The Generosity Power Move That Can Boost Your Career
To get ahead, learn how to be a connector
To get ahead, learn how to be a connector
Connectors always know just who you should talk to. They send the perfect introductory emails: warm, crisp, direct. And they make it look so effortless.
“It’s almost like music or something,” says David Dewane, a Chicago architect who loves introducing contacts from all parts of his life. “If you do it right, what you get is a little flash of possibility for both people.”
And possibility for the connector, too. Call it karma, the power of networks , or even just luck . If you become that hub for your friends and colleagues, it will come back to you, enriching your circles.
I think of people I know in my own life, the ones I speed text when I need a doctor for my kid. I feel so grateful, like they’re these life buoys that help keep me afloat. I wonder: Can the rest of us do that?
“We all develop a point at which the network that we’re in can’t satisfy our needs anymore,” says Brian Uzzi, a professor at Northwestern’s Kellogg School of Management who studies social network science.
When we become brokers, dipping in and out of various groups, we have access to all kinds of new information: little tips, fresh opportunities. Synthesizing multiple viewpoints, we’re better able to solve problems in innovative ways, Uzzi says. People love us for it.
Connectors are more likely to get promoted and win bigger bonuses , Uzzi says. In one study of M.B.A. students, those who acted as brokers between cliques were twice as likely to get the best job offers upon graduating, he adds.
The key is to give before you ask.
“The idea of reciprocity is very powerful,” says Greg Pryor, a longtime human-resources executive who now researches organizational psychology topics.
Need a favor while you’re building a relationship, and you’re automatically in debt, he says. Instead, his career has been guided by a pay-it-forward mentality. He ends most calls by asking, “Is there anything I can do to help you?”
One time, a colleague asked if Pryor could get an acquaintance of hers up to speed on the topic of corporate culture and values. He spent a day with the friend-of-a-friend and connected her to others in the industry he thought could help.
The woman ended up becoming the chief human resources officer at software company Workday. When Pryor was looking for his next job, he reached out to her. A few weeks later, he was the new head of talent at Workday.
He spent a decade there, the best stretch of his career, he says.
There’s an art to crafting the perfect email intro. Dewane, the Chicago architect who’s orchestrated thousands of introductions, is constantly scanning his mental Rolodex for pairs of contacts who can solve each other’s problems. He usually gets preapproval to reach out from both parties, then turns to his formula.
There’s two paragraphs—one for each person. He describes what they do, why he thought of them, and how they’re perfect to connect on this particular thing. He includes hyperlinks to both LinkedIn profiles. And he always puts the person who stands to gain more from the interaction last, queuing them up to initiate contact.
“I get kind of paranoid if intros just hang there,” he says.
If there’s a big difference in power between the two people, he choreographs the thread even more intricately. When connecting architecture students with professionals he knows at design studios, he’ll inform the students that he’s sending the email at 8 a.m. They are to reply by 8:04 a.m.
“I am going to open the door and then you are going to walk through it,” he says.
Oftentimes people freeze as they sit down to pen an email, scared of overpromising, says Erica Dhawan, a St. Petersburg, Fla.-based leadership consultant and author of a book about digital communication. Sliding into someone’s inbox involves risk. You’re encroaching on their time and looping yourself to two disparate contacts who may or may not hit it off.
Dhawan recommends using the phrase, “no guilt, no obligation,” when asking people if they’re open to connecting.
“I want them to feel like there’s mutual benefit,” she says, not like they’re doing her a favor.
Being on the receiving end of an introduction can also leave your stomach in knots, if it’s not done right.
“I’m in an email thread and I’m like, I don’t know why I’m here,” says Khaled Bashir, the founder of a marketing agency and AI startup in Toronto. “What am I supposed to do?”
Fellow founders will often connect him with potential clients. At least he thinks that’s what they are. The context is sometimes missing, and he’d appreciate a funny icebreaker so he can slide into the conversation without it having to be all business.
Bad intros can have happy endings, though.
Years back, Bashir was thrown into a random WhatsApp group by a client. No explanation, just him and one other guy. It turned out the other person was a fellow agency owner. The pair became fast friends. They bonded over the synergies in their work and a love of Japanese comics. Now, Bashir is selling the marketing part of his business to the friend, a move that will let him focus on growing his AI offerings.
To make connections less awkward, add food. Michael Magdelinskas, who works in government affairs for a consulting firm, hosts frequent dinner parties at his Manhattan apartment. Over sous-vide pork chops and cognac ice cream, he brings together everyone from former colleagues to acquaintances visiting from overseas.
He crafts guest lists by thinking about common hobbies, hometowns and the ratio of introverts to extroverts. Recently, a group of attendees formed their own Instagram chat thread, bonding over an inside joke. They didn’t even think to include Magdelinskas.
“That’s a good thing,” he says. “That means the process is working.”
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
A 30-metre masterpiece unveiled in Monaco brings Lamborghini’s supercar drama to the high seas, powered by 7,600 horsepower and unmistakable Italian design.
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
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.
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.”
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.
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