The $10 Billion Startup Training AI to Do Your Job

Summary

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Podcast Summary: "The $10 Billion Startup Training AI to Do Your Job"

Podcast: The Big Take (Bloomberg & iHeartPodcasts)
Episode Date: April 29, 2026
Host/Reporter: Tom Foster
Main Guests: Tasha Kozak (Social Worker), Mercur contract workers
Main Theme: Exploring how the tech startup Mercur is reshaping white-collar work by paying professionals to train AI models to eventually perform — and potentially replace — their jobs.

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Overview

This episode delves into Mercur, a $10 billion-valued startup at the center of a new labor market: hiring skilled professionals not to do their old jobs, but to teach AI how to do them. Bloomberg reporter Tom Foster unpacks Mercur's rapid ascent, its ambitious vision for the future of work, and the looming implications — both hopeful and troubling — for workers, the AI industry, and the broader economy. Through interviews and insights, the episode examines the rewards workers are seeing, the existential anxieties sparked by this trend, and the controversies already dogging Mercur’s model.

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Key Discussion Points & Insights

1. Layoffs and Market Forces Driving AI Adoption

• Companies like Meta, Block, Amazon, and Microsoft are making steep job cuts, attributing them to efficiency drives fueled by AI investment.
• The job market remains ostensibly stable, with the Fed keeping rates unchanged amid low job growth and elevated inflation.
• Quote:

  “The dramatic moves only add to the sense that artificial intelligence could be coming for human jobs.” — Tom Foster (02:09)

2. Mercur’s Unique Business Model

• Mercur appears on job boards, advertising high-paying freelance gigs for roles like “editor in chief” or expert filmmaker. These are not traditional jobs; the core task is to train AI by modeling how the job is done.
• Mercur supplies these training services to companies like OpenAI, Anthropic, and Google (03:23).
• Quote:

  “What you're doing is you're lending your expertise in your field to the AI models to train them how to do your job.” — Tom Foster (03:46)

• This work is detailed, breaking jobs into micro-steps for the AI to learn (05:08).

3. The Work of Training AI — Real-World Examples

• Broad range of professionals are hired: doctors, social workers, writers, physicists, and more.

• Example: Tasha Kozak, a full-time social worker, does 20 hours weekly on Mercur (in addition to her 40-hour district job) and makes roughly the same income.

• Tasks include feeding AI fictional scenarios, lab reports, and crafting individualized responses — essentially distilled expertise delivered as data.

• Quote:

  “At the end of the day, AI is a machine. And even though humans are training, always takes a human eye... In the center of social work, we say: meet the person where they're at. I think it would be a very long time until any sort of AI... will be able to do that.” — Tasha Kozak (08:31)

• Hierarchical review system: Work done by one freelancer is reviewed by another, and that review is also reviewed — mimicking academic/journalistic quality control (07:50).

4. Motivations and Concerns for Workers

• Motivations: Flexibility, high pay, opportunity to shape the tools that may one day replace them, or (as one doctor said) to avoid becoming obsolete.
• Risks/Limits: All assignments are short-term, unpredictable, and offer no employment guarantees. When AI “learns the job,” the opportunity may vanish (10:49).
• Quote:

  “There's no guarantee how many hours per week you're going to get. There's no guarantee how long this gig is going to last. There's no guarantee if this gig ends that there will be another one for you.” — Tom Foster (10:49)

5. Mercur's Founders & Silicon Valley Philosophy

• Three founders, all Silicon Valley natives, aged 23, with typical tech pedigrees and a Peter Thiel fellowship backing.

• Original idea: Build a “LinkedIn on steroids” as a global labor clearinghouse, later pivoting to supplying experts to train AI (11:45).

• Quote:

  “What he wants to do is basically, ultimately, he thinks there won't even be like real job jobs. Everything just sort of becomes a gig and it becomes this global marketplace of talent. Companies don't really need employees. What they need is work done.” — Tom Foster, describing founder Brendan Foody’s vision (12:55)

• The company is already worth $10 billion and backed by top-tier investors: General Catalyst, Benchmark, Peter Thiel, Larry Summers, Jack Dorsey, etc. (13:55).

6. Critics, Risks & Legal Challenges

• Many gig workers express dissatisfaction on forums like Reddit: lack of stability, unpredictability, algorithmic management.
• Worker misclassification lawsuits — echoes of Uber, Lyft, and other gig platforms.
• Massive data breach (4TB of data leaked), with unclear impacts. Meta suspended its partnership post-breach; other companies are reevaluating (18:20).
• Mercur has issued only minimal responses to these crises (20:13).

7. Is AI Actually Ready for These Jobs?

• Despite the hype and investment, the current reality is that AIs are still not competent at most skilled white-collar jobs — but are catching up fast (21:08).

• Investors remain confident, but debate persists about whether AI will really replace or simply augment skilled professionals (21:26).

• Some layoffs may be “AI-washing,” using AI as a convenient reason for broader cost-cutting (22:36).

• Brendan Foody’s rationale:

  “What this will do is free up opportunities to work on bigger and bigger problems. Because of all of this, we will now get to spend more time on the moon and go to Mars and cure cancer and do all these other large things because we are freeing up humans from doing all the drudgery.” — Tom Foster, paraphrasing Foody (23:23)

8. The Future: A Glimpse at AI-Managed Workforces

• Beyond training, the infrastructure to manage, deploy, and maintain swarms of company-specific AI “agents” may become a huge market. Mercur wants to be the central hub for both humans and AI (23:59).
• Quote:

  "Once you've got this like, workforce of AI agents out there, there has to be infrastructure for them. And Mercour and a bunch of other companies see that as an enormous opportunity..." — Tom Foster (23:59)

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Notable Quotes & Memorable Moments

• On the existential shift:

  “How much of our work actually requires that human skill. We've all thought the line is in one place, but as the AIs are learning these jobs, I think we're all learning the line might be in a slightly different place than we thought it was.” — Tom Foster (09:19)

• The gigification of white-collar work:

  “This is his idea... There won't even be real job jobs. Everything just sort of becomes a gig... Companies don't really need employees. What they need is work done.” — Tom Foster (12:55)

• After the Data Breach:

  “There was a large data breach just a couple of weeks ago... Within a week of this coming out, there were at least five other lawsuits... user data as well as training data.” — Tom Foster (18:20)

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Timestamps for Key Segments

• 02:09 — AI-linked layoffs at major tech companies
• 03:23 — Mercur’s real business: experts training AI
• 07:24 — Tasha Kozak explains AI training process
• 10:49 — Insecurity and limits of gig AI-labor
• 11:45 — Origins of Mercur’s founders and business model
• 18:20 — Lawsuits, worker complaints, and data breach crisis
• 21:08 — Is AI really ready? Market vs. reality
• 22:36 — Layoffs, “AI-washing,” and the future of work
• 23:59 — Managing future fleets of AI agents: Mercur’s next play

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The Takeaway

This episode gives a candid, insider’s look at a new wave of “AI gig work” — where the expertise of today’s skilled professionals is directly used to build the AIs that might eventually replace them. Mercur sits at the heart of this change: admired for lucrative, flexible gigs and Silicon Valley ambition; criticized for its precariousness and legal/ethical gray areas. The future for such work — and for Mercur — is uncertain, raising fundamental questions about the value of human skill, the social contract of employment, and how much we’re willing to trade stability for technological progress.

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Transcript

[Microsoft Representative]

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[IBM Representative]

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[Tom Foster (Bloomberg Reporter)]

Bloomberg

[Adobe Representative]

Audio Studios Podcasts Radio News for tech

[Tom Foster (Bloomberg Reporter)]

workers, it's been a long season of layoffs. Meta telling staff that it will cut about 10% of its workers in order to boost efficiency and offset its heavy spending on artificial intelligence.

[Tom Foster (Narrator/Reporter)]

Block Jack Dorsey's company up more than 23%. It's cutting 4,000 employees. It's reducing its workforce by nearly half.

[Tom Foster (Bloomberg Reporter)]

Metta and Block, Amazon and Microsoft. They've all announced plans to downsize as they lean into AI. The dramatic moves only add to the sense that artificial intelligence could be coming for human jobs. Maybe not quite yet. Data show the labor market isn't as bad as it feels. Today, the U.S. federal Reserve announced it would be keeping rates unchanged, citing, among other things, a stable unemployment rate, low job growth, and elevated inflation. Reporter Tom Foster has been digging into how AI could actually transform white collar work ever since he noticed a company called Mercour popping up on online job boards. Mercour seemed to be hiring for all sorts of roles, from filmmaker to Quantum field physicist.

[Tom Foster (Narrator/Reporter)]

So somebody in my background, you know, I'll see a listing that says editor in chief and I'm like, that's interesting, sure, but it's hourly and how does that make sense? But the pay is really good. It's very good hourly pay.

[Tom Foster (Bloomberg Reporter)]

Tom wanted to understand what this company was all about, so he started doing some reporting for Bloomberg Businessweek.

[Tom Foster (Narrator/Reporter)]

Just trying to figure out what is this thing, and then realized, oh, this is the future.

[Tom Foster (Bloomberg Reporter)]

Merkur isn't really offering a well paying hourly editor in chief role itself, but it is hoping an experienced editor or journalist will be intrigued enough to apply and teach artificial intelligence systems what only an editor in chief would know. Merkur is just the middleman. The training gigs are for companies like OpenAI, Anthropic or Google.

[Tom Foster (Narrator/Reporter)]

What you're doing is you're lending your expertise in your field to the AI models to train them how to do your job.

[Tom Foster (Bloomberg Reporter)]

Through interviews with some of Merkur's founders and contract workers it's hired, Tom has pieced together the company's business model and its ambitions to transform work itself.

[Tom Foster (Narrator/Reporter)]

What the future of work looks like in this vision is humans training AI.

[Tom Foster (Bloomberg Reporter)]

I'm Sarah Holder and this is the big take from Bloomberg News today. On the show, the upstart company that's trying to help turn big chunks of white collar jobs over to AI, making its founders the richest young tech entrepreneurs since Mark Zuckerberg and providing a blueprint for a future in which we all work in the gig economy. Tom Foster says that when you answer a Mercur job listing, things can move fast.

[Tom Foster (Narrator/Reporter)]

You get pretty quickly ushered into an interview and you're being interviewed by a robot, and then you're, you're talking to this, this AI, and the AI AI asks you about your job and asks smart questions.

[Tom Foster (Bloomberg Reporter)]

What kinds of jobs is Mercur hoping to automate or hoping to work with these white collar professionals to train AI models to do?

[Tom Foster (Narrator/Reporter)]

The question is, what kinds of jobs are they not? I mean, like everything really. The way they talk about it is that the first sort of round of AI training kind of came from the Internet and it was more or less general knowledge. And these models know a lot about all of these fields. But there's a difference between knowing a fair amount about these fields and being able to do these jobs. And that is the bridge that all of these companies are trying to cross. And to do that, it requires not just hiring thousands of doctors, lawyers, journalists, et cetera, but creating these exercises, these very, very specific, regimented exercises that Teach the models, step by micro step, how to do every particular aspect of that job.

[Tom Foster (Bloomberg Reporter)]

It's not hard to imagine how, say, an administrative assistant might train AI to do much of their work, but Mercur is trying to do that with highly specialized roles that have historically required a human touch, like medicine.

[Tom Foster (Narrator/Reporter)]

So it's like you're a doctor here, you know, lab reports, here's. Let's learn how to read the labs. What are the diagnoses we should make from them? What are the sort of plan of action we should put together from that?

[Tom Foster (Bloomberg Reporter)]

Or social work.

[Tasha Kozak (Social Worker)]

There's nothing quite as fulfilling as when you're able to connect with someone and help them kind of progress when they're in a really difficult time.

[Tom Foster (Bloomberg Reporter)]

That's Tasha Kozak, a social worker Tom spoke with.

[Tom Foster (Narrator/Reporter)]

She's based in Florida. She works for a giant school district there. And, you know, she really loves her work, but she, you know, a lot of the time she spends on her work is doing administrative stuff.

[Tasha Kozak (Social Worker)]

I think AI is fantastic for helping to put together reports, to consolidate information for data tracking.

[Tom Foster (Narrator/Reporter)]

And so she figures, you know, hey, I'm going to train the AI to take away all these sort of administrative parts of my job.

[Tom Foster (Bloomberg Reporter)]

Tasha told us a little bit more about what she does when she clocks into her Mercur gig after school or on the weekends. To train an AI model, Tasha would, for example, provide information about a hypothetical student and teach the AI to interpret that data.

[Tasha Kozak (Social Worker)]

For example, giving some student details, maybe some fictional medical records that I created, a story about their family situation or their, you know, current personal issue. And then the prompt itself would be to create a certain report for the student.

[Tom Foster (Bloomberg Reporter)]

Reports like an individualized education plan tailor made for the fictional student. Tasha works on a team with other Mercour workers.

[Tasha Kozak (Social Worker)]

When I started, you had a different selection of social workers who would review the work, and then you had reviewers who would review the reviewer's work. Really just hierarchy of different levels of review, which I think is really important because another person is going to have a different perspective and a different experience.

[Tom Foster (Bloomberg Reporter)]

Social work feels like such a human job. Not only the interactions you're having with clients, students, but also even the paperwork and the kinds of decisions that you're making about people's futures. I'm wondering if you can talk me through how you think about training an AI to take on that role.

[Tasha Kozak (Social Worker)]

At the end of the day, AI is a machine. And even though humans are, training always takes a human eye. If you're making a determination of, you know, suggesting next steps for the academic future of a child, you need that set of eyes and you need to also communicate with the person that you're making these decisions about. In the center of social work, we say meet the person where they're at. I think it would be a very long time until any sort of AI concept or technology will be able to do that.

[Tom Foster (Bloomberg Reporter)]

Tasha isn't too worried about AI fully replacing social workers anytime soon. But Tom says the work she and others do for Mercur is raising more fundamental questions about the real value of a human touch.

[Tom Foster (Narrator/Reporter)]

How much of our work actually requires that human skill. We've all thought the line is in one place, but as the AIs are learning these jobs, I think we're all learning the line might be in a slightly different place than we thought it was.

[Tom Foster (Bloomberg Reporter)]

You also spoke to a doctor of internal medicine. You spoke to a novelist, screenwriter. These are really a wide range of professions that people are bringing to Mercur. I'm wondering what is in it for them? Like, why do all these people end up working for Merkur?

[Tom Foster (Narrator/Reporter)]

There are a whole bunch of reasons. It's fascinating. The writer, this is a person who's done numerous television shows, written novels, like a very successful screenwriter and fiction writer. And she, ever since the Hollywood writers strike, she's currently sort of underemployed. Tasha Kozak, the social worker, she works 40 hours a week doing social work for the school district. She works another 20 hours working for Mercur every week. And she makes as much money in those 20 hours working for Mercur as she does in the 40 hours working in her actual full time job. The doctor I spoke with was really fascinating. She's an internist and her take is I'm doing this work so that I will not be obsolete. Because this is coming whether we like it or not. Let's. Let's learn how to be a part of it.

[Tom Foster (Bloomberg Reporter)]

But isn't there a limit to how much work you can get from a company like Mercur? If you train the AI, they can do the job as good or better than you.

[Tom Foster (Narrator/Reporter)]

I had this thought too, as I was sort of going through it. I was like, well, what happens when they're done? We've done it, we've trained the robots, let's close down the shop. Their take is there's just an infinite amount of this. We're nowhere near where that is in terms of what the variety of jobs that can be trained for is or the variety of tasks within those jobs. But that said, there's this whole Other aspect that once you're in the Mercour system, these are short term jobs, these are part time jobs. There is no guarantee how many hours per week you're going to get. There's no guarantee how long this gig is going to last. There's no guarantee if this gig ends that there will be another one for you or when, or that it will pay the same.

[Tom Foster (Bloomberg Reporter)]

So I want to talk a little bit more about the young founders of Merkor. Who are they and how did they get their start?

[Tom Foster (Narrator/Reporter)]

These guys they met in high school in Silicon Valley. There's three of them. They all come from sort of of tech family backgrounds, you know, parents or software engineers or. One's father was a founder of a company, a tech company. And one of the three founders was, was recently sort of moved out of an executive position into a chairman position. And the other two who remain are now co CEOs Brendan Foody and Adarsh Hiramath. They just turned 23. They all went to college for two years, did the typical drop out of college and start a company in this with the help of Peter Thiel. They applied for one of those Thiel fellowships where you get a couple hundred thousand dollars to start, you know, a moonshot company. And their, their idea was not actually training AI. Their idea was this is such a classic Silicon Valley thing. Brendan talks about the, the labor marketplace. This is a guy who's never had a job in his life, right? The labor marketplace is the most inefficient marketplace, you know, in history on Earth. There are, you know, billions of people looking for jobs, billions of jobs out there and no central clearinghouse.

[Tom Foster (Bloomberg Reporter)]

Has he heard of LinkedIn?

[Tom Foster (Narrator/Reporter)]

Well, what he wants to do is like several orders of magnitude more specific and maybe invasive than LinkedIn. What he wants to do is basically ultimately he thinks there won't even be like real job jobs. Everything just sort of like becomes a gig and it becomes this global marketplace of talent. Companies don't really need employees. What they need is work done. This is his idea. When they founded the. They will be the one company that has all the data on every person on the planet and their professional abilities and every single job or task or whatever that a company needs done will then be hired through this global database that this company has of all the sort of labor data in the world. They claim that they started building this global labor marketplace, this like LinkedIn on steroids. And realized in the process, as they were sort of working with some companies, what these companies need are like domain experts in all these other Fields as they're training for AI. And so they kind of pivoted to that. You know, venture capitalists are very eager to fund AI projects. And here was one that is essentially like infrastructure for the AI boom. So they started raising a whole lot of money. They're valued at $10 billion. They've raised about 500 million from, you know, the likes of General Catalyst, it's Benchmark, it's Peter Thiel, it's Larry Summers, Jack Dorsey, you know, this sort of like murderer's row of venture capitalists and other investors.

[Tom Foster (Bloomberg Reporter)]

What future of work are they building towards?

[Tom Foster (Narrator/Reporter)]

Yeah, I mean, I'm not entirely clear on that. I mean, I tried to have these conversations about, like, you know, the meaning of work and what we as humans draw from our work and, you know, the craft that we've perfected and all this. It's not really about that. It's a very Silicon Valley way of thinking where everything is just looked at in the abstract. And in the abstract, it's this idea that, sure, there are probably going to be some job jobs, but for the most part, what companies want is tasks completed. You've got AI agents doing the jobs and you've got humans overseeing them and training them and making sure they're doing it right. So in some ways, what people are doing for Merkor right now is, is a glimpse of the future of work.

[Tom Foster (Bloomberg Reporter)]

After the break, the people questioning Mercur's vision of the future and the investors who are betting on it.

[IBM Representative]

So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill their HR questions, resolving 94% of common questions, not noise. Proof of how we can help companies get smarter by putting AI where it actually pays off, deep in the work that moves the business. Let's create smarter business.

[Microsoft Representative]

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[Tom Foster (Narrator/Reporter)]

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[Microsoft Representative]

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[Tom Foster (Bloomberg Reporter)]

As Mercour helps AI companies upskill their machines, Tom Foster says the company has also been dealing with some human drama.

[Tom Foster (Narrator/Reporter)]

It is a controversial company, no question, and these guys know that. Of course, if you go spend some time on Reddit, for instance, you will see very quickly a whole lot of people complaining about Mercur and also people, you know, quite happy about the money they're making and, you know, thinking they're building the future. The complaints have to do with, you know, you take a gig and you don't know when it's going to end or whether it will end. And, you know, you have no job security. You know, what Merkur says in sort of its defense is like, hey, we were upfront about that. When you think about work as a series of tasks to be completed by task completers, these humans are just Kind of machines and you treat them like machines. Right. And that's where when people run up against the difficult side of that, they get angry. There have been class action lawsuits about misclassifying workers. So this is the kind of thing we have seen with other gig marketplaces where it's about, you know, should these people be contract employees or full time employees? Saying that everything that is expected of these people, they should be full time employees, not contract employees. That of course would break the entire model. Right. So another thing that's happened, there was a large data breach just a couple of weeks ago, as many as 4 terabytes of data. It's not clear exactly what was sort of exposed in this breach, but user data as well as training data seems to be the case. According to the hackers, what they posted on the Internet, that is a big deal. Within a week of this coming out, there were at least five other lawsuits that came out that were about not protecting users data. Almost immediately Meta paused all of its work with Mercour. The other companies, it's not clear, but obviously we're assessing their relationship with the company.

[Tom Foster (Bloomberg Reporter)]

How has the company responded to these lawsuits over worker classification and how did they respond to the data breach?

[Tom Foster (Narrator/Reporter)]

The company has essentially not responded to the data breach. They are investigating using a third party firm to help do a deeper deep dive investigation. In terms of the lawsuits, same thing. You know, they acknowledge that the lawsuits are there, they won't say anything in particular about it.

[Tom Foster (Bloomberg Reporter)]

And Tom, I mean, we've talked about a few different ideas of how AI might change the economy, change the labor force. You know, there's people who think AI is going to automate away thousands of jobs, completely upend the economy for better or worse. People who think it's mostly just going to, you know, augment productivity, change what kind of jobs we do, and that the economy will ultimately be able to adapt. There are disagreements about how fast this is all going to happen. What does the data actually tell us about how AI will and is already changing work?

[Tom Foster (Narrator/Reporter)]

That's the biggest question, right? They can say, hey, we're training the robots to do your jobs, but is it working? Can the robots do the jobs right? What are they actually capable of? The fact is the AI is nowhere near ready to do these jobs competently at this point, but it is improving very quickly.

[Tom Foster (Bloomberg Reporter)]

What does mercur's financial success reveal about at least the markets and investors belief in AI's capabilities right now? And what is the contrary case? Are there detractors who are worried that this Valuation is overblown and that AI is not going to be able to replace human work to this extent.

[Tom Foster (Narrator/Reporter)]

Mercour is profitable according to them. They're having no trouble raising money. It doesn't seem like there are investors who are pausing much. But that's the case with any of these AI companies. It seems to me that their experience is sort of in line with what we're seeing across the entire AI market. Is it all going to pan out to be worth that? I don't have the answer.

[Tom Foster (Bloomberg Reporter)]

And just zooming out from Mercour a little bit more, we've seen some high profile examples of companies justifying major layoffs with just this, with the idea that AI is going to be able to reduce the need for a large human workforce. I'm wondering how Mercur's founders might see this news. Do they see those layoffs as confirmation of their thesis?

[Tom Foster (Narrator/Reporter)]

I mean, they believe that we are moving in that direction. Yes. That, you know, there will be job losses, there will be, you know, types of jobs that just go away entirely. What most people say, including some folks at Mercur, maybe we're seeing a wave of AI washing here where people are doing rounds of layoffs for other reasons and attributing it to AI because that makes it look like they are ahead of the game or something, when in fact maybe there were some performance issues with the company. In terms of what Merkur thinks about all of this, yes, they talk about. Brendan Foody, the CEO, talks a lot about there will be job categories that go away, but also there will be new types of work that emerge. And whether that is new tasks within companies, learning to train AI or whatever, or as he likes to say, what this will do is free up opportunities to work on bigger and bigger problems. Because of all of this, we will now get to spend more time on the moon and go to Mars and cure cancer and do all these other large things because we are freeing up humans from doing all the drudgery.

[Tom Foster (Bloomberg Reporter)]

And Tom says that kind of future could be especially bright for Mercur.

[Tom Foster (Narrator/Reporter)]

There's the question of like, building AI agents for companies. Who manages them, how are they deployed, how are they trained, how are they maintained? How do all of the things, you know, once you've got this like, workforce of AI agents out there, there has to be infrastructure for them. And Mercour and a bunch of other companies see that as an enormous opportunity for the company.

[Tom Foster (Bloomberg Reporter)]

This is the big take from Bloomberg News. I'm Sarah Holder to get more from the big take and unlimited access to all of bloomberg.com, subscribe [e-mail] podcastoffer if you like this episode, make sure to subscribe and review the Big Take. Wherever you listen to podcasts, it helps people find the show. Thanks for listening. We'll be back tomorrow.

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[Microsoft Representative]

leaders, word on the street is security incidents are dropping way down with Windows 11 PCs built in. Security for the Win upgrade to Windows 11 Pro at windows means business.com hey

[Tom Foster (Bloomberg Reporter)]

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