The AI Daily Brief: Artificial Intelligence News and Analysis - Why AI Could Be Better for Plumbers than Programmers

Why AI Could Be Better for Plumbers than Programmers

Feb 22, 2026 - 22m 56s

AI is reshaping the economy—but not always in the way most leaders expect. This episode explores why AI could matter more for plumbers than programmers, shifting leverage to trade entrepreneurs by removing operational friction rather than replacing skilled labor. From Gen Z’s growing pivot toward the trades to the rise of agentic tools that unlock scale without headcount, the real opportunity isn’t cost cutting—it’s empowering small operators to run dramatically better businesses.

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AI's Impact on Blue Collar Workers vs. Programmers

The episode discusses the shifting dynamics of AI's impact on the job sector, highlighting the idea that AI may significantly benefit blue-collar workers more than programmers. David Heycock's op-ed illustrates how AI can enhance operational efficiency in plumbing and other trades, allowing workers to manage more complexity without expanding their workforce. This shift changes the leverage dynamic, making it crucial for businesses to consider how AI can empower rather than reduce their workforce.

Changing Perceptions of Blue Collar Work

The discussion brings to light a cultural shift among younger generations, particularly Gen Z, who are increasingly viewing blue collar jobs as more stable and potentially rewarding in the face of AI's advancement. Surveys indicated a growing skepticism toward traditional college education, with many Gen Z individuals exploring trade professions for their perceived resilience against AI job displacement.

The Future of AI in Physical Businesses

As AI technology evolves, its integration into blue-collar sectors remains at a nascent stage. The episode speculates on how AI will allow trade entrepreneurs to significantly enhance their businesses by removing operational friction rather than replacing skilled labor. The possibilities range from improved scheduling to better forecasting, creating efficiency without reducing headcount, which has been a common fear in conversations about AI.

Opportunities and Challenges in Trade Professions

Despite the promising outlook for AI in blue-collar work, the conversation acknowledges potential threats, particularly from the emergence of embodied AI. However, the advantages of AI providing leverage and operational efficiency are emphasized, suggesting that those willing to embrace it can find significant opportunities in what may currently be seen as lower-tech sectors.

Transcription

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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That today we're exploring a theme which I think is going to be a growing topic throughout the year.

In short, it's what sort of impact AI is going to have on blue collar workers, both in terms of swelling their ranks, as well as potentially changing the nature of how they run their businesses.

This is a topic that is growing as a focus, particularly as we get farther into the AI change, and we start to get better glimpses of how AI might actually impact the jobs market, especially in the short term.

To be clear, I think we still have absolutely no idea what things are going to look like in the future, but regardless of that, there is going to be a big transitional period with a lot of change during it, even if it's not the end state.

Now, this is of course a long-read slash big-think episode, and the specific catalyst for this was an op-ed in Fortune magazine by David Heycock.

David is the CEO and founder of Filter Buy, which is a direct-to-consumer air filtration company.

Filter Buy generates over a billion dollars in revenue, has more than seven million customers, and employs over a thousand people.

The company was also fully bootstrapped.

Now David himself has an interesting path.

He started his career as an options trader at Goldman Sachs, but in 2012 he left Wall Street to take over the family business which was this filter manufacturing business.

So the piece is titled, and keep in mind this was written by an editor I guarantee, I'm a CEO who grew a quote unquote boring air filter business into a $260 million company.

And AI is going to help blue collar everyday people just like me.

Now, this is just the latest in this theme that I've seen, so first let's read this piece it's not all that long, and then we'll get into the broader context.

David writes, When I was 13, I had a side hustle building websites for local businesses.

This was the 1990s, building a site meant weeks on a dial-up connection, hand-coding HTML line by line, and breaking layouts because you missed a single character.

If I made $2,000 in a summer, it was because I gave up nearly every waking hour to do it.

My income was capped by how fast I could work.

Around that same time, my grandfather gave me advice that I still come back to, focused on building something people actually need.

He had spent his life running a real business, serving real customers, and he had little patience for trends that didn't solve a clear problem.

Years later, when I was exploring different product ideas, I ran them by him.

Some were flashy.

One was even sneakers.

He listened politely.

Then I told him I was thinking about air filters.

filters.

He leaned in.

Air filters made sense.

People need them.

They're not exciting, but they matter.

That reaction told me I was on to something.

Today, I run Filter Buy, a $260 million domestic manufacturing company that makes and ships air filters across the country, looking back that early experience taught me something most people still miss.

Effort scales poorly, but leverage compounds.

That's why I think many leaders are mistreating what AI actually represents for the economy.

Most executive conversations about AI focus on risk, regulation, or cost reduction.

Those are valid concerns, but they miss the larger shift.

AI isn't primarily about replacing workers or cutting headcount.

It's about changing who gets leverage.

For most of American history, leverage belonged to people who could hire large teams, raise capital, or build software.

Everyone else traded time for money.

That's now changing, and the biggest beneficiaries won't be programmers.

They'll be people running practical non-tech businesses.

Consider what a small service operator looks like today.

A plumber, HVAC technician, or local manufacturer spends a surprising amount of time on work that has nothing to do with their core skill.

Scheduling job, sending invoices, following up with customers forecasting demand.

Those tasks aren't hard, but they create friction.

Over time, that friction caps growth.

AI doesn't eliminate the need for skilled labor in those businesses.

it removes the drag around it.

A plumber who uses AI to handle dispatching, estimates, customer communication, and follow-ups is no longer limited by paperwork or missed calls.

That operator can serve more customers with the same crew, reduce stress, and run a cleaner business.

The work itself doesn't change.

The scale does.

That's why I believe AI matters more to plumbers than programmers.

In tech, AI often improves something that already scales well.

In physical businesses, it changes the math entirely.

It allows one capable operator to manage complexity that used to require layers of staff or outside vendors.

You're no longer growing by adding people as fast as revenue.

You're growing by removing bottlenecks.

We've seen this first hand at FilterBuy.

We didn't use technology to replace people on the factory floor.

We used it to clean up scheduling issues, improve forecasting, reduce errors, and speed up decision making.

The value didn't come from automation alone.

It came from giving our team better tools and fewer obstacles.

That's where I think many AI discussions go wrong.

They focus on novelty and set of deployment on vision decks instead of daily operations.

In non-tech industries, the opportunity isn't to build something flashy.

It's to quietly remove the friction that holds good businesses back.

This has implications for the C-suite.

The wrong question is, how do we use AI to cut costs?

The better question is, how do we use AI to make our people more effective?

If you have 100 employees, the goal shouldn't be to get to 80.

It should be to allow those 100 people to operate at a higher level.

That's where durable value is created.

Companies that do this well won't look radically different from the outside.

They'll just execute better than everyone else.

We're entering a phase where AI stops being a topic and starts being infrastructure.

It won't sit in a separate strategy deck.

It will show up and how work actually gets done.

One, scheduling will be tighter, decisions will be faster, fewer things will fall through the cracks.

I've spent my career leaning into physical goods and so-called boring businesses because that's where real economic value is built.

AI is the first tool I've seen that meaningfully shifts leverage towards people who operate in that world.

The internet gave us access to information.

AI is giving us access to operational leverage.

For leaders willing to apply it, where work actually happens, not where it looks impressive, the upside is real.

The companies that win won't be the loudest about AI.

They'll be the ones quietly using it to run better businesses.

All right, so back to NLW here.

Thanks, of course, to David for writing that.

And there are actually a couple different ideas going on in there.

One of them is applicable to everyone.

It's not just about blue collar.

It's about the idea of how to conceptualize AI basically for any leader.

David's argument, which is what I agree with, is that the losing way in the long term of looking at AI as a cost-cutting technology, and the winning way in the long-term is looking at it as an opportunity creation technology.

We always talk about this in the context of efficiency AI versus opportunity AI.

David is applying that to the mindset of corporate leaders who need to set goals for what their AI initiatives are supposed to achieve.

The lessons that he's applying the idea that team members can have more leverage isn't just restricted to real-world physical or blue collar businesses.

It's available for anyone.

And all of that is 100% true.

But the part that I want to explore is the context of physical real world businesses.

And ones, I think, that are much smaller than even those being described by David in this piece.

One of the things that makes AI so interesting is that it breaks the trend of the last couple hundred years where new technology changes tended to hit blue collar workers first, at least the negative side.

Right now, what we're seeing is that the places where the most realized disruption is happening is in fact in white collar rolls.

The way that people think about programmers themselves, for example, is changing.

Now I think the jury is very much still out on how that all shakes out.

We're going through a period where there's a lot of AI job displacement concern and a fair bit of job displacement, but job displacement that clearly has a lot of other factors going on besides just AI.

The other thing is, of course, even though AI can do the work that programmers used to do, my base case is still that we end up with radically more programming jobs, versus everyone just firing the programmers they have access to, but it will take time to see how that all shakes out.

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I think David is right to point out that AI gives the people who choose to wield it well way more leverage.

And it's leverage that in the hands of blue collar businesses can be incredibly powerful.

Now, there are actually a lot of different conversations happening right now when it comes to the relationship between AI and blue collar work.

First of all, there is just simply put more demand for blue collar workers because of the AI data center buildout.

Last September, Ford CEO Jim Farley warned that we simply didn't have enough skilled workers in areas like construction and maintenance.

Said Farley, I think the intent is there, but there's nothing to backfill the ambition.

How can we reshore all this stuff if we don't have the people to work there?

These comments came as Farley actually hosted a summit in Detroit called accelerate the essential economy, though it is all about expanding the pipeline of these skilled essential workers.

In a blog post, Farley estimated that the US needed 600,000 more manufacturing workers, 500,000 more construction workers, and 400,000 more automotive technicians.

Farley said it looks like a people problem, but it's actually not that simple.

It's an awareness problem.

It's a societal problem.

If I were to take the typical American family and say, would you rather your kid be a software programmer making 170,000, or be an HVAC specialist to make 97,000, which one would you prefer, I would say many, many Americans would prefer the software engineer.

And yet, the steady drum beat of people calling for more blue collar workers just continues to get louder and louder.

Recently at the World Economic Forum and video CEO, Jensen Huang, argued that the value of blue collar work would increase.

Partially that's because he sees entire new categories of blue collar work in roles that mix physical work with digital NAI tools.

Think about data center technicians, workers who deal with advanced manufacturing equipment, or like Farley was talking about the team's responsible for the energy and infrastructure build out.

Now what's interesting is that Gen Z kind of seems to be taking up the call, and while Farley's comments about what families would prefer for their kids might be true in some areas, there is a bit of a cultural shift underway.

Last July, HR dive wrote a post called anxiety about AI drives Gen Z career pivot to blue collar work.

The article focused on a survey that had come out recently by Career Website Zetti.

It was a survey of 1,000 Gen Z workers, and it was very clear that they were in the midst of a re-evaluation of what a quote-unquote safe career looked like.

Almost three and four of those surveyed thought that AI would reduce entry-level corporate jobs over the coming five years.

Meanwhile, many of the respondents ranked skilled trades in labor, as well as people-focused professions like health care and education as among those jobs that were relatively more AI proof.

The survey also found a growing skepticism of college degrees.

In that Zeddy report 65% of respondents thought that college degrees wouldn't protect them from AI-related job loss.

That harkened back to an indeed report from April of last year that found about half of the respondents thought that new technology made their college education irrelevant.

Because of all this, there's the start of a reorientation towards blue collar or skilled trade jobs.

Another survey this time from resume builder back in May of 25 found that 42% of its Gen Z respondents were either currently working in or pursuing a blue collar or skilled trade job, even though more than a third of them had bachelor's degrees.

Which is not to say that there was universal excitement about this shift.

HR Dive summarized, while Gen Z said they were excited about certain elements of blue collar work such as higher pay, more job opportunities and greater flexibility, they cited physical labor demands, concerns about upward mobility, and lack of awareness about trades as challenges that remain.

And yet, in spite of that, this narrative continues to grow.

In September, Forbes published an op-ed called as AI sweeps the white collar world blue collar work sees a renaissance.

That essay had as its catalyst, a then-recent report from Jobber called Gen Z in the blue collar revolution.

If one thing is super clear from that report, it's that even when skilled trades are not their answer, AI proofing careers is very much at the top of minds for the younger generations.

63% of Gen Z parents said that AI was making it harder for young people to break into the workforce and 77% of Gen Z said it was important to them to choose a career that was difficult to automate.

Only 16% of Gen Z parents now believe a college degree guarantees long-term job security that is a vanishingly small number for one of the biggest expenses of people's lives.

Nearly 72% of parents said that they'd talk to their children about how automation might impact their careers.

And 56.7% of parents said that they believed that AI would significantly change the types of jobs available over the next 10 years.

Nearly a third as well, 29.6% said that they believed that blue collar or hands-on jobs were safer from AI than office jobs.

And nearly 40% said that they would actively encourage a vocational path if it meant AI resilience.

Here's the dramatic shift to me.

Only 16% of Gen Z parents now think a college degree protects tax kids from AI-related job disruption.

Meanwhile, 73% say they believe a trade entrepreneur has more long-term security than a tech employee at a major company.

And I think that idea of trade entrepreneurship is really important.

Increasingly, it's clear that the younger generations and their parents understand that entrepreneurship isn't just about risk, it's also about resilience.

62% of Gen Z parents said that trade jobs can offer entrepreneurial opportunities and 62.1% said that it would be proud if their child became a tradesperson.

Okay, so let's start to add this up.

We've got first the shifting sands that AI represents, changing people's perceptions of the durability and safety of white collar jobs, which is making people more favorably inclined towards blue collar and skilled trade jobs, which then people are also recognizing are vehicles for entrepreneurship and self-destiny.

And that gets us to the second part of this blue collar AI conversation, which is not just why AI is driving people to the trades, but how people in the trades can use AI to increase their outcomes.

Or as David put it in that first piece that we heard, how they can use it to increase their leverage.

Now at this stage, AI's penetration into blue collar work is still fairly nascent.

One survey in Finland, which is obviously a very different economic context, but it was recently taken found that only around a quarter of union members in blue collar occupations said that they had used AI at work.

That was even though 60% said that they had used AI outside of the workplace.

A third though said that they felt there was greater scope for using AI in their work.

So how might AI make it into trades professions?

I think there are a couple paths.

First of all, we are now living in an open-claw world.

And while one would be forgiven for rightly being skeptical that this very nascent hacker early adoption phase is likely to impact many people at all in white collar professions or blue collar professions, given the technological burden that comes along with setting up your Mac mini for your little agent.

This state of affairs is not going to last long.

OpenClaw is not an isolated phenomenon.

It is instead the waypoint in our transition to an agentic economy, already you can find so many companies that are racing to simplify implementation of OpenClaw for less technical folks.

That is going to radically hasten the productization of agents that can actually do useful things for people.

And while we are still figuring out the exact use cases that work for different contexts and settings and people and jobs and roles and types of companies, it's pretty clear to me, even from my own experiments, that this is not enough in burger.

And what's more, I think a lot of the general assistant type of use cases that many open-claw users are experimenting with right now might be exactly the type that are incredibly useful for trade entrepreneurs, email management, calendar management, on-the-go problem triage.

These are all things that this new generation of agents actually does quite well, and it's exactly the type of things that could be useful for folks who have a lot of real world physical constraints on their time.

But there's another dimension of this as well.

One of the other impacts of the AI era is that the cost of building software is coming down dramatically.

Now, that does not mean that I expect trade entrepreneurs on mass to build applications for themselves, although certainly some will.

Instead, what I think it means is that markets that would have previously been seen as too small for people who build software to be interested in.

Because they don't meet the criteria for venture backing, all of a sudden start to look really interesting.

Dedicated software for a niche trades category?

If you don't need millions of dollars from a venture capitalist to build it, all of a sudden looks like it could be a really interesting opportunity.

I would expect to see an absolute flourishing and renaissance in dedicated, highly focused applications that are designed to solve the specific problems of specific categories of trades workers, enabled by the reduced cost profile of building with AI.

And once again, because those companies are built by small entrepreneurial teams who don't have the constraints of the types of outcomes that a venture capitalist needs to see, that also changes the nature of the business model that they put into practice, which I think probably brings down the cost profile for those tradespeople and trades entrepreneurs.

Now none of this is to say that there aren't threats from AI for blue collar work as well.

We are at the very beginning of the era of embodied AI, and there are plenty of companies, big venture-backed companies, that are trying to build highly capable humanoid robots that can do things that blue-collar workers do now.

It would be polyannish to write off that risk entirely.

But I think whereas much of the disruption from software AI is here right now, we have a long way to go before we know exactly how the economics of embodied AI really work out.

For example, people tend to think that the reduced cost of a robot compared to a human is the only factor that matters, but I think human preference to have other humans helping them with the things that they need is going to be a dramatically higher barrier than people are anticipating.

Anyways, the point isn't that we should be blind about all of this, but that there is this really exciting new opportunity happening, and one that I think we don't talk about enough.

Anyway, let me know what you think.

I'm excited to have this conversation more.

For now, that's going to do it for the AI Daily Brief.

Appreciate you listening or watching, as always, and until next time, peace!","created_at":"2026-02-22T14:01:58.000000Z","updated_at":"2026-02-22T14:03:28.000000Z","requested_by":[2],"status":"completed","delay_time":33724,"worker_id":"n2d85damqk97p1","job_id":"95025fb1-1678-4986-bbff-ce66b255cc46-u2","execution_time":29592,"runpod_job_id":null,"error_message":null,"completed_at":null,"word_level_timestamps":null,"claimed_at":null,"embedding_claimed_at":null,"embedding_worker_id":null,"retry_count":0}