Does Warren Buffett Know Something That We Don’t?

When the world’s most-followed investor doesn’t feel comfortable investing, should the rest of us be worried?

Warren Buffett , who has quipped that his favourite holding period for a stock is “forever,” continues to have substantial money at work in American companies. But he has never taken this much off the table either—a whopping $325 billion in cash and equivalents, mostly in the form of Treasury bills.

To appreciate the immensity of that hoard, consider that it would allow Berkshire to write a check, with change left over, for all but the 25 or so most-valuable listed U.S. corporations—iconic ones such as Walt Disney, Goldman Sachs , Pfizer, General Electric or AT&T. In addition to letting the dividends and interest pile up on its balance sheet, the conglomerate has aggressively sold down two of its largest shareholdings, Apple and Bank of America, in the past several months. And, for the first time in six years, it has stopped buying more of the stock it knows best— Berkshire Hathaway.

Does that mean mere investing mortals should be cautious about the market? Maybe, but it tells us even more about Berkshire.

Buffett and his late business partner Charlie Munger didn’t outperform the stock market 140-fold by being market-timers. Probably Munger’s most famous quote is his first rule of compounding: “Never interrupt it unnecessarily.” Investors who follow Berkshire closely and hope for a bit of its magic to rub off on their portfolios pay very close attention to what it is buying and selling, but much less to when.

Yet the seemingly always optimistic and patient Buffett has turned cautious before, famously shutting his extremely successful partnership in 1969 when he said markets were too frothy and also building up substantial cash in the years leading up to the global financial crisis—money he deployed opportunistically.

“He’s cognisant of the fact that markets gyrate and go to extremes,” says Adam J. Mead, a New Hampshire money manager and Buffetologist who is the author of “The Complete Financial History of Berkshire Hathaway.”

Stock values being stretched doesn’t mean they are on the precipice of a crash or even a bear market. Instead, zoom out and look at what today’s valuations say about returns over the next several years, which will include both good and bad periods. Goldman Sachs strategist David Kostin predicted recently that the S&P 500’s return over the next decade would average just 3% a year—less than a third of the postwar pace.

Kostin’s report went over like a record scratch at a time of high investor optimism, but it is consistent with other forecasts. Giant asset manager Vanguard recently predicted an annual return range of 3% to 5% for large U.S. stocks and just 0.1% to 2.1% for growth stocks over a decade. And Prof. Robert Shiller ’s cyclically adjusted price-to-earnings ratio is consistent with an average return of about 0.5% a year after inflation —similar to Kostin’s projection.

Then there is the even simpler “Buffett Indicator,” which the Oracle of Omaha once called “probably the best single measure of where valuations stand at any given moment.” There are variants on the theme, but it is basically a ratio of all listed stocks to the size of the U.S. economy. Taking the Wilshire 5000 Index as a proxy it is now around 200%, which would leave it more stretched than at the peak of the tech bubble.

With T-bills now yielding more than the prospective return on stocks, it might seem that Buffett has taken as many chips off of the table as possible since there is no upside in risky stocks. But he is on record saying that he would love to spend it.

“What we’d really like to do is buy great businesses,” he said at Berkshire’s 2023 annual meeting. “If we could buy a company for $50 billion or $75 billion, $100 billion, we could do it.”

With Berkshire now worth $1 trillion, it would take a deal of that size to move the needle. Mead explains that a transaction matching acquisitions like 2010’s Burlington Northern Santa Fe deal or the 1998 acquisition of insurer General Re would be worth $100 billion scaled to today’s balance sheet.

Could it also mean that Buffett sees value in keeping dry powder ahead of the next crisis or general froth in the market? Yes, but he isn’t saying, and individual investors also have more options than he does. First of all, we don’t have to pay a 20% or more premium to the market price to invest in a business like Berkshire would in a takeover. We also can sail in much shallower waters and smaller ponds. For example, Vanguard’s 10-year projections range from 7% to 9% a year for non-U.S. developed market stocks and 5% to 7% for U.S. small capitalisation stocks. Other than a very profitable bet on Japanese trading companies in recent years, though, Buffett has kept his money mostly stateside and likely will continue to do so.

Changes at Berkshire are inevitable, though—and not just because the 94-year-old is nearing the end of his remarkable career. Buffett hasn’t hesitated to return cash to shareholders, almost exclusively through stock buybacks, yet he clearly deems even his own stock too pricey for that.

Berkshire also has reached a size at which it can’t replicate its long-run record of deploying its profits and handily beating the market. It is going to have to hand money back somehow—probably through a dividend, reckons Mead. Eventually it becomes necessary to interrupt compounding.

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.

Does Warren Buffett Know Something That We Don’t?

Berkshire Hathaway is hoarding cash in a pattern seen before the financial crisis, but it has a new reason this time

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

Playing a different game

Overlooked