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

Starting point is 00:00:00 Today on the AI Daily Brief, why AI could matter more for plumbers than for programmers. 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, racks-based technologies, robots and pencils, blitzie, and super-intelligent. To get an ad-free version of the show, go to patreon.com.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. Ad-free is just $3 a month. to learn about sponsoring the show, send us a note at sponsors at AIDailydief.ai, and of course AIDailybrief.aI.com is where you can find out everything else about this

Starting point is 00:00:40 ecosystem of projects that we have as well. Now, 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

Starting point is 00:01:20 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, this was an op-ed in Fortune magazine by David Haycock. 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 7 million customers, and employs over 1,000 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.

Starting point is 00:01:59 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,

Starting point is 00:02:38 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, focus 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. 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 Filterby, a $260 million domestic manufacturing company that makes and ships

Starting point is 00:03:21 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 misreading 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. There'll be people running practical non-tech businesses. Consider what a small service operator looks like today.

Starting point is 00:04:10 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

Starting point is 00:04:46 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 firsthand at Filterby. 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.

Starting point is 00:05:25 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 instead 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?

Starting point is 00:05:56 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.

Starting point is 00:06:18 It will show up in how work actually gets done. 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,

Starting point is 00:06:47 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 one 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

Starting point is 00:07:26 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

Starting point is 00:08:09 places where the most realized disruption is happening is in fact in white-collar roles. 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

Starting point is 00:08:41 versus everyone just firing the programmers they have access to, but it will take time to see how that all shakes out. All right, friends, quick break to talk about a question I hear constantly. How do you actually move from AI experimentation to production without getting buried in infrastructure decisions? That's where Rackspace AI Launchpad comes in. It's a fully managed service designed to help enterprises build, test, and scale AI workloads through a guided phased approach.

Starting point is 00:09:09 With AI Launchpad, Rackspace manages the infrastructure GPU and core tooling, so teams can focus on validating use cases instead of building environments from scratch. You start with a proof of concept, move into a real pilot, and then scale into production on managed enterprise-grade GPU infrastructure. Whether you're testing inference at the edge, fine-tuning foundation models, or standing up a production pipeline, the goal is the same. Faster progress with less operational friction.

Starting point is 00:09:33 If you're ready to move beyond demos and actually put AI to work, take a look at Rackspace AI launch pad and see how a managed path to production can accelerate results. Visit raxpace.com slash AI Launchpad to learn more. Most companies don't struggle with ideas. They struggle with turning them into real AI systems that deliver value. Robots and Pencils is a company built to close that gap. They design and deliver intelligent cloud-native systems powered by generative and agentic AI with focus, speed, and clear outcomes.

Starting point is 00:10:02 Robots and pencils works in small, high-impact pods. Engineers, strategists, designers, and applied AI specialists working together to move from idea to production without unnecessary friction. Powered by RoboWorks, their agentic acceleration platform, teams deliver meaningful results including initial launches in as little as 45 days depending on scope. If your organization is ready to move faster, reduce complexity, and turn AI ambition into real results, robots and pencils is built for that moment.

Starting point is 00:10:27 Start the conversation at robots and pencils.com slash AI Daily Brief. That's robots and pencils.com slash AI Daily Brief. Robots and pencils. Impact at velocity. Weekends are for vibe code. It has never been easier to bring a passion project to life, so go ahead and fire up your favorite vibe coding tool. But Monday is coming, and before you know it, you'll be staring down a maze of microservices, a legacy cobal system from the 1970s, and an engineering roadmap that will exist well past

Starting point is 00:10:52 your retirement party. That's why you need Blitzy, the first autonomous software development platform designed for enterprise-scale codebases. Deploy the beginning of every sprint and tackle your roadmap 500% faster. Blitzies agents suggest your entire codebase, plan the work, and deliver over 80% autonomously, validated end-to-end tested premium quality code at the speed of compute. Months of engineering compressed into days. Vibe code your passion projects on the weekend.

Starting point is 00:11:16 Bring Blitsey to work on Monday. See why Fortune 500s trust Blitsey for the code that matters at blitzie.com. That's BLYTZY.com. Today's episode is brought to you by Super Intelligence. Super Intelligence is a platform that very simply put is all about helping your company figure out how to use AI better. We deploy voice agents to interview people across your company. Combine that with proprietary intelligence. about what's working for other companies and give you a set of recommendations around use cases,

Starting point is 00:11:42 change management initiatives that add up to an AI roadmap that can help you get value out of AI for your company. But now we want to empower the folks inside your team who are responsible for that transformation with an even more direct platform. Our forthcoming AI strategy compass tool is ready to start to be tested. This is a power tool for anyone who is responsible for AI adoption or AI transformation inside their companies. It's going to allow you to do a lot of the things that we do at super intelligent, but in a much more automated, self-managed way and with a totally different cost structure. If you're interested in checking it out, go to AIDailybrief.ai slash compass, fill out the form and we will be in touch soon.

Starting point is 00:12:21 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 so. 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 resure all this stuff if we don't have the people

Starting point is 00:13:00 to work there? These comments came as Farley actually hosted a summit in Detroit called Accelerate the Essential Economy. That is all about expanding the pipeline of these skilled essential workers. In a blog post, Farley estimated that the U.S. 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,

Starting point is 00:13:32 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 drumbeat of people calling for more blue-collar workers just continues to get louder and louder. Recently at the World Economic Forum, Nvidia 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 and AI 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 interest. infrastructure buildout. Now, what's interesting is that Gen Z kind of seems to be taking up the call.

Starting point is 00:14:17 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 Zee Career Pivot to Blue Collar Work. The article focused on a survey that had come out recently by Career website ZETI. It was a survey of a thousand Gen Z workers, and it was very clear that they were in the midst of a reevaluation 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

Starting point is 00:14:55 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 ZETI 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

Starting point is 00:15:34 than a third of them had bachelor's degrees. Which is not to say that there was usually. universal excitement about this shift. H.R. Dives 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 Caesar 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,

Starting point is 00:16:14 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,

Starting point is 00:16:57 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 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 generation, and their parents understand that entrepreneurship isn't just about risk, it's also about resilience.

Starting point is 00:17:40 62% of Gen Z parents said that trade jobs can offer entrepreneurial opportunities, and 62.1% said that they 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

Starting point is 00:18:18 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.

Starting point is 00:18:53 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

Starting point is 00:19:36 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 a nothingberger. 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

Starting point is 00:20:17 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 en masse 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,

Starting point is 00:20:59 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 tradesworkers, 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.

Starting point is 00:21:43 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 polyanish 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.

Starting point is 00:22:24 Anyways, the point isn't that we should be blithe 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.

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

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.