The ‘October Theory’ of Changing Your Life

October is traditionally the time to break out the cozy sweaters and consume as many pumpkin-spice drinks as possible. Instead, people are now using it to reset their goals.

Dubbed “October Theory,” these people are rethinking their approach to the last three months of the year. They’re using it as a time to set goals, pick up new habits and reflect—essentially taking on the role New Year’s plays.

October Theory is the latest “theory” social media has latched onto. Between the uneven job market, inflation, and the usual daily grind, people are looking for something they can control. Setting goals and improving their lives —whether it’s their health, finances or mindset—is something they are gravitating toward.

Sarah Stone, a 35-year-old Realtor in Kansas City, Mo., says October is a better time to reflect on the previous nine months and also home in on what she wants to achieve in the last few months of the year. This month, she’s decluttering her home and purging habits such as too much impulse shopping at TJ Maxx.

“It feels almost like the beginning of the year is in the wrong place on the calendar,” says Stone.

October can feel like an introspective time for people since the seasons are changing, a new academic school year has started and the current year is on its way out, says Laurie Kramer, a licensed clinical psychologist and a professor of applied psychology at Northeastern University. The Jewish new year—Rosh Hashana—also takes place in September or October, giving millions a time to reflect.

“This is a great time, 90 days from the new year, from the holidays, to reassess, see where you are with things,” Kramer says.

Start now, win later

October Theory is catching on partly because it sets someone up for success by the time January rolls around, say fans of the trend. Instead of picking up a new habit in the dead of winter—at the same time everyone else is trying to make it to the gym, for instance—it has already been in place for three months.

Every new year, Allison Bucheleres, a 30-year-old lifestyle and fashion content creator in Miami, tries to set new goals. Often, she fails because she doesn’t have a routine in place to make it happen.

Most of her goals this month revolve around setting new daily routines, such as waking up at 7 a.m., journaling her thoughts and writing self-affirmations to reframe her thinking. Around the middle of the day, she’ll repeat her positive phrases—at times over 100 of them—and will sometimes write one on a sticky note to post on her bathroom mirror.

Bucheleres’s newest self-mantra: “I can control my work and my self belief, but not the timing.”

Simple behaviours that are easy to repeat could take as few as 30 times to become a habit. More complex ones, such as going to the gym, could take up to three months of daily practice, says Wendy Wood, professor emerita of psychology and business at the University of Southern California.

The best time to change behaviour is during a big life change, such as moving to a new house or starting a new job or relationship—regardless of whether it’s in January or October, she says.

“You have a sort of window of opportunity to make decisions about what you want to do without your old habits getting in the way,” Wood says.

Making the most of 2024

Others view October as a last chance to fulfil the goals and aspirations they set months ago.

That includes Mateo Pérez, who is in the final stretch for his weightlifting and running regimen. The 19-year-old sophomore, who is majoring in creative advertising at the University of Miami, is also working on an application to transfer to New York University for the fall 2025 semester. Pérez wants to finish the application by the end of this semester in December.

“Right now, it’s like a reflection of this whole year and how can we make the most of the last three months,” Pérez says.

Psychologists say being introspective—at any time of the year—helps people develop habits and routines. It is often the key to following through on your goals.

Two Octobers ago, Kelly Sites, a 38-year-old customer-support manager and content creator, decided to stop living overseas. By February, she had moved to Kansas City, Mo.

This year, she’s trying to set up a daily meditation and breathing practice, and eat more whole foods. In a TikTok post on Oct. 2, Sites encouraged people to go to their photo albums and type in October to see how much their lives have changed in the 10th month of the year.

“It’s this idea of hibernation, seasons changing,” Sites says. “There’s always seeds of my life that were planted in October that changed the rest of the year.”

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.

The ‘October Theory’ of Changing Your Life

People are using the beginning of fall as the best time to reset their goals and values, inspired by a social-media trend

Start now, win later

Making the most of 2024

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

Playing a different game

Overlooked