In 1996, a physics professor named Alan Sokal submitted a paper to Social Text, an academic journal of cultural studies. The paper, titled “Transgressing the Boundaries: Towards a Transformative Hermeneutics of Quantum Gravity,” proposed that quantum gravity is a social and linguistic construct. The journal published it.

Three weeks later, Sokal revealed that the paper was entirely made up. He’d written the paper to test whether an academic journal would publish anything that sounded good and confirmed its editors’ ideological leanings. It did. The “Sokol affair,” as it came to be known, kicked off a debate about intellectual rigor in academia that lasted for years.

A Planet Money episode from February 2026 explored what’s known as the “replication crisis” in social science: the pattern where published studies can’t be reproduced when other researchers try to verify them. Economist Abel Brodeur, a professor at the University of Ottawa, has been organizing events called “Replication Games,” where teams of social scientists audit published papers by re-running the original code and data.

What they’re finding isn’t always fraud. Sometimes it’s honest errors in coding or data handling. But sometimes it’s something more uncomfortable: researchers who massaged their datasets until they got a statistically significant result. Brodeur admitted to doing exactly this himself as a master’s student. He ran analysis after analysis on data about smoking bans until he finally got a result worth publishing. He later decided to publish the more accurate (and less exciting) null result instead — and went on to build the Institute for Replication to address the problem at scale.

Today, the packaging has gotten a lot more sophisticated, and answering the question, “What is real?” is even more difficult to answer.

The problem is older than AI

There’s a tendency to talk about AI-generated misinformation as though we were living in some golden age of accuracy before large language models arrived. We weren’t.

This problem is as old as research. Sokal proved that we’re willing to believe what we want to believe, even from seemingly credible sources. Brodeur shows us that research is sometimes manipulated. That’s to say nothing of the endless spree of disinformation on The Internet.

Now consider what happens when AI enters the process, which is already our reality. In December 2025, Sam Rodriques, CEO of FutureHouse and Edison Scientific, claimed to accomplish six months of doctoral-level research in a 12-hour run with his AI agent, Kosmos. Rodriques walked through how the tool identified a genetic mechanism for type 2 diabetes — connecting a variant, a binding protein, and a gene involved in pancreatic function — by analyzing massive amounts of raw data that would take a human researcher much longer to sort through.

Stories like what Rodriques shared are genuinely impressive. And it’s easy to imagine how tools like this could accelerate scientific discovery in ways that matter (drug development, disease research, climate modeling, etc).

But the same qualities that make AI useful for research also make it dangerous. AI models hallucinate and present hallucinations with the same confidence as factual information.

A Stanford RegLab/HAI study found that general-purpose AI models hallucinate between 69% and 88% of the time on specific legal queries, using state-of-the-art models. The researchers noted that these models “often lack self-awareness about their errors and tend to reinforce incorrect legal assumptions and beliefs.”

The lack of self-awareness is the alarming part. A human researcher who massages data is making a conscious choice (even if it’s a rationalized one). A journalist who spins a story knows the angle they’re taking. AI has no clue that it’s wrong. It presents fabricated information with the exact same tone it uses when presenting accurate information.

The Sokal hoax was discovered because Sokal himself revealed it. Academic replication errors can take years or decades to surface. AI can generate plausible-sounding misinformation instantly, at scale, and no one is around to reveal the errors. The same dynamics that made any research vulnerable — confirmation bias, incentive structures, lack of verification — now operate at the speed of typing into a chatbot. And these systems that claim to “democratize access” also make it easy for misinformation to propagate (like the guy who claimed that he cured his dog’s cancer with ChatGPT).

We’re right to be skeptical

None of this means AI is useless. But it does mean the question of “what is real?” now applies to virtually every piece of information we encounter — including (maybe especially) the information that sounds the most authoritative.

Cory Doctorow is a science fiction writer and tech journalist, and is well-known for coining the phrase “the enshittifcation of the internet.” He put it bluntly on Offline with Jon Favreau:

“The big problem with AI is that it’s just not real. No one’s ever lost as much money as they have on AI. AI is the losingest proposition in business in the history of the world.”

AI companies are selling a story — that AI can replace human workers — because that story is what investors want to hear. Whether or not AI can actually do the work is almost beside the point. The narrative has become as important as the product.

Companies are making claims about AI that are extraordinarily difficult to verify. When a company says “AI replaced 10 people,” what does that mean, exactly? What’s the output comparison? What’s the error rate? What’s the timeline? In most cases, we have no idea, because the data either doesn’t exist or isn’t shared. A Harvard Business Review analysis from early 2026 laid it out clearly: companies are laying off workers based on AI’s potential, not its actual performance.

The question of “what is real?” has always required effort to answer. Academic papers require peer review (but it might be lacking). News stories require fact-checking (but may still have bias). Corporate claims require scrutiny (and rarely get it). What’s changed isn’t the need for verification. It’s that the effort required has increased exponentially, because AI can produce information with such speed and at scale. The tools for manufacturing a wholly convincing unreality have gotten exponentially easier to use.

When the people making the tools say one thing, and the people using the tools experience something else entirely, it fuels this credibility problem with AI.

I think far too few people (and even fewer corporations) share real, tangible, honest examples of how AI has made their work better. Even in examples of scientific research, we’re right to ask, “Can those results be trusted?”

Personally, I use AI a lot. I try to share specific examples of my use cases, because I realize that I’m fighting the “AI can do everything! It’s amazing!” narrative and a proliferation of slop. But I’m also one person, and I don’t claim anything at the scale of “AI has changed my life and made my work 10,000% better.”

The best defense is the same one it’s always been: question the source, verify what you can, and be especially skeptical of the claims from people who have an incentive to demonstrate a specific result. That’s the lesson from Sokal, 30 years later.

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I saw a thread online recently about a pattern that probably sounds familiar: the employees who raise concerns, suggest improvements, or push back on bad decisions are frequently rebranded by their managers as “having a bad attitude.” The label sticks whether or not the feedback had merit.

It’s worth pausing on who these employees usually are. The people who complain are often the ones who still care. They want to be successful at their jobs. They want the workplace to be better, too. Complaints — real ones, not venting — are a form of participation. They’re evidence that someone still believes the company is capable of improving.

So what does it mean when those same employees stop complaining?

In the U.S., employee engagement has dropped to a 10-year low of 31%, with 17% of workers actively disengaged. Globally, 1 in 5 employees now report feeling trapped in ongoing job dissatisfaction. Companies tend to treat the absence of pushback as a sign that things are working. But silence is often the last sound before employees walk out the door.

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I worked at a software company for 15 years. For a long time, I advocated for fixing anything that I perceived as broken: processes, messaging, shortcomings in the product itself. As I moved up the ranks and eventually was promoted to an executive role, I hit the ceiling of what could be fixed. Management simply wasn’t willing to address some pervasive underlying issues.

I stopped complaining because it was useless. I stopped caring. And I quit.

AI is the newest thing employees are being told to stop complaining about

Disengagement is accelerating right now because companies are pushing AI adoption on employees who have real, valid, and specific concerns. Yet CEOs are dismissing those concerns as resistance to change.

On top of how AI is used at work, there’s a whole additional layer of concern about AI as an industry. A Pew survey found that 73% of AI experts believe AI will have a positive impact on how people do their jobs. Only 23% of the American public agrees. That’s a 50-point gap between the people building AI and the people living with it.

The tech journalist Nilay Patel captured the broader frustration in a recent episode of The Vergecast:

“The AI industry is staring at these polls that say everyone hates them. And it’s because they are asking for so much. They’re asking for a lot of power. They’re asking for a lot of land to build data centers. They are asking for every stick of RAM that has ever existed in the history of the world. They’re asking to scan every book without payment.

Whatever it is that they’re asking for, they’re doing it without permission and they’re asking for a lot and they have not given back a product that makes people feel the way that the internet made them feel or the smartphone made them feel or YouTube made them feel. It just doesn’t exist yet.”

To be clear: AI is a useful tool. I use it every day. The critique here isn’t about AI itself. It’s about what happens when companies deploy it in a way that ignores legitimate concerns and how the vast majority of people feel about the technology.

Most executives haven’t grasped that there are three layers of mistrust stacking on top of each other. Employees don’t trust AI as a technology, for reasons that are well-documented in public surveys. Separately, employees don’t trust the way their employer is rolling it out — often with mandates, with performance reviews tied to “AI fluency.” Thirdly, the social contract has long been broken with sweeping layoffs, so employees don’t trust that their employer won’t replace them with AI at the first chance they get.

You could dismiss the workplace mistrust as resistance to change. But when the same people are also skeptical of AI in their personal lives, “resistance to change” isn’t a satisfying explanation. What’s being resisted is something more specific: being told to adopt, quickly and without question, a technology that the general public is nervous about and that has not yet proven itself to be “life-changing” in the way that AI leaders have promised.

What happens after silence

Most of the writing about employee disengagement focuses on what companies lose: productivity, revenue, and institutional knowledge. That framing is aimed at executives and misses the other side of the equation entirely.

When companies mislabel that skepticism as a bad attitude, employees eventually stop voicing it. It probably won’t lead to a mass exit, because, at present, employees think, “Where else can I go? Will the next company be the same way?” Instead, they start to wonder, “What else can I do with my career? How can I regain control?”

When you stop trying to fix a system that doesn’t want to be fixed, you start seeing the potential exit paths more clearly. The mental energy you were spending on advocacy becomes available for something else — a job search, a side project, or a plan to leave entirely.

If you’ve stopped speaking up because no one was listening, that’s information worth taking seriously. Not every company deserves your energy, and the decision to stop pushing isn’t a failure on your part. Sometimes it’s an accurate read of the situation and a deliberate move to protect your mental health.

In the current labor market, the realization that no one is going to listen is often less specific to their current employer. It’s not, “This company won’t listen.” It’s “No company will listen” (at least, not in a way that matters). There’s no “grass is greener” outlook.

Final thoughts

If you’ve given up on the idea that they can change, you have to think about your next steps. Is it laying low and doing the best you can to avoid a layoff? Or is it something else entirely?

A lot of entrepreneurs and solopreneurs can trace their exit from corporate life back to a moment like this. Not a dramatic blow-up. Not a single bad boss. Just the realization that nobody was going to listen, no matter how well they made the case.

If you’re reading this and recognizing yourself in the silence, pay attention to what it’s telling you. Silence at work is rarely the end of the story. It’s usually the start of a transition.

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In 2015, Paul Ford published a 38,000-word essay in Bloomberg called What Is Code? It’s an explainer for non-technical people who may find themselves in technical meetings with software developers and engineers. Recently, on an episode of The Vergecast, Ford says, “I wrote What Is Code? because I really did believe that this was a good way into the middle class, and it had been for me.”

In the same episode, he acknowledges, “There’s somebody out there… who is counting on their tech job. That somebody like me told them 15 years ago was the safest possible bet. And they went and got a certificate in AWS management. And now people are telling them, ‘Why would I ever do that? I’ll just deploy by using Claude.’” These jobs are existentially at risk.

For a generation, the career advice given to displaced workers, uncertain graduates, and anyone looking for a stable path was essentially the same: find a way to get into tech. Learn to code. Become a product manager. Work for the sales or marketing department at a tech company. Join the industry that is the disruption, not the one getting disrupted.

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I’ve worked in the tech industry (and now, tech-adjacent) since 2006. It was well-paying and, until late 2021, felt safe. I left my tech job voluntarily and went into content marketing for tech companies. 18 months later, I lost my job. A lot of factors played into that turn of events, but one was that the tech company was being decimated. Companies no longer had the budgets for marketing, impacting the marketing agency I worked for.

Over the past few years, I’ve watched the ground shift beneath the feet of so many people I know. That assumption that tech is “safe” has crumbled into dust. And the people who believed it most are the ones feeling it hardest.

The decade that didn’t deliver what was promised

There’s a cohort of workers — mostly elder millennials — who arrived at what was supposed to be the “payoff phase” of their careers at the exact moment everything started to change. Mid-to-senior titles. Accumulated equity at startups. Stable (even growing!) compensation. The decade was supposed to deliver on the promise that patience and hard work in tech would lead to security.

But then the pandemic hit. Tech layoffs hit. Generative AI hit. Just as this cohort reached the positions they’d been climbing toward, the industry started dismantling itself.

As of early April 2026, tech layoffs this year alone have impacted over 91,000 workers. In 2025, that number was approximately 246,000 across 783 companies. While some layoffs have been from startups struggling to survive, others are from companies that aren’t strapped for money. Amazon reported record revenue of $716.9 billion in 2025 while cutting 30,000 corporate roles. Block — the fintech company behind Square and Cash App — cut 40% of its workforce, roughly 4,000 people, explicitly because of AI. CEO Jack Dorsey said it wasn’t driven by financial difficulty. After the announcement, the company’s stock went up.

What makes the current wave of layoffs structurally different from what came before is what’s driving it. The first wave of tech layoffs (2022–2024) was a post-pandemic correction. Companies had to dial back the hiring sprees they went on during COVID. Painful, yes, but cyclical. The thing that’s happening now is something else entirely. Companies are explicitly stating that they are replacing human roles with AI systems. In a Resume.org survey, 44% of hiring managers anticipate AI will be a top driver of layoffs in 2026.

And here’s what I keep thinking about: the executives making these workforce decisions are acting on a capability that, by most reports, hasn’t fully materialized. Microsoft’s AI CEO, Mustafa Suleyman, predicted that most white-collar tasks — lawyers, accountants, project managers, marketers — will be “fully automated” within 12 to 18 months. Meanwhile, a randomized controlled trial by METR (published July 2025) found that experienced developers using AI tools took 19% longer on tasks than those working without them, even though they were faster.

The gap between what executives promise (or what they believe will happen) and what workers actually experience is enormous. Employees are bearing the cost of a bet they didn’t place, when we were promised something different.

The decision to pivot

Not everyone who’s leaving tech is being pushed out. Some are choosing to go.

There’s a steadily growing sentiment among the cohort that was supposed to be entering the highlight of their careers. It’s less about the dramatic exits of The Great Resignation and more about a widening gap between what tech promised and what it actually delivers at this stage of life. Kids entering adolescence. Parents aging. Bodies changing. Energy levels changing. Perspectives changing. People already juggling more “life outside of work” are rightfully questioning the constant grinding of their careers.

And the incentive to retool themselves again — this time at the breakneck speed that AI requires inside a corporate structure — just isn’t there. Think of it this way: why apply yourself to learning AI, when all of the benefit goes to the company, not the individual? The company gets more output. The individual gets more work.

Many are choosing something else, such as consulting, starting a business, or even learning trades. They’re turning long-held hobbies or passions into second careers. It’s intentional.

Part of what’s driving this shift is that people want more from work itself. More meaningful work instead of more money. More flexibility and control instead of a prestigious title at a company that might lay them off next quarter. RTO mandates, constant restructuring, AI-related pressures at every performance review… the culture of tech has changed. For some workers, the industry that used to feel generous and exciting doesn’t feel that way anymore.

And then there are the golden handcuffs. The math used to be simple: the paychecks from working for a tech company are often big enough that leaving feels irresponsible. But the equation changes when those paychecks come with layoff anxiety, RTO mandates, and the persistent feeling of dread, thinking that you’re one AI deployment away from being replaced. At some point, the handcuffs aren’t golden anymore… they’re just handcuffs.

I left my work at a tech company years before AI arrived, and before the mass layoffs hit. But the desire for “something else” was my motivator. I felt the thrill of building something — a product I truly believed in — early in my career. As I reached my 40s, with older kids and a post-pandemic lack of tolerance for bullshit, my personal calculus changed.

Was tech ever the destination?

Here’s what’s worth knowing if you’re in that space of “what do I do next?” right now: career pivoters are overwhelmingly happy on the other side. I’ve talked to many, many people over the years. And sure, it’s a small sample, but I feel confident that it’s representative of how people feel overall. They’re relieved, even if the initial “getting through change” phase is hard.

I’ve written before about the portfolio career replacing the career ladder, and about the different types of career pivots people make. What’s happening in tech right now is a collision of several of those pivot types at once: forced pivots from layoffs, anticipatory pivots from people who see the writing on the wall, and boredom pivots from workers who’ve mentally checked out of an industry that no longer resembles the one they signed up for.

Non-linear paths are not consolation prizes. They’re increasingly what sustainable careers actually look like — especially for people who’ve already navigated one or two major industry shifts. They can build on what they’ve learned, instead of clinging to something that’s disappearing.

We don’t fully know how this plays out. But the assumption that tech was a career safe harbor? That’s gone. So if you’re in tech and uneasy, considering leaving, or already have one foot out the door, keep this in mind: your experience is more portable than it feels right now. Systems thinking, project management, data interpretation, navigating ambiguity…. those skills don’t evaporate when you leave the industry that taught them to you.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

A recent Entrepreneur headline proclaimed: “Dell Shrunk Its Workforce By 10% for the Third Year in a Row — Without Layoffs.”

Dell has about 97,000 employees. That’s according to its latest federal filing, published this week. In February 2023, it had 133,000. That’s a reduction of nearly 30% of its workforce in three years.

Except... Dell did lay off 12,500 employees in August 2024. That was less than two years ago. Someone on the editorial team at Entrepreneur failed at the most basic task of “accurate information.” (The article itself notes the layoff, which is a direct contradiction to the headline.)

On top of the layoff, Dell has employed other methods of reducing its workforce, such as hiring freezes, “employee reorganizations,” and a five-day return-to-office mandate. The end result is the same: reducing the size of the workforce. They’re layoffs without negative publicity.

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I wrote about Dell in March 2024, when the company announced that remote employees would be ineligible for promotion. At the time, Dell’s own internal data showed the policy disproportionately impacted women. I said then that it looked like Dell was trying to force employees to quit rather than go through another expensive round of layoffs. When employees quit due to a change in working conditions, the company can shrug and say, “Not our fault that they quit.” Two years later, the numbers confirm exactly what I predicted would happen.

What Dell and other companies are doing is part of a broader shift toward what Glassdoor calls “forever layoffs“: continuous, small-scale workforce reductions that fly under the radar. But they create lasting damage to the people left behind.

The playbook for disappearing workers

In these “forever layoff” scenarios, the work doesn’t disappear. It gets redistributed to the people left behind.

The high-profile layoffs grab attention: Block cut 40% of its workforce in February 2026, with Jack Dorsey explicitly pointing to AI. Meta is reportedly planning to cut 20% of its staff. Atlassian cut 10%. But plenty of companies are taking the same approach as Dell and handling a reduction in force (RIF) much more quietly, to avoid attention.

But the cumulative effect is the same. And the impact on the people who stay is significant. Glassdoor’s research from September 2025 found that after a layoff, employee sentiment among remaining workers takes more than two years to recover. Repeated layoffs have double the impact on sentiment, with the biggest drops among key talent, managers, and new hires. Employee mentions of “layoffs” and “job insecurity” in Glassdoor reviews are now higher than they were in March 2020, at the onset of the pandemic.

The near-constant layoffs-that-aren’t-layoffs are demoralizing in a very specific way. Workers never know when the next “reorg” will eliminate a few people in their department. They absorb more work without more pay. They watch colleagues deactivated in Slack in real-time. Rolling layoffs breed cultures of anxiety, insecurity, and resentment.

“Just use AI” isn’t a workforce strategy

The CEO mantra of “just use AI” as a solution to a smaller workforce doesn’t sit well with the people actually doing the work. AI doesn’t replace a whole human, and certainly makes the remaining workers further wonder if their jobs will be next on the chopping block.

Zuckerberg said in January that he was seeing “projects that used to require big teams now be accomplished by a single very talented person.” That framing — one talented person replacing an entire team — is becoming the justification for cutting headcount across the industry. Though Meta’s plans to cut headcount are in part to offset the $135 billion in infrastructure costs of AI (which is wild, considering how bad Meta is at AI compared to the frontier models). You’d think Meta could spare some of that investment for its human employees.

But how much of Zuckerberg’s claims of employees’ use of AI are actually happening on the ground? Technology reporter Kevin Roose wondered this on the Hard Fork podcast: “The data that we have is largely self-reports. And I think some firms have exaggerated how much they are doing with AI because they want to appear to be cutting edge and futuristic, and look how transformed we are.”

Even if it is the case that humans are now overseeing multiple AI agents, as Zuckerberg suggests, researchers have found that “AI brain fry“ is on the rise. This is defined as a type of cognitive strain and mental fatigue related to the excessive use of, interaction with, or oversight of AI — beyond one’s cognitive abilities. “Doing the work” alongside human colleagues is a far different experience than overseeing a bunch of AI agents.

At the other end of the spectrum, with employees less comfortable with AI experimentation on their own experience a fundamental training gap. Companies are telling workers to “just use AI,” but they’re not investing in teaching them how. If companies aren’t even providing the basics of AI training, expecting workers to use it as a substitute for human colleagues is setting them up for failure. Especially as many employees now report that AI usage is a part of their performance reviews.

It’s no wonder that employees are resentful.

Why the narrative isn’t fooling anyone

Dell, Block, Meta, and others like to claim that AI is so capable that companies genuinely need fewer people. In reality, these companies have decided that workers are the most expendable line item — and are using the current AI hype cycle as cover. When Jack Dorsey announced Block’s layoffs, its stock price jumped more than 20%. When reports of Meta’s potential layoffs surfaced, Meta’s stock climbed too. The market is rewarding companies for cutting people.

So they’re optimizing for short-term gains and framing it as “strategy.” Nobody seems to be asking what happens when the remaining workers burn out, suffer from “AI brain fry,” or when institutional knowledge walks out the door.

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A few weeks ago, I vibe-coded a new website for myself. If you’re not familiar with vibe coding, it’s using natural language (“Hey Claude, we’re going to work on a new homepage for me”) to code something. An article in Microsoft Source describes it this way:

Coding has long been limited to the realm of software engineers who studied it in school. But now there are so-called no-code, low-code and pro-code AI tools. That’s broadening who can build apps, helping everyone from non-technical business professionals to experienced developers solve problems, save time and boost creativity.

It’s addicting… after building my initial website, I spun up several more. I’ve spent hours fiddling with Claude CoWork. It’s exciting and genuinely a big deal for people who like to “tinker.” You can now build the tool you’ve always wanted — either because no company was going to make it (because the use case is too specific to you), or because you don’t want to pay a monthly subscription for something you’ll only partially use.

All of this has a real impact on people’s lives, both at work and personally. But the ability to build doesn’t mean you should build everything. And the line between building something useful and building for building’s sake is thinner than most of us realize.

The new math of building

Companies have always wrestled with the “build vs. buy” decision. If they wanted a tool to do something, they could either build it themselves (which takes time, money, and resources) or buy it (which lacks full control and customization). Now the calculation is murkier, and it can rely on individual decisions instead of a big corporate buy-in. You want something? You can build it yourself. The question is whether you should.

What used to require hiring a designer, a developer, or a consultant can now be done in a few hours with an AI tool. That’s a real shift, and for many people, it’s the first time they’ve been able to bring an idea to life without depending on someone else.

Regular people are building personal websites, scheduling tools, custom dashboards, automations that connect their apps — things that weren’t possible a year ago. The potential is enormous.

But the potential also has a way of expanding to fill all available time, rather than saving time.

Katie Parrott wrote a piece called “AI Was Supposed to Free My Time. It Consumed It.” She describes staying up until 1 a.m., building and rebuilding with her AI assistant. Her piece captures something important: a compulsive quality of AI-assisted building that many people find once they get started. It doesn’t feel like work. It feels like momentum… and that’s what makes it hard to stop. (You can read Katie’s guest essay about productivity for this publication here.)

There’s a version of this playing out on a much larger scale. On a recent episode of The Verge’s Decoder podcast, Hasbro CEO Chris Cocks described how AI-assisted design has transformed the company’s product development. Where Hasbro’s teams used to take one or two toy concepts to the full prototype phase, they can now take 10 or 20. More ideas, faster, at the same cost.

That sounds like pure upside. But it’s also a perfect illustration of Parkinson’s law, a concept based on a satirical essay that contained the line, “Work expands so as to fill the time available for its completion.” When AI makes it possible to generate 20 prototypes instead of two, you don’t stop at two and go home early. You generate all 20. And then you review all 20. And then you iterate on the five most promising ones. The capacity to do more becomes the expectation to do more.

This pattern shows up in survey data, too. The Upwork Research Institute surveyed 2,500 workers in 2024, including executives, employees, and freelancers. 77% of employees said AI tools had actually added to their workload. Workers reported spending more time reviewing AI-generated output, more time learning the tools, and being asked to do more work as a direct result of the technology. More recently, Upwork’s 2025 follow-up study found that of the workers reporting the highest productivity gains from AI, 88% of them experienced burnout.

This cycle of constant building with AI only benefits workers if they were previously overworked, and AI actually reduces the load. If the “newfound time” just gets filled with more stuff (more prototypes, more iterations, more output), then the gains flow to the employer. The worker doesn’t get any time back.

Building with intention

This isn’t an argument against AI tools. I’m a fan, trust me. But it’s an observation that the low friction to get started doesn’t mean you should build everything. It’s no longer a “build vs. buy” question, but instead a “build vs. ‘what do I gain from building?’” question.

The temptation to build everything you can build is real. And the people who benefit most from these tools are the ones who build the right things: the things that actually improve their lives rather than just consuming their attention.

I could stay up allll night (like my friend Katie) and build new things in CoWork or Claude Code. Instead, I’ve got to decide how to meaningfully apply my time and attention. If I were working for an employer, it would be the same.

Before you sit down to build something with AI (whether it’s a custom app, an automation, or a new workflow), a few questions are worth asking:

What specific problem does this solve? If you can’t name a real use case — something that’s actually costing you time, money, or frustration on a regular basis — it might be a distraction posing as a productivity gain.

What’s the real cost? Not in dollars, but in hours. How much time will you spend getting this up and running versus how much time it will actually save you? A tool that takes 10 hours to build and saves you 20 minutes a week will take a while to “pay for itself” (though that certainly compounds if you save 20 minutes a week forever).

When will I stop? Deciding on an end result before you start is fundamentally different from trying to stop once you’re in the flow. (The flow is a trap!)

What will I do with the time I get back? This is the question that keeps the whole building process in check. If AI takes something off your plate, the benefit only exists if you’re intentional about what fills that space. Otherwise, you’ve just replaced one type of busy with another.

Honestly, I’m haven’t reached the point where building gives me more time… yet. I’m too deep into changing processes. Some are things I’ve had in place for years and are forcing me to fundamentally change how I do work. Will it pay off, eventually? That’s the bet I’m making: that this upfront work will be worth something.

Want to build a life-first business? These reflections will help you determine your priorities.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

Ever feel like the amount of work you have to do is running you into the ground? Most of us — whether working for an employer or working for ourselves — don’t have the luxury of handing off tasks to a team. Everything lands on your plate, and there’s never enough time.

AI won’t run your life for you (despite what some of the big AI companies would have you believe). But it can give you back hours every week. Some tools are AI-first, meaning their primary job is to perform an AI-driven task. You can also look at adding AI features inside tools you’re already using.

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These days, I rely heavily on AI. I can get more done in less time, without sacrificing quality in any of my work.

Here are a few AI tools that can make a huge difference in your work.

Meeting notetakers

An AI notetaker was the first AI-first tool I added to my business. My notetaker auto-joins my calls, records the conversation, transcribes everything, and sends me a recap with action items. Instead of scrambling to remember what a client said three months ago, I have a searchable archive of every meeting.

This solves a real problem: you can be fully present during the conversation rather than taking notes by hand. You also don’t risk missing something important, which can happen with manual note-taking.

Tools: Otter, Fireflies* [affiliate link], Fathom

Knowledge systems

Over time, we accumulate a mountain of valuable material: proposals, client emails, blog drafts, research notes, and random thoughts. Most of it gets buried in folders (or notebooks), which makes it hard to track through your thinking or find related ideas.

A personal knowledge system changes that. It creates a searchable “second brain” – like your own Wikipedia. Add AI into the mix, and you can “chat” with your own content instead of digging through your notes and files. Think of AI as a personal research assistant who has read everything you’ve ever written.

Tools: Google Notebook LM, Tana, Notion AI* [affiliate link], Reflect

Standard operating procedures

Even if you work alone now, you might eventually bring on help (like a virtual assistant, a subcontractor, or a specialist for a specific project). When that happens, you’ll need documented processes. The problem is that writing step-by-step instructions for everything you do is tedious. Most people never get around to it.

AI tools solve this by recording your screen as you complete a task and automatically generating written documentation. You walk through a process once, and the tool creates a standard operating procedure (SOP), complete with screenshots and written instructions — without any extra effort on our part.

SOP tools are uncannily good. I usually only need to make small tweaks to the written version, and sometimes don’t need to make any edits. I store them on my Google Drive so I can easily share them if needed.

Tools: Loom AI, Scribe* [affiliate link], Tango

A business coach

AI chatbots can serve as an on-demand sounding board. They won’t replace your judgment, since they can’t understand the nuance of the real world and human relationships. But they’re useful for thinking through options, drafting difficult emails, or walking you through the different angles of an idea you might have.

In Claude, I’ve created a “Business Coach” project. I’ve uploaded a lot of files so Claude has context, including information about who I am, the work that I do, my brand, and the potential clients I’m targeting. When I’m trying to think through something, Claude asks me questions. By responding, I clarify my own thinking.

You can also do this if you’re working for an employer by providing context about your role, team, or projects. Or your “business coach” might help you think through the next phase of your career, if you’re looking to make a change.

The key is prompting well. The more context you give about your situation, and any constraints (like your time or finances), the more useful the output.

Tools: ChatGPT, Claude, Gemini

AI features embedded in existing tools

Every company has been rushing to add AI features to its products. Some are good. Some are included with your existing subscription, while others treat AI as an add-on.

For example, I rely on Airtable* [affiliate link] to run the “back-end” portion of my business. AI-powered “field agents” have been able to accomplish a lot of tasks I used to do manually.

A few other ideas:

• AI-powered transaction matching in accounting software like QuickBooks or Kick can categorize your expenses and spot anomalies

• AI scheduling assistants in tools like Motion or Reclaim* [affiliate link] can help you plan your day and protect your calendar from too many meetings

• AI email features in apps like Superhuman or Spark can draft replies or prioritize your inbox

The tools you or your employer already pay for are getting better. If AI has been added since you originally signed up, the features are worth exploring.

Start with one new tool

AI fluency is becoming a baseline skill, like knowing how to use a spreadsheet. And it’s becoming ubiquitous: apps will keep adding AI features to make work easier and faster.

But you don’t need to master everything at once. Pick the tool that solves an obvious problem or can complete a task that drains a lot of time from our day. Figure out how to get the most out of it before adding the next thing.

Want to build a life-first business? These reflections will help you determine your priorities.

* Affiliate link: If you sign up, I may earn a small commission, at no additional cost to you.

An executive says out loud what many executives believe privately: “I’m successful because I put work above everything else in my life.” The room — full of C-suite leaders — nods along.

A Wall Street Journal opinion piece by a young entrepreneur took it even further, proclaiming that “Work-life balance will keep you mediocre.” He wrote, “In a winner-takes-all economy, extreme efficiency during your peak physical and mental years becomes a baseline for building wealth that lasts a lifetime.” Sacrificing time with family and personal relationships in college was, by his definition, necessary for success.

These aren’t fringe opinions. They’re the standard playbook of most people in corporate leadership. Ambition should hurt. The hardest worker wins.

This belief system treats sacrifice as proof of commitment — that the only way to earn your success is to give up everything else in pursuit of it. But what if it’s not a requirement for success? What if it’s just a story we’ve been told so many times that it feels like a fact?

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The cost of the sacrifice narrative

I remember nights early in my career, furiously typing away at the keyboard late into the night. I had to be the best. I had to prove how hard I was willing to work. It was effective, because I received promotion after promotion in my corporate life. Work was everything — until I had kids. And thank goodness I did, because kids fundamentally changed my perspective about what was important.

You can’t have it all, as the saying goes. You’ve got to make choices about how you spend your time. But in addition to damaging relationships, the “sacrifice everything” model has measurable health costs. A study co-authored by researchers at Wharton and UC Berkeley examined the long-term effects of stress on CEOs’ health. The findings were stark: CEO lifespans decreased by 1.5 years after an industry-wide downturn. When insulated from intense market pressure, their lifespans increased by two years.

While the study focused on CEOs, the implications extend to other workers. The same pressures — long hours, high-stakes decisions, chronic stress — are present at every level of management. Middle managers, in fact, report the highest rates of burnout of any group, with 71% saying they feel burned out. The people on the path to becoming those corner-office leaders are already paying the price.

There’s a well-known adage that people don’t lie on their deathbeds thinking, “I wish I had worked more.” They wish they’d spent more time with the people they care about and doing the things they love. And, according to the research, intense overwork doesn’t just diminish the quality of life. It actually shortens its length.

Thankfully, the next generation is already opting out. There’s a term for what’s happening: “conscious unbossing.” According to DDI’s Global Leadership Forecast 2025, Gen Z is 1.7 times more likely than other generations to step away from leadership roles to protect their well-being.

This is a rational response to watching their managers burn out and deciding the trade-off isn’t worth it. Younger workers have observed the sacrifice model up close — the missed family dinners, the 10 p.m. emails, the manager who hasn’t taken a real vacation in years — and they’re saying, “I don’t want that life.” They’re refusing to accept that suffering is a prerequisite for achievement.

And research consistently links work-life balance with higher job satisfaction and job performance — not lower. There’s no real evidence for the assumption that balance breeds mediocrity.

Redefining success on your own terms

The appropriate reframe to “success requires sacrifice” is that success requires clarity about what matters to you — and the discipline to protect it.

For employees:

The executives who wear sacrifice as a badge of honor are modeling a particular version of success. It’s not the only one. If your company’s culture treats burnout as a badge of honor, that tells you something about the company — not about what success requires.

If you’re being asked to sacrifice everything and told that’s just “what it takes,” consider whether the system is designed for your success... or for the company’s. After all, companies benefit from your overwork.

For self-employed people:

The sacrifice narrative can follow you out of corporate life. When you’re building something on your own, it’s easy to slip back into corporate habits — working around the clock because that’s what “dedication” looked like for years.

It’s also easy to compare yourself to others. I hear entrepreneurs brag about their revenue or how many hours they put into their business. I have to remind myself that another person’s definition of success is not the same as mine.

The advantage of working for yourself is that you get to define what success looks like, from top to bottom.

Final thoughts:

The people who say “you can’t succeed without sacrifice” may genuinely believe it. But their belief is self-reinforcing. The people who’ve made sacrifices point to their own sacrifice as evidence that it’s necessary. They made it to the top, and the cost was enormous, so the cost must have been required. It’s a circular argument.

What if the question isn’t “how much are you willing to sacrifice?” but “what kind of success are you building — and will you have space in your life to enjoy it?”

Thinking about a career change? Download my free guide: The 5 Types of Career Pivots.

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You quit the 9-to-5 to have more control over your time. You wanted flexibility, autonomy, and the freedom to structure your days around your life instead of someone else’s schedule.

Yet here you are, apologizing to a client for not responding to a message immediately. Feeling guilty on a Tuesday afternoon when you’ve only worked for four hours that day. Checking Slack at 9:00 PM because that’s been your routine for most of your working career.

Many solopreneurs don’t realize they’ve inadvertently recreated corporate life until they’re already living it. You traded a demanding boss for a dozen demanding clients. You swapped mandatory meetings for back-to-back Zoom calls. That freedom you craved? Doesn’t exist in your solopreneur world.

To find actual freedom as a solopreneur, you have to recognize that you’re following a corporate playbook — and make a conscious decision to change.

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I recently vibe-coded a new website for myself. Even though I worked at a software company for many years, I’m not a developer. But a few hours with Claude Code, and I was able to create a website just by “talking” to Claude with phrases like, “Can you move that to the center?” or “Can you change the color here?”

To pay someone to create a website for me would have likely cost thousands of dollars. Now, it’s a few hours with an AI coding tool — even without any specialized skills.

This is a small, personal example of something much larger happening across the labor market. AI is changing work from two directions at once. It’s changing how people get hired (AI screening, AI interviews, AI deciding whether your resume ever reaches a human). And it’s changing whether companies need to hire at all, as AI agents start replacing headcount entirely.

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Both of these trends are quietly hollowing out the foundation of how careers have traditionally been built. Workers are rightly nervous because they see the seismic shift coming... but don’t yet know how it will impact them.

AI’s role in hiring: gatekeeper or equalizer?

AI is now embedded in the hiring process, but the results are a mixed bag. Sometimes, AI reduces human biases, while other times it reinforces discrimination that has always made hiring problematic.

Derek Mobley, a Black man over 40 with a disability, applied to more than 100 jobs through Workday’s platform. He was rejected every time, often within minutes, sometimes in the middle of the night. He’s now suing Workday, alleging their AI screening tools discriminate based on race, age, and disability.

The numbers are staggering: Workday disclosed that 1.1 billion applications were rejected using its software during the relevant period. The class action lawsuit could potentially include hundreds of millions of members. Even though the case hasn’t settled yet, the message is clear: companies may be liable for the actions of their AI systems if those systems violate existing laws.

But there’s another way to think about how AI can impact the hiring process.

PSG Global Solutions developed an AI interviewer called “Anna” and had researcher Brian Jabarian at the University of Chicago Booth School of Business run an experiment on 70,000 job applicants. Applicants interviewed by Anna were 12% more likely to get a job offer and 18% more likely to stay in the job for at least a month. Reports of gender discrimination were cut nearly in half compared to human-led interviews.

Surprisingly, when given a choice, 78% of candidates chose the AI interviewer over a human. Why? The theory is that people felt the AI was “less judgy.” For example, a human interviewer might penalize a candidate for being nervous (whether consciously or unconsciously). The AI also captured more job-relevant information: an average of nine topics per interview compared to five for human interviewers.

So which is it? AI can reduce human bias, but it can also perpetuate biases at scale. We don’t fully know the answer (yet), but the difference seems to be in how the AI is designed and what data it’s trained on. For the time being, job seekers have no way of knowing whether that’s working for them or against them.

AI replacing humans: the appeal and the problem

In January 2025, I wrote “No, AI isn’t coming for all the jobs.” I truly believed what I wrote at the time. But it seems more and more that AI can replace some of the work of humans, in ways we couldn’t have predicted even a year ago.

Jason Lemkin is the founder of SaaStr, the world’s largest community for software founders, and a veteran SaaS investor. After two of his salespeople quit, he made a decision that fundamentally changed how his company: he replaced his entire go-to-market team with AI agents. SaasTr now has 20 AI agents managed by 1.2 humans (one full-time, one part-time) doing the work that used to require 10 sales development representatives and account executives.

The result? Same revenue, 24/7 availability, able to handle greater volume, and instant response times.

His framing is really telling: “The job that would have gone to a new rep now goes to an AI agent. The headcount just never gets added.”

But there’s a problem with this approach. You need seasoned, senior people to train AI agents. It worked for SaaStr right now because the senior people already exist. But what happens five to ten years from now when there are no more junior people becoming senior people?

According to data from Revelio Labs, entry-level tech hiring has declined about 35% since January 2023. While this data is specific to tech workers, the pattern will easily extend to other industries as AI tools become more capable and accessible.

It’s a classic case of short-term thinking with long-term consequences. Companies are solving today’s labor struggles by creating a future talent crisis.

So, as workers, what can we do?

I see people online who are still opposed to AI. I get it: there’s still a lot to figure out. In addition to biases and job displacement fears, many of the ethical and environmental questions are very real and unresolved.

And yet... AI isn’t going anywhere. Continuing to resist will likely be a losing strategy.

Early in my career, I helped banks with digital transformation. Customers had bought enterprise software to replace a lot of manual internal processes. There were always employees who insisted that the “old ways” were better. But, after a period of time, the employees who were most successful were the ones who figured out how the software could help them do their jobs better.

AI is going to become as ubiquitous as a calculator or a spreadsheet. The question isn’t whether it will change your work. It’s whether you’ll be ready when it does.

For employees:

If you work for an employer, you’re probably going to need to learn on your own. Part of this is because companies consistently fail to train employees properly. If you wait for formal training, it may never come.

Lemkin’s advice is practical: “Pick an AI tool today. Train it yourself. Become the person at your company who knows how to make AI agents productive. That skill set is the new job security.”

For self-employed people:

AI can extend your skills without extending your costs or the amount of effort you put in. My vibe coding example is proof of that. But it also means your competitors can do the same. Staying ahead means staying curious and constantly testing new tools and new ways of working with AI.

Final thoughts:

The labor market is being reshaped, and we don’t fully know the outcome. The workers who protect themselves are the ones who see this uncertainty and prepare themselves as best they can.

Want to build a life-first business? These reflections will help you determine your priorities.

If you want to support my work as a writer, you can subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

In 2022, I was working at a marketing agency. My manager was... not good at his job. In my prior role at a tech company, I’d been a manager for many years and recognized all the ways the company was spiraling under his indecisiveness and lack of experience.

After a few months of struggling under his leadership, I admitted to him that the job wasn’t working for me. I wanted to come up with some type of exit plan that could allow me to transition out, something I thought he’d be open to as a purported “people-first” company.

His response? He fired me the next day. The role had changed dramatically from what I was hired to do, and we both knew that its current iteration was not the right fit for me. When I said the words out loud, it gave him permission (in his mind) to cut me loose.

As someone who cares deeply about words, I found myself stuck in a strange linguistic limbo. When people asked what happened, I didn’t know what to say. “Fired” implies wrongdoing — like I violated company policy or didn’t perform. But I hadn’t done anything like that. But “laid off“ wasn’t the right phrase either, since it implies business decisions, like restructuring or budget-driven factors.

What actually happened was different: I lost my job because the environment was dysfunctional. The management was bad. The fit was off, not because of some failing on my part, but because the company didn’t know what it wanted from the role and then failed to set me up for success.

I found myself struggling to describe how the job ended, because we don’t have words for that scenario. In the end, I usually say simply, “I lost my job.” Sometimes I’ll say, “I was laid off.” But I refuse to say, “I was fired” because I didn’t do anything wrong.

Without the right language, employees absorb shame that doesn’t belong to them. And employers face no accountability for their role in the situation.

We don’t have employment protections

In many countries, employers can’t just fire someone because the situation isn’t working out. They have to prove cause.

In Japan, “at-will” employment doesn’t exist, and arbitrary dismissals can lead to serious legal consequences. Japan’s Labor Contract Act explicitly states that if a termination lacks “objectively reasonable grounds and is not found to be appropriate by general societal terms,” the termination is considered void. The Philippines takes a similar approach. Employees have a legal “right to security of tenure” and can only be dismissed for “just” or “authorized” causes as defined in the Labor Code. The burden of proof falls on the employer to justify why the termination was necessary.

The United States, by contrast, offers almost zero protection outside of organized labor unions. According to the OECD’s indicators of employment protection legislation, the U.S. is the least regulated country when it comes to dismissing individual workers. At-will employment — which is the default in 49 states — means you can be fired for almost any reason, or no reason at all, as long as it’s not explicitly discriminatory.

Americans have internalized a uniquely individualistic narrative around job loss. We assume that if someone lost their job, they must have done something wrong. The absence of structural protection becomes an invisible weight we carry. Institutional failures become personal shame.

How to reframe your story

Bad management is one of the leading causes of employee departure. According to data from BambooHR, 58% of people leave their jobs because of bad managers. Yet somehow, if the employer makes the decision to part ways instead of the employee, it’s the employee’s fault.

Employers often lean on vague language like “not a good fit.” It sounds neutral, but carries an implicit accusation: that the employee was somehow wrong for the role, rather than the role (or the management, or the culture) being wrong for the employee. The vagueness leaves you holding the bag (and on the financial hook) for a situation you didn’t create.

If you’ve been in this situation — or you’re in it now — here’s how to think about moving forward.

Document what actually happened. You may not need to use it, but having a clear-eyed record of the dysfunction helps you own your story. Write down the specific incidents, the patterns of bad management, and the moments when you tried to make it work. When you write it down, you have clarity. You’re less likely to rewrite history with yourself as the villain.

Don’t use their language. If “fired” doesn’t capture the truth, don’t use it. You can say “the role ended,” or “we parted ways,” or “the job wasn’t sustainable.” You don’t owe **anyone **an explanation that makes you the bad guy in a story where you weren’t.

Recognize the shame isn’t yours to carry. When a job wasn’t a “good fit,” that’s a problem with hiring. You were brought into a situation where you couldn’t possibly succeed. It’s not your fault that you got mixed up in it.

The standard career advice world tells us to never badmouth a former employer. There’s some truth to that. Bitterness isn’t a good look, and interviewers don’t want to hear you trash-talk.

But maybe the real problem is that we’ve made it taboo to call out dysfunction when we see it. We’ve created a system where employers can create toxic environments, make poor hiring decisions, and provide inadequate management — and then frame voluntary or involuntary departures as the employee’s fault.

Until we have language for “I lost my job because the company sucked,” employers will keep escaping accountability. And employees will keep bearing the brunt of those decisions.

Want to build a life-first business? These reflections will help you determine your priorities.

If you want to support my work as a writer, you can subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

The stat that will surprise no one: more than 60% of meetings have no agenda at all. No stated purpose, no direction, no clear reason for existing beyond the fact that they’re already there. Research from Atlassian paints an even grimmer picture: meetings are ineffective 72% of the time, while 78% of people say it’s hard to get their work done because of meetings.

And yet, we keep showing up.

We know meetings suck. But yet, most companies/managers haven’t put in the effort to figure out better ways to collaborate (which might be asynchronously, at a coffee shop, cameras off, etc).

The issue isn’t that meetings are inherently bad, per se. I worked for a company that was very meeting-averse, because the whole team worked asynchronously. We’d only hop on a meeting when the back-and-forth via our project management tool started to get out of control. In that case, it was faster to hop in a meeting and hash things out (and document the decision after the fact).

But on the whole, many people don’t question whether a meeting is the right tool for collaboration. Instead of evaluating the options, we accept the calendar invite (and then wonder why we have Zoom fatigue by 3 p.m.).

Meetings as a default way of collaborating were born during a completely different era of work. Everyone showed up to the same building at 9 a.m., sat in the same conference room, and didn’t have technology to collaborate. Those constraints no longer exist, but the habits remain. They persist not because they’re effective, but because they serve a different purpose entirely: management’s need for visibility and control.

Stuck in a meeting rut

When remote work skyrocketed during the pandemic, it was an opportunity to rethink meetings. We didn’t. We just took the structure of a physical meeting and moved it online.

Not only that, but meetings increased. According to Microsoft’s own data from that year, weekly meeting time jumped 10% almost immediately after offices closed. For the average employee, this was an additional three meetings per week.

To a large extent, I get it. That was a very difficult time since many people abruptly changed their work environments (moving from in-office to a home workspace). People were overwhelmed, and it wasn’t the time to imagine new ways of working. But we’ve had plenty of time since then, and meetings are still terrible.

There’s also a disconnect between workplace flexibility and how meetings are structured. You can work from home, from a co-working space, from a different time zone. And yet, that flexibility rarely extends to how people collaborate. The contradiction is glaring. We acknowledge that people work best at different times and in different environments, but force everyone into the same synchronous meeting format regardless.

Part of this is about optics. Meetings create the appearance of productivity. People in meetings look like people who are working. For remote employees in particular, visibility becomes a proxy for engagement. If you’re not on camera, what are you doing? Meetings scheduled “in the name of transparency” are often just performative — a way for managers and leadership to skirt the harder work of trusting their teams to get the job done.

Asynchronous communication could handle many of these “updates” more efficiently. A written summary takes five minutes to read. I actually think this is a good use case for AI, scouring an email inbox (for example) and writing a succinct recap that keeps the team informed.

A 30-minute meeting takes 30 minutes, plus the context-switching on either side. But async only works if managers are willing to let go of the comfort that comes from seeing faces on a screen and hearing voices in real time. And have to come up with an asynchronous format that’s actually meaningful and not furthering performative work.

Rethinking how we collaborate

Too many people have made “meeting” synonymous with “collaboration.” Companies are stuck in the belief that if people aren’t on a scheduled call, they’re not really working together. But some of the best collaboration happens in writing, over days, with time to think. It happens while out on a walk, when the creative juices are flowing. It happens in environments that look nothing like a conference room or a grid of faces on a video call.

The solution isn’t “better meetings.” It’s questioning whether a meeting is the right tool in the first place.

Before scheduling one, ask yourself what you’re actually trying to accomplish.

• Quick question? How about a Slack message or a short Loom video.

• Brainstorming? Start as a collaborative doc that everyone contributes to before a short meeting.

• A decision that requires input from people? Maybe a 30-minute call, not 60 minutes, with the agenda shared in advance.

• Status updates? That’s a written recap. No meeting required.

If you’re on the receiving end of meeting invites, push back. Ask, “Can we do this async?” or “Do we need the full hour?” If you can, block off meeting-free time on your calendar. Protect this time so you can actually get work done.

True collaboration flexibility means having no default at all. If there’s no automatic assumption that a meeting is the answer, people are forced to actually think about the goal. “Easy for the system” (i.e., maintaining the structure of meetings) rarely means “effective for the people.” And the people — not the system — should be the driving factor.

Want to build a life-first business? These reflections will help you determine your priorities.

If you want to support my work as a writer, you can subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

Not all career pivots have the same impact on your life.

I’ve made several career pivots in my life — some by choice, some not. I made a clear decision to leave a 15-year career in fintech to try something new. After eight months at a marketing agency, I left and joined another agency (not really a pivot, just a job change). I was laid off a year later and started my own business. Each of those transitions felt completely different.

When people talk about pivoting, they often lump everything together. But understanding what kind of pivot you’re making (or considering!) can help you approach it with the right mindset. A pivot born from boredom requires different energy than a pivot forced by a layoff. A pivot driven by curiosity looks nothing like one driven by fear.

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Not every pivot will fit neatly into one of these categories, but identifying your primary driver can help you figure out what you actually need.

1. The forced pivot

This is the pivot nobody wants, but many of us experience. You get laid off. Your company folds. You face industry upheaval. Suddenly, the path you were on doesn’t exist anymore.

Forced pivots are really disorienting because they can strip people of part of their identity. One day, you have a job and an identity attached to it. The next day you’re updating your resume and wondering what just happened.

The silver lining (if there is one) is that forced pivots often push people toward things they wouldn’t have chosen on their own. I had been considering a new path as a freelance writer, but the timing never seemed right. At what point would I have made the leap on my own? Who knows. But losing my job forced the situation.

Let me be clear: I do not think “everything happens for a reason” or any of that nonsense. You are not meant to lose your job so that you’re forced into a stressful situation. I only mean that stressful situations might force you to consider options you otherwise might not have considered.

If you’re in a forced pivot, give yourself permission to grieve the old path before rushing into the next one. But if your financial stability is at stake, speed also matters. You’ll need to adapt quickly, even if you don’t feel ready.

2. The anticipatory pivot

This is the pivot you make before you’re forced to. You see the writing on the wall that your current work won’t be viable for much longer. Maybe it’s AI reshaping your industry. Maybe it’s a shift in market demand. Maybe it’s your company slowly sinking. You decide to move before the decision is made for you.

Reactive pivots require foresight and a willingness to act on information that isn’t yet urgent. Most people wait until the disruption hits them directly. If you can anticipate the change and reposition yourself early, you’ll have more options than those scrambling after the fact.

The risk here is acting on a prediction that doesn’t materialize. Let’s say your company announces a merger with another company, and you think, “I don’t want to stick around for that, I’m out.” So you spend a lot of time and energy finding a new job. Then after you leave, the merger falls apart.

But the bigger risk — for most people — is waiting too long and having the forced pivot happen anyway.

3. The growth pivot

This type of pivot comes from a different place: you’ve outgrown your current role and want something new. Maybe you’ve mastered the skills required, or maybe you’ve hit a ceiling at your current organization.

Growth pivots are driven by a desire for challenge. You’re not running away from something; you’re running toward something. You want to learn new skills, take on bigger problems, or finally make the jump to a different type of role (like managing a team or a decision-making role).

The tricky part? Depending on how much you’re itching to try something new, you might jump into something too quickly and end up in a role or at a company that isn’t the right fit. You don’t want to spend a lot of time and energy looking for a new job only to find yourself at a job you hate.

It also can be difficult to find a new job that requires the skills you want, but don’t have yet. You know you can do the role, but the hiring manager has to be convinced of the same. And, from an employer’s perspective, hiring someone who has “done the job before” is a safer bet than taking a chance on someone.

Growth pivots require you to be honest about what “growth” actually means to you. Is it a title? More money? More autonomy? More impact? The answer will shape what kind of move makes sense.

4. The boredom pivot

This is similar to the growth pivot, but with a crucial difference: you’re not just looking to go up in your career. You’re looking for different.

Boredom pivots happen when the work itself no longer holds your interest. You could keep doing it, and you’re probably really good at it. But you’ve mentally checked out and you’re not sure you can fake enthusiasm in a similar role at another company. This type of pivot often leads people to change industries or start their own business.

This is a harder pivot to justify to others (and sometimes to yourself). “I was bored” doesn’t sound as legitimate as “I wanted to grow” or “I got laid off.” When I told people that I’d quit my executive job at a tech company, I said, “I’m pursuing work I love” (writing).

Boredom is real, and staying in work that doesn’t excite you has costs: your energy, your creativity, and (eventually) your performance. You can’t do your best work if you’re just churning out the same output over and over.

Start paying attention to what does interest you, even if it seems unrelated to your current career. That’s often where your next chapter is waiting.

5. The exploration pivot

This is the pivot fueled by curiosity. You’re not unhappy where you are. You’re not bored. You dind’t lose your job. You just... want to try something else.

Exploration pivots are common among self-employed people and solopreneurs. Your first exploration might be making the leap from corporate to solopreneur. As you build something of your own, you might decide to add a new income stream or test a new product or service.

Think of this type of pivot as experimentation. You’re willing to try something totally different, even if you’re not sure what the final destination will be.

With an exploration pivot, you have to embrace discomfort. You have to be comfortable being a beginner again, and you need enough natural curiosity to put in the time to learn something new. You’re constantly making changes based on what you’ve learned.

What kind of pivot are you considering?

If you’re feeling like you need to make a change, it’s worth asking yourself which of these types of career pivots is driving you.

Most pivots aren’t purely one type. My pivots were a combination of several factors. But understanding the primary driver can help you set the right expectations, identify the right timeline, and find the right support.

Want to build a life-first business? These reflections will help you determine your priorities.

If you want to support my work as a writer, you can buy me a coffee or subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

What happens to your work when you truly can’t keep all the plates spinning?

I’m not talking about a head cold. I’m not talking about a mental health day. (Though I think it’s important to take days as needed and don’t feel like you have to power through).

I’m talking about when your body or mind makes a demand in a way that overrides everything else. When work falls to the absolute bottom of your priority list because you have to put yourself first.

Last year, I found out that I had a brain tumor. It was benign, thankfully, but it still required surgery and a long recovery. It wasn’t the type of absence where I could check in occasionally while lying in bed. I had to completely step away from work for almost two months.

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For anyone who has faced a serious illness — cancer, autoimmune conditions, surgery, mental health crises, etc. — you know how quickly the ground can shift beneath you. One day, you’re worrying about deadlines, deliverables, and the next meeting with your client/boss. The next, you’re trying to process what your doctor just told you while your mind swirls around the question, “What will happen to me?” The dissonance is staggering.

Once you have your bearings, you realize that you have to deal with more than just the personal impact. You have to figure out what will happen at work.

The illusion of indispensability

We’re conditioned to believe we are indispensable. That if we step away, everything will fall apart. Our value is tied directly to our presence and output.

I’ve taken maternity leave three times throughout my career (plus two extended leaves after pregnancy loss). Set aside the fact that paid maternity leave doesn’t exist in the U.S., but I felt pressure to continue interacting with my employer while on leave. I answered emails and handled a few projects behind the scenes. I worked for a small company and definitely had a “What will they do without me?” mentality.

Stepping away to recover from brain surgery was different because the recovery was non-negotiable. I had to stop, no matter how I felt mentally. Every instinct screamed at me to keep going. To not become a burden or inconvenience to my clients and people around me. Internal pressure is baked into our workplace systems, whether we’re working for an employer or working for ourselves.

On top of that, when you’re facing something serious, colleagues often don’t know how to step in (or don’t realize they should). The work piles up. No one picks up the slack, because there’s no road map for “what comes next” with major medical issues. That feeds into the perception that we’re indispensable.

A study from the University of South Florida identified an implicit or explicit expectation that you show up, no matter what. The study refers to this as “presenteeism pressure.” But pushing through comes at a cost: recovery may take longer. And it also takes a toll on mental health, since you’re putting work ahead of health.

A major medical issue can feel like you’re falling off the edge of the world, with no clear path back. Outside of the need to step away from work, suddenly you’re in a different place from everyone around you. They’re exchanging their time and skills for a paycheck. You’re doing the same, while also trying to survive an intensely difficult time in your life.

Helping others

I wish I could tell you that the solution is systemic change. Countries outside of the U.S. have figured out that paid sick leave should be a mandatory benefit. Step away from work, take care of yourself.

But here, there’s no such security. People drag themselves to work when they’re sick because they’re afraid of losing income (or, worse, their job and health insurance). Or they’re afraid of “letting the team down” or “being a burden to others” because it is so ingrained in our culture of Every Person For Themselves.

I have no illusion that companies will suddenly start treating illness like the human reality it is. Instead, change will come at the person-to-person level in how we take care of each other.

If you work for an employer

Take your sick time. I know that sounds obvious, but so many people don’t. Use whatever you’re allowed to take, without guilt. Paid time off is part of your total compensation package, so not taking sick leave is effectively donating your time to the company, when the company should be paying you not to work.

You may not be able to overhaul a company’s lack of a backup plan, especially for an extended medical leave. But you can request better documentation, cross-training, and coverage plans. These can be the difference between feeling supported and lying awake at night panicking about what’s happening in your absence.

Be the person who steps up when someone else steps away. It doesn’t have to be a grand gesture — that’s for the company to figure out. But you can take something off that person’s plate, or send a message that says, “I’ve got this. Focus on yourself.”

If you’re self-employed

This is admittedly harder, especially if you’re running a solo business. You don’t have a team you can turn to. At best, you can have systems in place so things continue to run smoothly, even when you’re away.

Designate someone who can triage things like incoming inquiries or anything critical that might potentially come up (think of it as a solopreneur buddy system). Automate what you can: invoices, recurring communications, project updates. Document your workflows so that if someone else ever needs to step in, they’re not guessing.

Stepping fully away from my business to recover from surgery was incredibly hard. I wondered if everything would collapse without me there. But I prepared as much as I could and had to hope for the best, because working after brain surgery was simply not an option.

Asking for help

People in our lives often don’t know how to support us. They’ll say, “Let me know how I can help.” I hate this, because it puts the burden on the person who needs help to think of something. But the reality is, in a situation like work, they don’t know what would be helpful to you.

If you’re facing a health crisis, prepare your responses to this question. As soon as you can think clearly, make a list. When someone offers to help, reply, “Actually, if you could do XYZ thing for me, that would be great.” As much as you can, match the ask to the person’s interests or skillset.

We treat health crises like a very individual problem, even though most health crises are completely outside of our control. Bodies break down. Work culture that doesn’t account for this is unsustainable at best and inhumane at worst.

If you go through something in your life, take care of yourself first. It’s ok to lean on other people, even at work (especially at work).

And if you know someone going through a major medical issue, be the person who shows up and offers real support.

If you need to step away from work, this free guide walks you through everything you need to do to prepare.

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I grew up believing that careers are a ladder. You start at the bottom and you climb up based on your hard work and perseverance. Eventually, you reach the top where everything falls into place: the title, the salary, the earned respect. If you’re lucky, you reach this point early enough that you benefit from the elevated position for decades before you retire.

Except that ladder? It doesn’t really exist anymore. Companies have largely stopped investing in the very thing that would make career ladders possible. Learning budgets are slashed. Management training programs have all but disappeared.

Gen Z is projected to hold 18 jobs across six different careers in their lifetime. Not 18 jobs in one field — six entire careers. The climb-one-ladder-for-forty-years model is a relic of a workforce that no longer exists.

I fully expected my career to be linear. I stayed at one company for 15 years, and reached the executive level. At one point, I fully expected to stay until I retired. Maybe even be the CEO one day. But then I left, first to pursue a different industry, and then to become a solopreneur. I wish I could say that these transitions were part of some master plan on my part, but they weren’t. They were responses to opportunity, curiosity, and necessity (losing my job).

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While a non-linear career path was once seen as a “red flag” by employers, it’s nothing to apologize for. How you frame the portfolio of experiences in your career is up to you.

The value of a non-linear career

In early 2025, a survey found that nearly 70% of U.S. workers considered changing careers. I think that’s a reflection of the current job economy more than anything else and that people can’t find new jobs in their current industries.

But as major career changes become the norm, companies will have to change their hiring practices (and some already have). Employers are starting to recognize the value of people who’ve worked across different industries, roles, and environments.

Fresh perspectives. People with non-linear career paths look at things differently. They’ve seen various approaches to problem-solving. They can draw connections between seemingly unrelated ideas.

Adaptability. People who have navigated roles in different careers are more likely to handle complex challenges without panicking. They’ve been the new person in the room before. They’ve had to learn new systems, new jargon, new cultures. In an era where AI is reshaping entire industries overnight, that kind of adaptability is critical.

Versatility. The skills in demand today might be obsolete in five years, replaced by skills that don’t even exist yet (can we say AI, for example?). People who’ve built careers on learning new things are better positioned to weather the changes.

And here’s the thing to keep in mind (a mindset I had to break): a non-linear career isn’t “job hopping.” Job hopping implies erratic, impulsive moves. Don’t let anyone frame your career that way simply because you’ve made changes over the years.

With a non-linear career, you’re making intentional moves down different paths. Whether you’ve carefully planned your next steps for months (or longer) or simply reacting to the environment around you, it’s your decision.

How to frame your non-linear career

If you’re currently thinking about your next move, start by shifting your mindset. Think of your career as a portfolio, not a ladder. As you look at the various roles and jobs you’ve had, ask yourself, “What did I gain?”

Self-employed people like myself often have an online portfolio showcasing work. People in traditional jobs should think the same way. If you had an online portfolio of your skills, what would it include?

Document your transferable skills now. Every role teaches you something portable. When I left my job at a tech company, I relied heavily on my skills with customer communication and project management — even though they weren’t the primary part of my new job description. You may not need to use that documentation right, but when the time comes — whether by choice or by circumstance — you’ll be ready.

For people considering a career change, a few thoughts:

Your non-linear background might be why someone hires you. Lead with what you can do, not just where you’ve been. Highlight the connections between your past experiences and the new thing you’re pursuing — even if the connection is simply “I kept learning and taking on new challenges.”

If you take time off before diving into something new, frame it as intentional. Even if the time off wasn’t by choice (like you were laid off or dealing with a personal situation), emphasize what you did during that time. Did you take a course? Keep your skills sharp? Care for a family member? Whatever happened, say, “Here’s what I got from that experience” if the question comes up.

The career ladder was never the reality

For most people, the career ladder was aspirational. It was an idea sold to keep workers compliant and loyal. Keep your head down, do good work, and eventually you’ll be rewarded.

A career ladder discourages risk. It serves employers, not employees. It gave companies a way to string people along with the promise of future promotion while extracting maximum value from them today.

And for a long time, the narrative has implied that deviating from the prescribed path is failure.

I rewatched the movie “Father of the Bride” recently, after the great Diane Keaton passed away. As the bride-to-be introduces her fiancé to her parents, she tells them that he’s an independent communications consultant. Her dad (played by Steve Martin) says, “That’s code for unemployed.” The movie was released in 1991. And that message has been everywhere, for decades.

But the people who’ve “made it” and are happy with the outcome rarely followed a straight line. They pivoted. They took risks. They failed and started over.

So don’t apologize for your winding path. Start owning your portfolio of experience as the asset it truly is.

Want to build a life-first business? These reflections will help you determine your priorities.

If you want to support my work as a writer, you can buy me a coffee or subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

It’s that time of year: the season of reflection, resolutions, Plans™, and Goals™. You might look back on 2025 and think, “Things were stable.” You still have a job. Your team didn’t implode. You limped over the finish line, despite some ups and downs. On paper: a tolerable year.

But here’s the thing about tolerating another year of work: we often think things are stable when we’re really in survival mode. We confuse “not falling apart” with “being okay.”

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Survival mode is bad for our nervous systems. It involves constant vigilance, overfunctioning, and emotional detachment. We crank through tasks without thinking about how exhausted we are. It’s the corporate equivalent of white-knuckling the steering wheel during a snowstorm and calling it “good driving.”

Having a job is not stability. At least, not anymore. And because we’ve been collectively conditioned to praise endurance, we rebrand survival mode as “handling pressure well.” The corporate world applauds us for coping. It took leaving the corporate world entirely for me to realize how distorted my view of stability had become.

We’ve been taught to mistake survival mode for stability

Many of us have worked for companies where overwork was the norm. Staying late? I’m committed. Never taking sick time? I’m dependable. Ignoring every sign of burnout? I’m resilient. The more we pushed ourselves beyond our limits, the more praise we received.

In 2009, the company I worked for laid off one-third of its staff. We were all warned that it was coming. But I was the above-and-beyond person, so I felt like my job was safe. I told myself that my performance mattered. That my dedication would protect me. A few years later, the company went through another round of cuts.

In reality, I should have been far more stressed and concerned than I was. I should have seen the signs that the company was floundering and poorly run. But somehow I convinced myself that my job was safe. I finally broke free of the chokehold that job had me in when I quit in 2021. I recognized that my stable job was actually chaos underneath, and I’d been operating in survival mode for a long time.

From the outside, it’s easier to see what happened: layoffs aren’t sudden, warning signs are everywhere, and individual performance is irrelevant to systemic decisions.

Companies thrive on people who make the same mistake I did: employees who think that overwork shields them from layoffs, or who consistently overfunction as a stress-coping mechanism. This is reinforced by the messages that the company is “like family” (right before adding more to your workload). And there is gaslighting (it’s not that bad, everyone’s stressed). And there are shifting expectations (every deliverable and outcome is a moving target).

For many people, survival mode is the baseline. It’s the water we’ve all been treading in, trying not to drown.

The feeling of corporate stability is emotional, not structural. It’s built on praise, reassurance, manager approval, and staying busy. Companies reward your endurance, otherwise known as “operating in survival mode without collapsing.” Promotions go to the people who can tolerate the most nonsense without complaining. Praise is reserved for the “team players” who sacrifice evenings, boundaries, and well-being. Overwork becomes the norm, and if you’re not exhausted, you worry you’re not doing enough.

But no amount of working hard can buy job security. Your fate will always be in the employer’s hands. Structural stability would look like mandatory severance, required notice periods, formal re-skilling programs, and unemployment insurance that isn’t impossible to navigate.

We’ve become excellent at surviving systems that were never designed to provide stability.

True stability doesn’t feel like a threat

Operating in survival mode gives the illusion of stability because it feels predictable. You know the rules (even if they’re terrible). You know what’s expected (do more with less). You know how to earn validation (tolerate hardship, stay quiet, work harder).

Survival mode convinces you that you are the variable. When things feel unstable, you assume you need to try harder, be better, adapt again. From the outside, it’s obvious that corporate instability was never personal. From the inside, survival mode looks like the responsible approach.

Even after leaving corporate work, survival mode lingers. Your nervous system doesn’t immediately trust calm. And the reality is that underlying structural issues remain that make almost any work inherently unstable. You can opt to leave corporate (like I did) and then be faced with the ups and downs of running your own business.

But as we step into a new year, it’s worth questioning whether what feels “stable” is actually just familiar stress wearing a nicer outfit.

A few things to consider as you reflect on 2025 and look toward 2026:

• Does “being stable” simply mean “I’m no longer in trouble”?

• Do you feel anxious or paranoid when work feels calm?

• Has surviving become your entire personality at work?

The truth is: real stability is quiet. Uneventful. Maybe even a little boring. It’s work that doesn’t require hypervigilance. It’s rest that isn’t earned through suffering. It’s the absence of dread. Or, it’s work that you can control: work where you can pivot in a way that helps you and doesn’t harm you.

As you plan for the year ahead, give yourself permission to want more than survival. Survival mode kept you going. But stability — real stability — is where work is something you enjoy or can comfortably keep at arm’s length while you focus on other aspects of your life.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

I write a lot on The Internet. I have a blog for solopreneurs/freelancers. I have a website of tutorials. I have a newsletter. And I have a personal blog. (On top of all of that, I write for clients.)

I’m writing at least one long-form piece of content every weekday. And while there are similarities in how I structure my writing time and process, each publication is unique. Each audience is unique. Even the platforms are unique: this publication is on Substack, my blogs are on Ghost, and my newsletter is on Kit (more about that here).

As a writer, I’m fascinated by the writing habits of other writers. I’ve devoured the Daily Rituals books by Mason Currey, where he dives into the rituals of creatives. I eagerly read Anne Helen Peterson’s article How I Write Culture Study. And I decided to capture my process for Work. Better.

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Here’s what goes into the typical essay.

It starts with an idea

Almost every essay starts as nothing more than a fleeting idea, like “the benefits of a non-linear career” or “toxic positivity” (both actual ideas I have for future issues).

Ideas can come from social media posts, articles I read, or podcasts I listen to. If I think of something, I try to capture it in the moment so I can come back to it later.

I keep track of ideas in Trello, divided into three categories: New Ideas (might be only a fragment of an idea), On Deck (where I expand on the idea), and Scheduled (where I actually put the idea on my content calendar to write it). In Trello, I’ll link any resources related to the idea, like an article.

An idea turns into an outline

Each essay has three parts: an introduction to the idea, a second section that expands on the idea or provides context, and a conclusion that either provides a contrarian view or gives my thoughts on the idea.

As I expand on an idea (On Deck), I write down every related thought I have. Usually, these are a bunch of bullet points. I might also pull direct quotes or stats from articles I’ve read to support my argument. I’ll also search Reflect, which is my knowledge management system (and also my drafting tool). Reflect syncs notes from articles I read (via Readwise) and podcasts I listen to (via Snipd). I’m searching for related ideas that I might want to incorporate into the outline.

I’ll often take my notes to ChatGPT. I have a project set up for Work. Better. and I’ll ask Chatty to organize my scant notes into a more coherent outline. Chatty will sometimes supplement with additional articles or stats for me to read (and verify).

I’ll take the outline output from ChatGPT and refine it. I’ll remove anything I don’t like. Or sometimes Chatty will include something that leads to another idea. If my outline gets too unwieldy, I’ll break it into smaller pieces and set aside parts for a future article, rather than the one I’m working on.

An outline turns into a draft

Depending on how robust my outline is, drafting is the “easy” part. I’ve already worked out what I want to say and the direction I want to go. Now I’m just pulling everything together.

Of course, there are times when my outline isn’t as good as I’d like. Then I have to spend more time researching/writing simultaneously — so the draft takes longer. I’ve also had instances where I completely change what I want to write for the week, because I want to respond to a current event. In those cases, I have less preparation time between outline and draft, so I’m also less prepared when I sit down to write.

I draft in Reflect. I have automation set up between Trello and Reflect so that, when an idea reaches the “outline” stage, a new document is created in Reflect automatically. The Reflect URL is added back to Trello, so everything is tied together.

Polishing and publishing

Once I’m done with the draft, I return to ChatGPT. I have a style guide created and attached to a Project. Within the project, I ask ChatGPT for feedback. Most of the suggestions are Not Good, but every once in a while, Chatty will suggest something I hadn’t considered or tell me to clarify something. Working without the benefit of an editor is hard, and ChatGPT is the closest I can get to a “second set of eyes” on my work.

Then I’ll load the draft into Substack and run it through Grammarly. I’ll add internal links to related articles I’ve written. All of my prior content is stored in Airtable, and I use Airtable AI to find internal links. I use the prompt:

I’m writing a new article about [insert topic]. What internal links should I include?

Airtable will return a list of links. I’ve found this to be much more accurate than asking ChatGPT to find links on my blog. ChatGPT will still hallucinate links, even with the URL to my blog provided.

Next, I’ll create an image in Midjourney. I use ChatGPT to create a Midjourney prompt based on the draft. Midjourney style codes ensure that each image has a similar look/feel. Someday, if I earn a living from my online writing, I’ll hire an illustrator to create images. But until then, it’s either Midjourney or generic images from Unsplash (and I can’t stand using the same stock photos that everyone uses).

Finally, I’ll schedule the post for publication.

Start to finish, it takes several hours for me to write each essay including research, outlining, drafting, and getting a post ready for publication.

Sharing and re-sharing

I pre-write teasers for each essay. The free editions are published on Friday or Saturday, and I share the link the following Monday. Over the weekend, I’ll add the teaser and the published link to Buffer. I’ll also download images that Substack creates to share on Instagram. I’ll share the link to Substack Notes.

Because I track all of my published content in Airtable, I’ll also re-share past essays across social media, if I think they’re worth re-sharing. I spend a lot of time putting the essays together, and I want to give them as much “life” as possible.

Post-production

A few things happen after a post publishes that I’d be remiss not to mention.

• A record is added to my content library in Airtable, which is where I keep track of everything I’ve published across all platforms. It includes things like the URL, the date published, and topics covered.

• A copy of the post is added to a new Google Doc in my Google Drive. That way, I always have a backup copy of the final, published post.

• The post’s image is added to my Google Drive.

All three of these things happen automatically via Zapier, relying on data from the RSS feed.

Perspectives series

The one type of content that’s handled differently is my Perspectives series. For Perspectives, I either publish guest essays or interviews.

If it’s an interview, I conduct the interview via Google Meet and then edit the transcript. If it’s a guest essay, I only do light editing so that it stylistically matches my publication.

It’s important to me to share voices from other people. I think many people have work stories that they want to share. I give them a platform to do that, whether they share using their names or choose to remain anonymous.

Perspectives usually end up taking me less time. Even though I conduct an interview, editing the transcript is a lot faster than researching/writing an essay.

How the publication has changed over the years

I started this publication in October of 2021. At the time, I just sat down and wrote whatever popped into my head. I published bi-weekly. Now I publish weekly, with a few extra posts each month for paying subscribers. I interview people for my Perspectives series. It requires more planning as the publication has evolved (and also, as my life has gotten busier with more writing).

In total, I’ve published 205 articles in Work. Better. That seems like a lot when I type it out, but also... not a lot? This publication is different than my blog for freelancers/solopreneurs, which prioritizes helpful and tactical advice.

By contrast, here I explore the frustrating and often unfair parts of work. That’s also changed. I started this publication with a post about The Great Resignation. I was filled with optimism about the future of work at the time. But things have certainly gotten dark over the past few years.

The link between the two publications is that corporate life sometimes pushes people to a solopreneur life. It certainly did for me. I know there might be some overlap in the audience, but I still treat them as separate entities. This continues to be a passion project of mine.

Thank you for reading and your interest in the topics I write about.

If you want to support my work as a writer, you can buy me a coffee or subscribe to receive additional issues I publish.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.

A few months ago, I went to visit my primary care doctor. At the start of my appointment, she asked if she could record our conversation. I said, “Of course.” She took out her phone and launched an app.

During the visit, she was more attentive. Because she could focus on talking to me instead of typing notes on the computer. AI was running in the background, doing her documentation. I can’t imagine the number of hours doctors and other medical staff spend on notes, but I’m sure it’s a lot. AI lets them decrease their workloads and focus more on patient care.

That’s the type of AI technology we all need. Something that operates in the background and quietly makes work better. But that’s also not the type of AI that many companies are promising with their “life-changing” AI workflows that will replace humans entirely.

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An AI company called Friend spent $1 million to advertise around New York, including in the subway tunnels. Friend is a wearble that users can talk to throughout the day.

New Yorkers did not take kindly to the ads for Friend, defacing the ads with graffiti lines like “Surveillance capitalism” and “Get real friends.”

Meanwhile, the world collectively assumes that we are on the brink of an AI bubble. McKinsey estimates that companies will need to invest $6.7 trillion by 2030 to keep up with the demand for AI compute — a staggering investment by any measure. But for all the money, it seems like companies are largely building and pushing the wrong solutions.

AI notetaking for meetings and appointments = helpful
AI “friend” that you can wear around your neck = not helpful

The AI we’re getting versus the AI we need

In the past year, CEOs have loved to drop announcements like “We’re freezing hiring due to AI” or “We’re restructuring the organization because of AI efficiency.”

Microsoft has cut thousands of jobs in 2025 alone. In a blog post, chairman Satya Nadella mentions that “AI transformation” is a business priority and that “getting both the product and platform right for the AI wave is our North Star.”

Collectively, companies have invested tens of billions of dollars in so-called AI transformation. Yet, according to research from MIT, 95% of companies have gotten zero return on investment in their AI pilot programs.

On one hand, leaders are acting like AI is about to make the entire company more efficient, so much so that they need to restructure and lay off people. On the other hand, they can’t get basic pilot programs off the ground.

I spent the first ten years of my professional career implementing enterprise software. I know exactly why pilot programs fail. Leadership teams buy products based on a promise, but implementation requires a lot of thinking and planning. Internally, employees who actually do the work have to be on board and understand the promise of an outcome (if implemented correctly).

The biggest failures happened when no one internally was driving the bus. In turn, the employees expected to use the product never received the proper training. Or there wasn’t an internal “champion” excited about change enough to get other people excited to learn. Instead, employees saw the software as an unwelcome disruption and distraction from their work.

With AI, tech companies are sprinting toward “transformative” experience. Workers are asking for practicality — and need the training and proper implementation to make it happen. Instead, they work under the threat that AI could replace them.

And also: “boring and genuinely helpful” doesn’t attract venture capital investments like “flashy and transformative,” so here we are, on the brink of AI bubble collapse.

The contradiction of money, capabilities, and human involvement

The fear of AI’s impact on jobs isn’t universal. According to a survey in Germany, only 5% of employees are worried that AI could threaten their jobs within the next five years. In the same survey, under 40% of employees had received any training related to AI.

No wonder AI experiments at companies fail. I know firsthand from many years of experience training thousands of people to use enterprise software that people often can’t just “figure it out” on their own. They need to be given specific guidelines. And that was for a product that was far more straightforward than AI use cases.

Researchers at MIT’s Sloan School of Management have tried to steer the conversation back to humans. They introduced the EPOCH framework: empathy, presence, opinion, creativity, and hope. These are the human capabilities that AI can’t replicate.

If companies are trying to introduce pilot programs to replicate (or replace) the human qualities introduced in the EPOCH framework, of course they will fail. Think: the companies that have tried to replace customer service agents with bots. That only succeeds in creating a doom loop when customers simply want to talk to a human.

I go back to the example of AI “running in the background” at my doctor’s appointment. I needed empathy, presence, and an opinion from my doctor. And while documentation is important, that’s not a part of her job that requires specific expertise.

If companies centered around EPOCH, the AI conversation wouldn’t be “replacement.” It would be augmentation. Humans are doing meaningful and/or creative work. AI is doing some of the necessary (albeit boring and repetitive) work underneath.

Some of the most transformative technologies in history didn’t replace humans. They replaced tedium. The calculator didn’t eliminate math. It eliminated the tedium of doing math by hand.

But right now, companies are still chasing spectacle over substance. It’s not that AI isn’t powerful. It’s that leaders want the benefits of AI without doing the hard, boring, systems-level work required to make AI actually useful. And when they get to those use cases — like an AI notetaker during medical appointments — does that justify the amount of investment in AI companies?

So yes, I’m excited about the AI that quietly makes life easier — the kind that helps my doctor be present, reduces tedious work, and helps teams spend less time on repetitive tasks. But I’m not sure that’s what CEOs are looking for when they talk about “transformational” change.

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The Wall Street Journal published an opinion piece titled “Why Work-Life Balance Will Keep You Mediocre.” Certainly a headline designed to draw ire from many readers, myself included.

The author advocates “ruthlessly” optimizing your time, from missing important events with loved ones to declining social events. The goal? In his case, he built a company worth $20 million and set himself up with financial freedom for the rest of his life.

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My gut reaction was, “That’s no way to live a life.” There was a time, in my early 20s, when I poured my energy and time into my job. I wore the badge of long hours and unlimited availability, replying to emails long into the evening as I worked on projects.

Then I had kids. I began working remotely. In no way did this keep me “mediocre.” In fact, I’d argue that work-life balance improved my career.

Learning to focus my impact

If you think you have 100 hours to work each week, you’ll undoubtedly find ways to fill 100 hours.

When I became a parent, my “extra” time disappeared. I couldn’t reliably work outside of business hours. Even my work within business hours changed, since small children are frequently sick or school is closed for various holidays.

I became brutally efficient with my time. I learned to think of my work in terms of the results it produced, not the hours I put in. I advocated for better apps and tools at the company that could help the entire team do more with less time. I taught myself how to use automation tools to keep tasks humming in the background.

“Work smarter, not harder” became my mantra. I wasn’t willing to sacrifice time with my family or a career I’d worked hard to build. I had to figure out how to get more done with less effort so I could enjoy a balance between work and life outside of work.

Learning adaptability and empathy

Being a parent taught me to be more adaptable. Kids don’t wait for your schedule. They don’t conform to your ideal workday. You have to pivot quickly to Plan B when Plan A fails.

I became a manager early in my career, and I’m now embarrassed to say that I was a very rigid thinker. I couldn’t understand when “life got in the way of work.” I assumed that other people were bad at managing their time.

Having kids made me more empathetic. I saw how life outside of work — even for reasons unrelated to children – happened, and deserved compassion.

I wasn’t mediocre by being more adaptable and empathetic. I became more human.

The entire team benefited from flexibility. As a manager, I let my team know that I trusted them to get work done, without micromanaging oversight. And if something unexpected came up, we would adjust.

Leading by example

At work, people take cues from other employees – especially those senior to them. If a company claims to be flexible, but your manager sends Slack messages while on vacation, it’s a pretty good indicator that you shouldn’t expect any work-life balance.

Or how about the job that provides zero coverage when you take time off? You return to a pile of work and spend the next week working extra hours to catch up. Not exactly restful if you’re “punished” for taking time off with more work.

The more I embraced work-life balance, the more my team followed suit. If my kids were sick (or I was sick), I took the day off. I took fully unplugged vacations during the year and encouraged others to do the same. We set up internal systems so that anyone taking time off had adequate coverage.

Most importantly, my kids have seen how much I prioritize work-life balance. I’m there to pick them up from after-school activities. They know that “being sick” means “resting and recovering” — not pushing through.

When my son was little, someone asked, “What do you want to be when you grow up?” He responded, “I want to work from home.” It was a proud moment for me, because I knew that my efforts to model work-life balance were paying off.

Do I have a million-dollar business, like the author of “Why Work-Life Balance Will Keep You Mediocre”? No. But his priorities are just that: his priorities. Not a universal truth.

Pursuing work-life balance is a worthwhile career goal. Don’t let anyone tell you otherwise.

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On November 11, 2008, I posted on Facebook:

“... wait, how did I get roped into doing produce specifications analysis on my day off?”

(At this point, Facebook’s primary purpose for me is to look at my “On This Day” memories, but I digress.)

November 11th would have been a federal holiday (Veterans’ Day), which my company would have observed. Yet, I volunteered — or was voluntold — to review product documentation.

Over the years, the company changed drastically. It became an incredibly flexible workplace. I developed better boundaries.

One of the reasons I stayed with that employer so long (15 years) was workplace flexibility. A few years ago, it felt like other workplaces were catching up. Many companies were talking about work-life balance. Remote work and async communication became the norm. Some companies even piloted 4-day workweeks and loudly celebrated how well they were doing.

It felt… hopeful. I even wrote about how hopeful it was. The job market had swung in favor of workers, who could simply and easily leave if the workplace wasn’t flexible enough or was toxic.

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But now? The pendulum has swung alllllll the way back. Companies across the U.S. are demanding that workers return to the office. Silicon Valley is embracing grind culture again, with the introduction of the 996 workweek (9:00 a.m. to 9:00 p.m., 6 days per week).

We were told that work should fit into our lives. That flexibility was the future.

Instead, companies are loudly and unapologetically walking it back. Workers are left wondering: What happened?

The flexibility that wasn’t built to last

Pandemic-era flexibility wasn’t a values shift. It was a reaction to a global crisis. Companies needed people to keep working, and the only way for that to happen was to adapt, overnight, to remote work.

When my employer went fully remote in 2010, the company hired consultants to help with the transition. It was a work-in-progress for months as we learned to take advantage of flexible hours. We also had to learn to trust our colleagues in a way that we didn’t when everyone was working synchronously.

Companies embraced remote and hybrid work at the onset of the pandemic, but didn’t have a specific plan. Everything became fluid… including when people were supposed to stop working. Slack notifications at 10 p.m. No ability to “step away” from work. Flexible work turned into “always on,” without boundaries.

Now we’re in a place of economic uncertainty. Companies are fighting to maintain the record-breaking profits they saw during the pandemic, even though consumer behavior has changed. As a result, companies have retreated to what feels safe and familiar: control and structure.

The grind mindset never disappeared. It was just hiding for a few years.

Employees have felt whiplash over the past few years, because the story and promise from companies keep shifting. One year, flexibility is the future. The next year, it’s butts-in-seats or you’ll lose your job.

What has remained the same, even as workplace flexibility has expanded and contracted, is an overarching theme: do more. Do more for the same salary. Put in more hours, even if your hours are working from home. The demand to do more may have felt tolerable while employees were at home and had a modicum of control over their days. But back in the office, this is intolerable.

It has always been about boundaries

MSN recently published an interview with the managing director of a law firm. He was “miffed” by the attitude of younger workers (Gen Z) who refuse to do anything outside of contracted hours. In the interview, he also noted that Gen Z is “unimpressed” with things like after-work happy hours or the company Christmas party.

Flexibility was never the problem. It’s the perception by managers and executives that employees are less committed to their jobs. When they work from home, they can blur work and home life. In the office, they’re willing to do what they’re paid to do and nothing more.

Gallup’s State of the Global Workplace report found that 79% of employees are either not engaged or actively disengaged. In the intro, Gallup points out that the drop in employee engagement cost the world economy $438 billion.

Is it disengagement? Or is it setting boundaries?

Let’s say that older generations were willing to work 10-hour days, so an additional 10 hours per week. I’ve written before that additional work without additional pay is corporate volunteerism and comes at no benefit to the employee. Now Gen Z says, “Nah, we’ll put in the work we’re paid to do and that’s it.”

Of course that’s going to cost the company money (or “productivity” as Gallup calls it). The company is squeezing fewer hours from each employee.

Some countries have recognized this. “Right to disconnect” laws have gone into effect in France, Italy, and Australia. Employers cannot contact employees outside of defined working hours, codifying the right to set boundaries between working hours and non-working hours.

A similar law was introduced in California in 2024, but died in committee. The 996 tech companies of Silicon Valley were probably horrified that it was even proposed.

Companies can swing from flexibility to grind culture as often as they want. But you don’t have to be dragged along with them.

The only way to protect yourself from corporate demands is to build your own boundaries, whether you’re in the office or working remotely. End your day at a specific time. Don’t reply to messages outside of your working hours. Companies won’t set those boundaries for you and will do everything they can to push you as far as you’re willing to go.

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I always thought I was bad at math. It didn’t come naturally to me.

Then, when I was sixteen, I got a job as a bank teller. My dad was on the bank’s board, and the owner liked to hire employees’ kids — he believed we’d work harder. (He wasn’t wrong. We all felt like we had something to prove).

“Banking math” was different. As it turns out, I was very good at it. Balancing a cash drawer made perfect sense to me. It was concrete and practical, unlike the calculus class I took. Later, in college, I started working in loan processing. I dug into complex banking regulations and read teh language of dnese financial laws to understand things.

That led to a job at a banking software company after I was done with college. I stayed there for 15 years. I found that I was also really good at data. I taught myself SQL queries. I became the company’s first product manager, writing technical specifications for new features.

I convinced myself that I loved my job, because I was good at it.

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But in reality, it was a career that “chose me” rather than one I chose. I flourished because I had a knack for data and complex systems. Working at a software company had a natural career progression through the ranks and paid well.

It took a global pandemic for me to step back and ask myself, “What am I even doing?”

The trap of being good at your job

Being good at something can give us fulfillment. When people praise you for your skills, it feels validating. Promotions, raises, and new responsibilities confirm you’re doing something “right.”

Before long, being really good at your job becomes a core part of your work identity. You stand out among your peers. “The cream rises,” as the saying goes. It’s how people end up in jobs — or even spending their entire careers — in work they never consciously chose. They got good at something early, and momentum kept carrying them forward.

When you’re rewarded for something, it’s easy to mistake recognition for purpose. You start building your self-worth around external validation: performance reviews, titles, and bigger paychecks. Genuine interest falls to the bottom of the priority list.

The thing about being good at your job? It’s hard to disengage. You’ve set the expectation that you’re good, which usually means you also work hard. Or manage other people. Disengagement or quiet quitting might not be an option.

I didn’t really start questioning my job until July of 2020. The COVID-19 pandemic was raging, and I gave myself permission to truly step back. In many ways, I was forced to step back — because I had no childcare and my kids needed me. I started to realize that I didn’t care the work I was doing. Or rather, there were things about the industry that I enjoyed, but the exact work was something I was “good at” rather than something I enjoyed.

Sometimes, we build entire careers out of what we can do, not what we want to do.

When a career no longer feels like it’s “yours”

The timing was fortuitous. I quit my job at the onset of The Great Resignation, and finding another job was easy. Now, I work for myself — which feels like what I was meant to do all along. I always wanted to control my work, and it turns out I’m happier working solo than working as an executive.

But it took a long time for me to recognize that being “good at work” wasn’t enough. Praise wasn’t a substitute for fulfillment. Recognizing the disconnect in your career is Step Number 1.

Maybe you fell into your industry by accident.

Maybe you feel fatigue from your workload and misalignment between what you do and what you feel like you’re meant to do.

Ask yourself:

Am I proud of your work, or just proud that I can do it well?

There’s a difference.

The job market is brutal right now, so it might not be the time to explore something new. My friend Nick Moore, a fellow freelance writer, wrote about working for satisfaction, not passion. And I think that’s an ok place to be. If you can take a step back from being “good at your job” — so you feel like you’re not overworked or over-invested — you can be “satisfied with your job” and leave space for other things in your life.

Nick wrote:

Your workplace is not your family, but work is a part of life. Putting work in the context of your life gives you more variables to think about, more dials to twist, more options to consider. You’re not stuck in the false binary of passion or drudgery.

You must work, yes, but you can figure out ways to find satisfaction in the day-to-day, maximize money and flexibility along the way, and fill the rest of your time with life rather than squeezing your life into work.

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Have a work story you’d like to share? Please reach out using this form. I can retell your story while protecting your identity, share a guest post, or conduct an interview.