• A millennial paid off more than $100,000 in student loan debt in two years by juggling two jobs.
• Secretly working multiple remote jobs allowed him to double his income.
• He said being "overemployed" is stressful at times, but the financial benefits are worth it.

Adam paid off his student loan debt last month, after more than doubling his income by juggling multiple remote jobs.

Two years prior, he had roughly $118,000 in student debt and was earning about $85,000 annually from one job as a security risk professional. Adam, who is in his 40s and based in Arizona, was eager to become debt-free as soon as possible. He started looking for ways to boost his income and discovered "overemployment."

Since early 2023, Adam has secretly juggled two full-time remote roles simultaneously. While his overemployed lifestyle has been stressful at times, he said he typically doesn't work more than 55 hours a week across his gigs — and that the financial benefits have outweighed the downsides.

"I would like to be a millionaire before I turn 50," said Adam, whose identity was verified by Business Insider but asked to use a pseudonym due to fear of professional repercussions. "I want the financial freedom to give more time to family and friends."

Adam is among the Americans who have worked multiple remote roles on the sly to boost their incomes. Over the past two years, BI has interviewed more than two dozen job jugglers who've used their extra earnings to pay off debt and travel the world. To be sure, holding multiple jobs without company approval could have professional repercussions and lead to burnout. But many current and former overemployed workers have told BI the financial benefits outweigh the downsides.

Job juggling is worth the stress

In 2022, Adam began supplementing his income by driving for food delivery platforms like DoorDash. But after growing frustrated by his meager earnings, he decided to explore other options. That same year, he watched a YouTube video about people secretly working multiple jobs to boost their incomes.

When Adam began looking for a second remote gig in early 2023, he said his two main goals were to double his income and pay off his student loans within two years. In February 2023, he landed a second remote security risk professional role that pushed his combined earnings to more than $170,000 annually.

Adam said working multiple jobs has been challenging at times. He said it can be difficult to juggle overlapping meetings and deadlines, and that coordinating vacation time across both jobs can be laborious — as each employer has a different policy and approval process. While he's generally been able to manage his workload, he said it can be difficult when colleagues quit or are out of the office, and he's asked to pick up some extra work.

"Managing priorities and ensuring both roles receive adequate attention requires careful planning and adaptability," he said.

While these challenges have been stressful at times, Adam said he's generally been able to avoid burnout. He tries to stay organized and automate his work wherever possible. Outside work, he makes an effort to spend plenty of time with his friends and family. When he needs a break during the workday, he sometimes plays video games.

"I have learned to manage stress pretty well," he said.

Looking ahead, Adam said he has no plans to stop job juggling. His goal is to boost his combined income to at least $250,000 annually by swapping one of his jobs for a higher-paying one or starting a consulting business on the side.

"I do plan on staying overemployed for the foreseeable future," he said. "The way I am overemployed may change."

Are you working multiple remote jobs at the same time and willing to provide details about your pay and schedule? If so, reach out to this reporter at [email protected].

Last week, a tweet by Stanford researcher Yegor Denisov-Blanch went viral within Silicon Valley. “We have data on the performance of >50k engineers from 100s of companies,” he tweeted. “~9.5% of software engineers do virtually nothing: Ghost Engineers.”

Denisov-Blanch said that tech companies have given his research team access to their internal code repositories (their internal, private Githubs, for example) and, for the last two years, he and his team have been running an algorithm against individual employees’ code. He said that this automated code review shows that nearly 10 percent of employees at the companies analyzed do essentially nothing, and are handsomely compensated for it. There are not many details about how his team’s review algorithm works in a paper about it, but it says that it attempts to answer the same questions a human reviewer might have about any specific segment of code, such as:

• “How difficult is the problem that this commit solves?
• How many hours would it take you to just write the code in this commit assuming you could fully focus on this task?
• How well structured is this source code relative to the previous commits? Quartile within this list
• How maintainable is this commit?”

Ghost Engineers, as determined by his algorithm, perform at less than 10 percent of the median software engineer (as in, they are measured as being 10 times worse/less productive than the median worker).

Denisov-Blanch wrote that tens of thousands of software engineers could be laid off and that companies could save billions of dollars by doing so. “It is insane that ~9.5 percent of software engineers do almost nothing while collecting paychecks,” Denisov-Blanch tweeted. “This unfairly burdens teams, wastes company resources, blocks jobs for others, and limits humanity’s progress. It has to stop.”

The Stanford research has not yet been published in any form outside of a few graphs Denisov-Blanch shared on Twitter. It has not been peer reviewed. But the fact that this sort of analysis is being done at all shows how much tech companies have become focused on the idea of “overemployment,” where people work multiple full-time jobs without the knowledge of their employers and its focus on getting workers to return to the office. Alongside Denisov-Blanch’s project, there has been an incredible amount of investment in worker surveillance tools. (Whether a ~9.5 percent rate of workers not being effective is high is hard to say; it's unclear what percentage of workers overall are ineffective, or what other industry's numbers look like).

Over the weekend, a post on the r/sysadmin subreddit went viral both there and on the r/overemployed subreddit. In that post, a worker said they had just sat through a sales pitch from an unnamed workplace surveillance AI company that purports to give employees “red flags” if their desktop sits idle for “more than 30-60 seconds,” which means “no ‘meaningful’ mouse and keyboard movement,” attempts to create “productivity graph” based on computer behavior, and pits workers against each other based on the time it takes to complete specific tasks. 

What is becoming clear is that companies are becoming obsessed with catching employees who are underperforming or who are functionally doing nothing at all, and, in a job market that has become much tougher for software engineers, are feeling emboldened to deploy new surveillance tactics. 

“In the past, engineers wielded a lot of power at companies. If you lost your engineers or their trust or demotivated the team—companies were scared shitless by this possibility,” Denisov-Blanch told 404 Media in a phone interview. “Companies looked at having 10-15 percent of engineers being unproductive as the cost of doing business.”

Denisov-Blanch and his colleagues published a paper in September outlining an “algorithmic model” for doing code reviews that essentially assess software engineer worker productivity. The paper claims that their algorithmic code assessment model “can estimate coding and implementation time with a high degree of accuracy,” essentially suggesting that it can judge worker performance as well as a human code reviewer can, but much more quickly and cheaply. 

I asked Denisov-Blanch if he thought his algorithm was scooping up people whose work contributions might not be able to be judged by code commits and code analysis alone. He said that he believes the algorithm has controlled for that, and that companies have told him specific workers who should be excluded from analysis because their job responsibilities extend beyond just pushing code. 

“Companies are very interested when we find these people [the ghost engineers] and we run it by them and say ‘it looks like this person is not doing a lot, how does that fit in with their job responsibilities?’” Denisov-Blanch said. “They have to launch a low-key investigation and sometimes they tell us ‘they’re fine,’ and we can exclude them. Other times, they’re very surprised.”

He said that the algorithm they have developed attempts to analyze code quality in addition to simply analyzing the number of commits (or code pushes) an engineer has made, because number of commits is already a well-known performance metric that can easily be gamed by pushing meaningless updates or pushing then reverting updates over and over. “Some people write empty lines of code and do commits that are meaningless,” he said. “You would think this would be caught during the manual review process, but apparently it isn’t. We started this research because there was no good way to use data in a scalable way that’s transparent and objective around your software engineering team.”

Much has been written about the rise of “overemployment” during the pandemic, where workers take on multiple full-time remote jobs and manage to juggle them. Some people have realized that they can do a passable enough job at work in just a few hours a day or less. 

“I have friends who do this. There’s a lot of anecdotal evidence of people doing this for years and getting away with it. Working two, three, four hours a day and now there’s return-to-office mandates and they have to have their butt in a seat in an office for eight hours a day or so,” he said. “That may be where a lot of the friction with the return-to-office movement comes from, this notion that ‘I can’t work two jobs.’ I have friends, I call them at 11 am on a Wednesday and they’re sleeping, literally. I’m like, ‘Whoa, don’t you work in big tech?’ But nobody checks, and they’ve been doing that for years.”

Denisov-Blanch said that, with massive tech layoffs over the last few years and a more difficult job market, it is no longer the case that software engineers can quit or get laid off and get a new job making the same or more money almost immediately. Meta and X have famously done huge rounds of layoffs to its staff, and Elon Musk famously claimed that X didn’t need those employees to keep the company running. When I asked Denisov-Blanch if his algorithm was being used by any companies in Silicon Valley to help inform layoffs, he said: “I can’t specifically comment on whether we were or were not involved in layoffs [at any company] because we’re under strict privacy agreements.”

The company signup page for the research project, however, tells companies that the “benefits of participation” in the project are “Use the results to support decision-making in your organization. Potentially reduce costs. Gain granular visibility into the output of your engineering processes.”

Denisov-Blanch said that he believes “very tactile workplace surveillance, things like looking at keystrokes—people are going to game them, and it creates a low trust environment and a toxic culture.” He said with his research he is “trying to not do surveillance,” but said that he imagines a future where engineers are judged more like salespeople, who get commission or laid off based on performance. 

“Software engineering could be more like this, as long as the thing you’re building is not just counting lines or keystrokes,” he said. “With LLMs and AI, you can make it more meritocratic.”

Denisov-Blanch said he could not name any companies that are part of the study but said that since he posted his thread, “it has really resonated with people,” and that many more companies have reached out to him to sign up within the last few days.