Stop Obsessing About Work All the Time
A revenge fantasy about your boss. Your to-do list. That flop of a meeting. You need to quit ruminating about your job. Here’s how to do it.
4 min
It’s one thing to work long hours. It’s another to surrender your free time to swirling thoughts of office predicaments and projects hanging over your head.
Many of us can’t let work go. It’s sinking our mental health and damaging our relationships. We need to shift the approach in our heads.
Joe Mellin thought maybe a week alone in the woods would do it. He journeyed by plane, bus and minivan to a remote pocket of Colorado for a program that coordinates solo wilderness excursions. Armed with a toothbrush, a journal and some dried split peas, the 41-year-old hunkered down to meditate and find out who he was.
Turned out, he was someone who really liked obsessing about his job.
“I was literally saying, Joe, you’re in Colorado, you’re off work, you’re in the middle of a forest, stop thinking about work,” the Washington-based tech worker recalls. By hour 36, in the quiet of his sleeping bag under the moon, he gave in. Soon he was sketching PowerPoint presentations in his journal, filling 20 pages with notes before he was finally able to let go.
Whether you’re on a spiritual quest in Colorado or at the playground with your kids, internally troubleshooting next week’s client pitch or entertaining revenge fantasies about a colleague, there’s a cost.
“You’re getting aggravated anew each time,” says Guy Winch, a psychologist and author who fashioned a TED Talk on the subject.
We often think we have to fix our jobs to relieve our work stress. “You might,” he says. “But fix you first.”
Break the cycle
Start by tracking how much time you’re spending ruminating about work, Winch says. For many of his patients, that’s 10 to 20 hours a week—after-hours. (At the office, we’re generally too busy doing the job to perseverate about it, he says.)
To stop the cycle, tax your mental capacity with something more complex than Netflix or a walk. Try a memory task like naming all 50 state capitals or recalling the items in your fridge, Winch suggests. Two to three minutes is often enough for a reset.
Then, channel what you had been obsessing about into something useful. Ask yourself: What’s the actual problem to be solved? If you’re worried about workload, can you delegate to teammates or decline meetings?
If there’s nothing to be done about the situation—some co-workers are just annoying—try to find the silver lining, Winch adds. Maybe this is the spark you finally need to find a new, better job. Maybe you’re building skills that will help you in the future.
When you are your job
We’re bombarded with emails, Slack messages and back-to-back Zoom calls during the day, so it’s no wonder we can’t turn off our brains when we shut the laptop. We mentally brace for pings of all kinds, even when they’re not coming.
And some of this is on us. So many employees have tied their identities to their jobs.
“They’ve defined their whole value this way, so it makes it that much harder to let go of things,” Rebecca Zucker, an executive coach, observes of some of her clients. “Something that goes badly at work can feel annihilating.”
Lauren Orcutt, a 36-year-old in Sacramento, Calif., loves being a copywriter. Some of her friends and family don’t love constantly hearing about it, she says.
“I think about it so much, it just comes out,” she explains.
She’s often up at 3 a.m., galvanised by an idea for a new blog post or needled by the realisation she messed up an email. “I kind of felt like I was working all night” for months, she says. Her sleep suffered.
To reclaim her brain space, Orcutt started jotting down her thoughts in a lavender notebook she now keeps on the nightstand. Mistakes that are plaguing her get their own page, which she rips out in the morning.
“I am going to throw it away and move on with my life,” she says. Even capturing the good ideas calms her, helping her drift back to sleep.
Reprioritise your life
Ruminating about work can make it hard to fall and stay asleep, and damage our mood and mental health, says Verena C. Haun, a professor at the Julius Maximilian University in Würzburg, Germany, who studies psychological detachment from work. Depleted, we often perform worse at work the next day.
She suggests marking the transition from work with a simple ritual, like washing out your coffee cup or changing clothes. Find a hobby, or three, that make you truly forget about work while you’re doing them. Set a goal, say, an hour spent gardening, especially on stressful work days.
You can’t think about work when you’re trying not to crash a boat, Jackie Hermes, the chief executive of a marketing firm, says she discovered. When the onset of the pandemic caused her business’s revenue to drop 40%, she rethought her relationship, once all-consuming, with her job.
“Is this really what I’m dedicating my entire life to?” she asked herself.
She doesn’t work less hours now, but she has changed how she thinks about work, allowing herself more flexibility and trying new things in her personal life. During the day, she’ll sometimes pop into the boating club she recently joined or catch a Milwaukee Brewers game at the ballpark.
“Work isn’t the only priority anymore,” she says, noting that so much about our jobs is out of our control anyway.
Now she tells herself, “I’m not behind. It’s always going to get done.”
Copyright 2020, Dow Jones & Company, Inc. All Rights Reserved Worldwide. LEARN MORE
From making unpopular decisions to learning when to listen, leaders from five businesses reveal what nobody prepared them for — and how running a company has challenged their expectations.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
The Swiss watchmaker’s first collaboration with Atlassian Williams F1 Team produces two sporting Laureato models inspired by the team’s 2026 racing car.
Rising rates, construction inflation and shrinking investor confidence are pushing Australia deeper into a dangerous housing spiral that monetary policy alone cannot fix.
