#economics

I've been wondering myself lately: Is AI working for us, or are we working for AI?

What they found across more than 40 “in-depth” interviews was that nobody was pressured at this company. Nobody was told to hit new targets. People just started doing more because the tools made more feel doable. But because they could do these things, work began bleeding into lunch breaks and late evenings. The employees’ to-do lists expanded to fill every hour that AI freed up, and then kept going.

As one engineer told them, “You had thought that maybe, oh, because you could be more productive with AI, then you save some time, you can work less. But then really, you don’t work less. You just work the same amount or even more.”

Over on the tech industry forum Hacker News, one commenter had the same reaction, writing, “I feel this. Since my team has jumped into an AI everything working style, expectations have tripled, stress has tripled and actual productivity has only gone up by maybe 10%. It feels like leadership is putting immense pressure on everyone to prove their investment in AI is worth it and we all feel the pressure to try to show them it is while actually having to work longer hours to do so.”

The researchers’ new findings aren’t entirely novel. A separate trial last summer found experienced developers using AI tools took 19% longer on tasks while believing they were 20% faster. Around the same time, a National Bureau of Economic Research study tracking AI adoption across thousands of workplaces found that productivity gains amounted to just 3% in time savings, with no significant impact on earnings or hours worked in any occupation. Both studies have gotten picked apart.

The report stated that layoffs are up 118% from the same period last year and 205% from December 2025. On the inverse side, employers added 5,306 jobs, the lowest since January 2009. It’s important to note that Challenger began tracking labor data in January 2009.  “Generally, we see a high number of job cuts in the first quarter, but this is a high total for January,” said Andy Challenger, the workplace expert and chief revenue officer of the company. “It means most of these plans were set at the end of 2025, signaling employers are less-than-optimistic about the outlook for 2026.” Transportation had the most cuts in January at 31,243, according to the report. The majority of these cuts came from UPS’s major layoff announcement.  Amazon, one of the tech industry’s largest companies, also announced significant job cuts. The company said it would lay off 16,000 workers, mostly corporate-level employees. The Challenger report said Amazon was the main contributor to the nearly 23,000 job cuts the tech industry saw last month.  The health care industry also saw large cuts, with more than 17,000 workers losing their jobs. That was the largest staff reduction for the industry since April 2020, the report stated.  “Healthcare providers and hospital systems are grappling with inflation and high labor costs,” researchers wrote. “Lower reimbursements from Medicaid and Medicare are also hitting hospital systems. These pressures are leading to job cuts, as well as other cutting measures, such as some pay and benefits.”

The monthly employment report gives a snapshot of Washington's job market. It includes the unemployment rate for Washington and the nation, the number of people working or looking for work in Washington, and the number of jobs in each industry. You can use this report to understand overall economic trends and how different industries are doing.

In 2025, the central Puget Sound region lost 12,900 jobs. If you exclude the anomaly of the COVID-19 pandemic, this is the first time the region has experienced an annual decrease of jobs since 2009, during the depths of the Great Recession.

Historically, jobs in the Puget Sound region have grown by between 30,000-40,000 jobs per year. Employment growth during the Amazon boom was significantly higher, peaking at 61,100 jobs added in 2016.

US job openings fell to 7.15 million in November, down from 7.45 million in the previous month, marking the lowest level since September 2024, according to the Bureau of Labor Statistics’ Job Openings and Labor Turnover Summary report released Wednesday.

declined across most industries, with the biggest pullback seen in leisure and hospitality, healthcare and social assistance, and transportation and warehousing. Only a few industries, including construction and retail, added jobs.

Hiring slowed as well, while layoffs declined to a six-month low, extending the “hire less, fire less” mode that has defined the US labor market for much of the past year

Even without adding in Trump’s own $5.5 billion net worth, Forbes estimates that his top advisors are worth $7.5 billion, more than doubling the $3.2 billion combined worth of Trump’s 2019 Cabinet. (By contrast, Biden’s Cabinet of regular Joes was barely worth $110 million combined in 2021.)

Nearly 400 millionaires and billionaires from 24 countries are calling on global leaders to increase taxes on the super-rich, amid growing concern that the wealthiest in society are buying political influence.

“A handful of global oligarchs with extreme wealth have bought up our democracies; taken over our governments; gagged the freedom of our media; placed a stranglehold on technology and innovation; deepened poverty and social exclusion; and accelerated the breakdown of our planet,” it reads. “What we treasure, rich and poor alike, is being eaten away by those intent on growing the gulf between their vast power and everyone else.

“The super-rich are being given complete free rein. It is beyond comprehension that the richest 1% now own three times more than the world’s total public wealth combined.

In just the past week, President Donald Trump has ordered defense companies to halt dividends and stock buybacks, and limited executive compensation to $5 million a year; ordered Fannie Mae and Freddie Mac to buy $200 billion of mortgage-backed securities; ordered an array of energy firms to invest in Venezuelan oil infrastructure, called for a 10 percent cap on credit card interest rates; announced steps to ban institutional purchases of single-family homes; and opened a criminal investigation into Jerome Powell's handling of Federal Reserve building renovations in an attempt to influence monetary policy.

Tech companies have moved more than $120bn of data centre spending off their balance sheets using special purpose vehicles funded by Wall Street investors, adding to concerns about the financial risks of their huge bet on artificial intelligence.

Meta in October completed the largest private credit data centre deal, a $30bn agreement for its proposed Hyperion facility in Louisiana that created an SPV called Beignet Investor with New York financing firm Blue Owl Capital.

The SPV raised $30bn, including about $27bn of loans from Pimco, BlackRock, Apollo and others, as well as $3bn in equity from Blue Owl.

Trump said at the roundtable, adding "this money would not be possible without tariffs."

Another way to spend the money that’s already been spent many times over.

Research by Harvard Business School Professor Alberto Cavallo illustrates the downward trend in the price levels for many retail goods, followed by an acceleration after tariff announcements. Prices on both imported and domestic goods have climbed modestly but steadily since March, even if the hike is still small relative to the size of the tariffs.

The researchers created indexes with daily prices collected by PriceStats, a private firm cofounded by Cavallo that provides online data for over 350,000 products sold by five major US retailers. The indexes allow them to track price changes in specific categories and from countries of origin. Overall, the prices of imported products have increased faster than those made in the US. An extended analysis, going back to January 2024, explores price changes of goods relative to their pre-tariff trend.

Current Tariff Rate: Consumers face an overall average effective tariff rate of 17.9%, the highest since 1934. After consumption shifts, the average tariff rate will be 17.4%. (If IEEPA tariffs are invalidated, the rate would be 9.1%.)

Overall Price Level & Distributional Effects: TBL assumes the Federal Reserve “looks through” the tariffs and allows prices to rise such that the tax burden is felt through prices rather than nominal incomes. The price level rises by 1.3% in the short run, representing a loss of $1,800 for the average household and $1,000 for households at the bottom of the income distribution. (Without IEEPA, the price level impact would instead be 0.6%.)

Walmart did announce a 25% reduction. It is offering this year’s basket for under $40, down from last year’s price of around $55.

But aside from the fact that any one company’s holiday promotion is not a good measure of the state of US inflation, the price of Walmart’s Thanksgiving basket is an especially poor proxy – because the composition of the basket changes every Thanksgiving.

The 50 year mortgage is a scam. I’m just not sure if the administration actually knows that or not.

By the numbers: Consider someone taking out a $500,000 home loan. The current rate on a 30-year mortgage is 6.22%, per Freddie Mac. For these calculations, let's assume that a 50-year loan's interest rate exceeds the 30-year by the same margin that the 30-year rate exceeds a 15-year rate.

That translates to a 6.94% rate on the 50-year loan — which would then have a monthly payment of $2,985, only $83 less than the 30-year mortgage. Zoom in: In the early decades of the loan's repayment, the 50-year borrower's payments would almost entirely go to interest, paying down the debt much more slowly.

After five years, for example, the 30-year borrower would have paid off $33,481 of the loan balance, versus $6,707 for the 50-year borrower. After three decades, when the 30-year mortgage is fully paid off, the 50-year borrower would still owe about $387,000.

Be patient. Not afraid.

For layoffs in the tech sector, a likely culprit is the financial stress that companies are experiencing because of their huge spending on AI infrastructure. Companies that are spending a lot with no significant increases in revenue can try to sustain profitability by cutting costs. Amazon increased its total CapEx from $54 billion in 2023 to $84 billion in 2024, and an estimated $118 billion in 2025. Meta is securing a $27 billion credit line to fund its data centers. Oracle plans to borrow $25 billion annually over the next few years to fulfill its AI contracts. 

“We’re running out of simple ways to secure more funding, so cost-cutting will follow,” Pratik Ratadiya, head of product at AI startup Narravance, wrote on X. “I maintain that companies have overspent on LLMs before establishing a sustainable financial model for these expenses.”

We’ve seen this act before. When companies are financially stressed, a relatively easy solution is to lay off workers and ask those who are not laid off to work harder and be thankful that they still have jobs. AI is just a convenient excuse for this cost-cutting.

Last week, when Amazon slashed 14,000 corporate jobs and hinted that more cuts could be coming, a top executive noted the current generation of AI is “enabling companies to innovate much faster than ever before.” Shortly thereafter, another Amazon rep anonymously admitted to NBC News that “AI is not the reason behind the vast majority of reductions.” On an investor call, Amazon CEO Andy Jassy admitted that the layoffs were “not even really AI driven.”

We have been following the slow growth in revenues for generative AI over the last few years, and the revenues are neither big enough to support the number of layoffs attributed to AI, nor to justify the capital expenditures on AI cloud infrastructure. Those expenditures may be approaching $1 trillion for 2025, while AI revenue—which would be used to pay for the use of AI infrastructure to run the software—will not exceed $30 billion this year. Are we to believe that such a small amount of revenue is driving economy-wide layoffs?

The SNAP shutdown halts roughly $8 billion a month in federal food assistance — money that usually flows straight into grocery stores and helps feed 42 million Americans. Without it, both low-income households and major retailers like Walmart, Aldi and Kroger feel the pinch. Driving the news: Companies and nonprofits are rolling out new programs to keep food flowing — from free grocery credits to multimillion-dollar donations.

Seems about right. Interesting metrics on startups too:

• Foundation Model Labs: Revenue must grow faster than Compute Costs.
• Enterprise AI Platforms: High Gross Retention because of high AI Feature Adoption.
• Application Layer: Net Revenue Retention (NRR) > 120% and CAC Payback < 12 months.
• Inference API Players: High Revenue per GPU-Hour (pricing power).
• Energy/Infrastructure: Structural Energy Cost Advantage and high utilization.

Energy infrastructure, unlike GPUs that become obsolete in five years, compounds in value over decades.

Consider the math: A single large AI training cluster can require 100+ megawatts of continuous power — equivalent to a small city. The United States currently generates about 1,200 gigawatts of electricity total. If AI compute grows at projected rates, it could demand 5-10% of the nation’s entire power generation within a decade.

And unlike fiber optic cable or GPU clusters, power infrastructure can’t be deployed quickly. Nuclear plants take 10-15 years to build. Major transmission lines face decades of regulatory approval. Even large solar farms require 3-5 years from planning to operation.

The companies prepping themselves to survive scarcity aren’t just stockpiling compute—they’re building root systems deep enough to tap multiple resources: energy contracts locked in for decades, gross retention rates above 120%, margin expansion even as they scale, and infrastructure that can flex between training and inference as market dynamics shift.