The Rise of the Zero Human Company

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.

Alright, friends, quick announcements before we dive in.

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And one other quick thing on aidelebrief.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 after month, and if you contribute to it, you will get the results before anyone

else.

Again, you can find that at aidelebrief.ai, 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 agent decoding 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 two 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 cloud code and codex, and who have recently decided that cursor is doomed.

At the end of February, Kyle Russell, who is at development lead at AI Finance Software

Startup Ballon, posted, this morning our CEO, Andrew Wang, requested that his cursor

seep be removed since he so deep into cloud 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.

TDOS of Menlo Ventures noted that the dynamics of enterprise procurement are far different

to the rapid service switching in startups and solar pernorship.

He wrote, narrative violation, cursor goes from 1 billion to 2 billion in three months.

Cloud code went from 0 to 2.5 billion in eight months.

Everyone on 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, tech Twitter says, cursor peaked, everyone's already

moved on to agents.

Next type, reality, ARR just doubled in three months to 2 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 Vanderwort, the CEO of Talent Startup Promote, also noted that there's actually some

meaningful differences between cursor and cloud code in the enterprise, commenting, cursor

is amazing for large code bases shared across many engineers.

Basically, the news hammer's 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 cloud code taking market share from cursor, it's

about the entire segment growing and growing fast, and that growth looks rapid and sustainable.

SPDK 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 cloud users finding the service

was down.

Clouds outage peaked at around 6.40am, right as I was using it before the kids got up.

Complaints fell by a third by 8.40, but Anthropics had an 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

unprecedented demand for cloud 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 & 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 scruffuffle with the DOD.

Indeed, according to data from sensor tower, chat GPT uninstalls tripled in a day between

Friday and Saturday.

US Daily Downloads fell by 13% day over day on Saturday and dropped by another 5% on Sunday,

which was a sharp break from the prior trend, where chat GPT downloads had been gaining

14% day over day on Friday.

One-star reviews for chat GPT surge by 775% on Saturday and another 100% on Sunday.

On the other side of the market, Anthropic's rise to number one in the App Store was driven

by their own surge in downloads.

The cloud app gained 37% on Friday and another 51% on Saturday.

Now to be clear, cloud has seen downloads something like 20X in a month according to

similar web.

Now the question, of course, is how persistent this switching behavior is?

Right now, chat GPT remains by far the dominant consumer AI platform.

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, Sam Altman has updated staff on revisions to open

AI'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, the AI system shall not be intentionally used for domestic surveillance of US persons

and nationals.

For the avoidance of doubt, the department understands this limitation to prohibit deliberate

tracking surveillance or monitoring of US persons or nationals, including through

the procurement or use of commercially acquired personal or identifiable information.

Altman added that the DOW has agreed that open AI 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 as supply chain risk and that they should be offered the same terms as open

AI.

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-clawed 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.

Silicon Valley representative Sam Lakardow 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

and 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 government using implicit threats and coercion rather than statutory powers.

Lakardow's bill is expected to be marked up in the House on Wednesday putting it on

the fast track 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 result 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 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 headset and trump are aware of them or not.

Lastly, today a fun little speculative one.

We might remember that around the Super Bowl, we got this leaked video that looked like

Alexander Skarsgard wearing these weird, bell-year device 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 disembowed that rumor, most ended up chalking

up the video as a hoax.

On Monday, however, Adam Founder's Zach Dive posted a picture in a video of Airbnb co-founder

and US government chief design officer Joe Gebbia in a San Francisco coffee shop.

In front of Gebbia 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 match the

ones from the ad.

Now, in 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 denied and built

curiosity.

Now, they have the CDO of America getting caught, quote-unquote, in a coffee shop with

a device.

Jog me up is thinking this is all a plant for a broader campaign, which if that's the

case is pretty cool.

For now, however, that is going to do it for today's headlines.

Next up, the main episode.

Agentic AI is powering a $3 trillion productivity revolution, and leaders are hitting a real decision

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KPMG's latest thought leadership paper, Agentic AI Untangled, navigating the build by

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Don't lock in the wrong model.

You can download the paper right now at www.kPMG.us-navigate, again, that's www.kPMG.us-navigate.

You've heard me talk about Assembly AI, and they're 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 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, they're fast, but they only see local silos of your code.

Research these tools across a large enterprise codebase and they quickly become less effective.

The fundamental constraint?

Context.

Blitzy solves this with infinite code context.

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all 5X faster.

See the Blitzy difference at Blitzy.com, that's B-L-I-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 AIUC1 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,

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 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 isn't 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 AIUC.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 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 back door into a speed discussion because smaller teams generally move faster

and faster teams generally win.

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.

From 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 Xi, who's now at Anthropic, has also been 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 start

up 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, you see companies that have four, five,

eight, basically single-digit employee accounts, and yet still millions in revenue.

Still, all of this is kind of a 2025 conception of tiny teams.

Sean, in fact, wrote that tiny team's 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 cloud code, 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.

Especially in the wake of open claw, 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 Kraft.

Felix was built by Nat Eliasin, and you may remember that when I was first covering open

claw actually back when it was clawed, but now was a person who I referenced.

While many of the other early experimenters were focused on sort of more plain administrative

tasks 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 claw agent

could function.

The output of that has been Felix Kraft.

Like many of these experiments, Felix didn't come into existence with a single focus 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, the Felix

Kraft dashboard at FelixCraft.ai shows how those experiments have gone.

Since exactly 30 days old, in its lifetime Felix Kraft has generated just under $78,000

in revenue.

There's been a fairly big pick up 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, 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 workspaces

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 deemphasize

it compared to the others, but overall it's generated just 230 in revenue.

The other big portion of revenue comes from Clomart, which you can find at shopclomart.com.

Clomart 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 Clomart.

The first are actual AI configurations and AI personas that you can buy wholesale.

For example, for $49 you can get Tegan, a content marketing AI with a multi-agent writing

pipeline, Grock 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 Coder 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.

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 Polsia.

Polsia goes even more meta.

Instead of just being a zero human company, Polsia is a platform for building zero human

companies.

It comes from entrepreneur Ben Cera or Ben Broca, I've seen it both ways, 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

that where I could build a thousand companies.

So it started with this crazy idea and I was like, you know what, let me start at the

end state because we all know the end state is that AI can do everything.

So let me build that now and see what breaks.

And so I started building it in November of last year 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, the Opus 4.5, 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, build a platform

to try to let it do everything and just wait it to see what would break in actual practice.

The platform is called Polsia and basically it's a platform for running companies autonomously.

When you sign up for Polsia, you can either grow your own company or 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 episode only to realize that it hadn't been plugged in.

So this is now the second time that I've had Polsia go out and 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 recognized

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.

And so as we wait for Polsia to determine what my second autonomous company would be,

this is what Polsia does.

Once you settle on an idea, it builds a mission statement, it does a market research guide,

it tweets it out on the Polsia Twitter account, and starts to do other things like build a

home page 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, Polsia 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 background.

Here's how Ben explained it on the product on 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 and that the real goal is to make money as the businesses launch with Polsia make money

taking a 20% rev share.

Ben says, think incubator not sass.

There is a lot of interest in Polsia, and to the extent that Polsia has become ground

zero for the broader zero human company space, clearly a lot of interest in the broader trend.

Since the beginning of February, Polsia has jumped from low single digit thousands of

ARR to a run rate of 1.5 million today.

That run rate has jumped a million dollars in one week.

There are now over 1500 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 Polsia, believe it or not, it is once again created almost exactly the

same 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, KPIs, performance

reviews, and org chart level visibility.

One dashboard for your entire digital workforce.

Now Polsia is not the only company going after this platform for zero human company space.

AI creator Tom Osman has also recently announced the ZHC company, ZHC standing of course

for zero human company, ZHC.company reads, ZHC is an autonomous AI platform that builds

and runs entire companies.

From CEO to developer, every role is an AI agent working 24-7.

Like Polsia, 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 1500 companies that are working

on Polsia.

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, hearkens back to the idea that we were talking about around Felix Crafts

had a higher in AI guide, where a lot of the early revenue that's actually realized

is from other 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 9.47 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.

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, often times 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 solar pranor has grown significantly, whereas the only type of entrepreneurship that

people used to talk about in 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 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 Pulsi is 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.

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 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.

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 resonance in the market.

That's effectively what a company like Polsia 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 them, 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 1500 that Polsia has created on behalf

of people and tweeted out, that would be highly resonant with me, and that I might be a

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 1500 tweets and then

double click into the ones that see 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 identified last year

as the work slot problem.

There is a massive gap between increased output and increased quality output.

This 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 priority lead to better outcomes.

So right now, 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.

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!