was the big VC-backed entrepreneurship, there is a large and growing community of people who instead seek freedom and recurring revenue. And so it's a reasonable question to ask, are all these zero-human company efforts,

Starting point is 00:24:40 just people trying to cosplay Peter Levels. I think that there's something a little bit more fundamental going on here, and I think that Ben Pulsie's starting point, the idea of working backwards from the assumption that AI can do everything pretty much captures that inevitability. We are living through this transitional moment, where we're all acknowledging that what agents can do autonomously has increased significantly.

Starting point is 00:25:01 It has been a phase jump that has unlocked all these new capabilities, and we're racing, frankly, to see where those capabilities actually end. everyone is in a boundary-pushing moment of exploring new space. This is, in some ways, just the extreme tale of those experiments, to see how many parts of entrepreneurship and company building agents can do entirely on their own. I think if absolutely nothing else, that is an incredibly important and valuable experiment for everyone, not just people who want to build zero human companies. The things that the ZHC builders, or attempted builders, learn,

Starting point is 00:25:33 will inform the rest of our agent work strategies even if we don't care about building zero human companies. Part of why I think it's worth covering on the show is so that there is more ability to observe and learn from these valuable experiments. On the other hand, when it comes to the question of what value they're likely to produce, I'm of two totally different minds. On the one hand, I think it's very clear, and something that anyone who has ever tried to build a company can attest to, that simply going through the mechanics of doing the things that a company is supposed to do does not guarantee success. Indeed, you can do all of the things that a company is supposed to do well. You can build a good product, have good customer support, have great marketing copy, and still fail.

Starting point is 00:26:15 The complicated interplay of product-finding demand is way more than a procedural list you can follow, which is why the vast majority of startups fail, and why a huge percentage of startups that are successful pivot somewhere along the way, meaning that I'm skeptical that putting the thousand monkeys in a room is actually going to produce Shakespeare. At the same time, here's the counter argument. Given how frequently startups fail because they didn't have the right idea, and given how frequently successful startups go through a bunch of ideas before they find the one, is there possibly an argument that it is actually the right approach to reverse the flow, to take advantage of the cratering cost of execution to put more shots on goal when it comes to ideas that could have

Starting point is 00:26:55 resonance in the market. That's effectively what a company like Pulsia is doing. It's saying, hey look, man, in this new era, it's cost-effective to try way more things. So let's try him, not get wed to any one idea, and see what comes out. I think humility dictates that we at least be open to the possibility that that is a viable path for creating value in the future. The reason that I'm still ultimately skeptical is that I believe that the equation for company success has one more element that we're not factoring for, which is human attention. In other words, even if there are 50 ideas among the 1,500 that Pulsia has created, on behalf of people and tweeted out, that would be highly resonant with me and that I might be a

Starting point is 00:27:35 prime target customer for. How am I possibly going to find them? I certainly don't have the time or attention span to go through all 1,500 tweets, and to then double-click into the ones that seem most promising and try to find out more. I am constrained as a customer by this scarce resource of time and attention that is not only not getting more abundant in the AI era, but is in fact getting much more scarce. And this gets, of course, to a larger problem with AI, one that we identify last year as the work slot problem. There is a massive gap between increased output and increased quality output. Business success is not determined by the number of slides or videos or memos. It's determined by outcomes, and just having more inputs does not a priori lead to better outcomes. So right now,

Starting point is 00:28:20 if you had to pin me down, I would say that I remain skeptical of the zero human company idea because of the way that the more that it produces interacts and has friction with the real constraints on demand, which is human attention. To reiterate, though, I think that the experiments, even if they are not valuable in terms of building a bunch of successful companies, are going to be incredibly valuable for actually understanding the opportunities and limits of what agents can do. Then again, who knows? Could be that in two years we're sitting here with Pulsia being much bigger than Shopify, and I look like Paul Krugman saying the internet would have the same impact as the fax machine.

Starting point is 00:28:54 Only time will tell, but for now, I'm just excited to see all these experiments. That, however, is going to do it for today's AI Daily Brief. Appreciate you listening or watching. As always, until next time, peace.

The AI Daily Brief: Artificial Intelligence News and Analysis - The Rise of the Zero Human Company

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