Why America Became Obsessed with "Learn to Code"—And Where That Strategy Went Wrong
Written by Massa Medi
For over a decade, “Learn to Code” dominated American education and career advice, sparking a computer science gold rush at elite universities and fueling a bootcamp bonanza. Yet, as the dust settles, troubling trends emerge: layoffs, degree inflation, overwhelmed students, and fewer actual jobs. What sparked this boom in computer science, why did it spiral out of control, and what does this teach us about the future of tech careers—and the myths we tell ourselves?
The 1,000% Surge: Computer Science Mania at America's Top Universities
Picture this: between 2011 and 2021, UC Berkeley witnessed a staggering 1,106% increase in computer science graduates. At this breakneck pace, one CS professor estimated that all 30,000 Berkeley undergraduates could be coding away within just seven years. If you extend this out far enough, by 2059 the institution could theoretically be producing more computer scientists than there are people in California.
Berkeley isn’t even the reigning champion of coding obsession. Take a tour around American academia and you’ll find even more dramatic numbers. At MIT—home to the birth of radar, spreadsheet software, and the lithium-ion battery—nearly 40% of all undergraduates major in computer science. For context, just seven students graduated with a Bachelor of Science in Chemistry last year. In contrast, 266 graduated in computer science and engineering, and more than twice as many completed the broader electrical engineering and computer science major.
The upshot? In just 15 years, American colleges shifted from offering a smorgasbord of majors to becoming Microsoft and Google training grounds, squeezing in a little philosophy and physics on the side. In 2023, Berkeley followed the lead of MIT and Cornell by launching a dedicated College of Computing—their first new school since Dwight Eisenhower was in the White House.
Silicon Valley Dreams: How Coding Became America’s “Golden Ticket”
How did we get here? The roots go back to the cultural and economic wave triggered by the launch of the iPhone in 2007, soon followed by tech juggernauts like Uber, Airbnb, and Instagram. Suddenly, Silicon Valley’s garages replaced Wall Street boardrooms as the nation’s power centers. TV and cinema, with hits like The Social Network and Silicon Valley, mythologized the tech founder, casting them as the 21st century’s answer to yesterday’s industrial tycoons: more meritocratic, more visionary, definitely more eccentric.
Then, the nation’s leaders officially declared coding the career path of the future. President Obama hailed coding as a ticket to the middle class, launched Computer Science Education Week, and promoted “Hour of Code.” Warnings of a coming "shortfall of 1 million STEM graduates by 2022" became gospel. Even New York Mayor Michael Bloomberg famously pledged in 2012 to learn to code himself—though, for the record, nobody has evidence that he actually did.
“Learn to code,” the era’s mantra, offered something for everyone:
- Republicans saw it as practical, vocational education.
- Corporations glimpsed a pipeline of cheap, pre-trained labor.
- National security hawks rallied behind its potential to keep America globally competitive.
- Diversity advocates pitched it as a way to expand opportunity.
- For Democrats engineering the post-recession recovery, it sounded hopeful and conveniently vague—ready to absorb complex questions about globalization and job losses.
The media echoed: “Learn to code.” Suddenly, computer science classes were as common as calculus—offered in nearly 15,000 high schools and 37% of all middle schools. Eleven states now require every student to take a CS class to graduate.
The Coding Mirage: What Rom-Coms, Politicians, and Pop Culture Got Wrong
So persuasive was this narrative that few questioned it. Media profiles declared “anyone can become a computer scientist with a little hard work.” President Biden put it bluntly: “Anybody who can throw coal into a furnace can learn how to program, for God’s sake.” One 2012 article, published while U.S. unemployment soared above 8%, promised anxious job seekers not just a new job, but a fun one—“more like architecture than mathematics.”
No wonder an entire generation—older Gen Z, younger millennials—flocked to CS degrees and coding bootcamps, especially after watching their siblings struggle through the Great Recession. The siren song was irresistible: six-figure jobs! Hoodies instead of suits! The freedom to work from a beanbag rather than a cubicle.
Colleges and Bootcamps Buckle: The Cracks Beneath the Coding Boom
Yet, for all of Big Tech’s readiness to soak up new talent, America’s universities were blindsided. Fads in college majors are nothing new—law schools booming after TV dramas, pharmacy’s spike amid a pharmacist shortage—but nothing matched the scale or speed of the CS explosion. Within a decade, undergraduate enrollments tripled. But the number of new PhDs—needed to teach the rapidly swelling undergraduate classes—remained flat. Why? Put simply, the money wasn’t there: a CS PhD student could fetch $40,000 a year, maybe, compared to $200,000 or more at Amazon or Netflix.
The outcome: impersonal, factory-like department cultures. Professors stretched past their limits, classes ballooning to 400, even 600 students. Peer teaching exploded; the only person you could turn to might be another undergrad who'd just survived the same grind last semester. Some universities, desperate to control the flood, made applicants re-apply to CS programs mid-degree, or, like at Swarthmore, University of Maryland, and UCSD, used pure lottery systems—paying over $90,000 in tuition, only to be denied, by the roll of electronic dice, your preferred major.
The result? Many students graduated disillusioned and in debt, with scant career support, minimal faculty interaction, and often only a shallow grasp of practical programming. Most programs focused on foundational algorithms and theoretical constructs, spread across a dozen languages but mastering none—hardly ideal for landing a modern tech job hungry for specific frameworks and hands-on skills.
Bootcamp Hype and Reality: A Short-Cut With Hidden Costs
Predictably, Silicon Valley’s disruptors sniffed an opportunity. Why wade through four years of general education when bootcamps, for $10,000 to $30,000, could promise a six-figure salary after just twelve weeks? Bootcamps pitched themselves with the promise of “tech interview prep,” churning out grads at half the rate of four-year CS programs and vacuuming up over $200 million per year at their peak.
But as their numbers swelled, bootcamps confronted painful realities. First, student reputations became a double-edged sword—if a graduate floundered or got fired, it hurt future alumni job prospects. Only the best applicants were accepted, with some bootcamps boasting Harvard-level selectivity (Hack Reactor’s acceptance rate? Just 3%). Teacher shortages loomed, salaries couldn’t match industry, and—mirroring academia—bootcamps hired their own recent grads, further inflating employment statistics.
Prices rose. Desperate for funding, they eyed federally-backed student loans but, lacking accreditation, couldn’t qualify—until a Department of Education loophole in 2011. Through partnerships with universities and “online program managers” (OPMs), bootcamps could court students under prestigious academic brands, take a 40% revenue cut, and gain access to government financial aid.
Ironically, in their rush to disrupt academia, bootcamps became just as bureaucratic and unwieldy as the colleges they aimed to replace—and, eventually, were absorbed by the very universities they sought to out-innovate.
The Crash: Tech Layoffs and the Limits of “Learn to Code”
All of this seemed to "work" while tech growth soared, but as the pandemic waned and the industry cooled, the bubble burst. In 2023, nearly half a million tech workers lost their jobs. In both 2022 and again in 2024, another quarter-million layoffs followed. That’s as many jobs as vanished in America’s much-lamented China manufacturing shock.
Suddenly, tech’s unemployment rate outpaced the national average. New graduates had offers canceled. Professors at elite programs like Berkeley reported that even their best students struggled to find jobs. Bootcamps fared worse: 2U filed for bankruptcy, Launch Academy “paused” enrollment, and Dev Bootcamp (acquired by Kaplan) shuttered for good.
For perspective, the U.S. has fewer software developers employed today than it did six years ago. We were warned there would be a shortfall of a million STEM jobs—somehow, we got the opposite. What happened? The answer isn’t complicated: supply and demand. UC Berkeley’s 1,000% growth couldn’t have been sustainable. “Learn to code” didn’t cause the tech downturn (interest rates and investment trends played a huge part), but it did flood the market, making programmers more dispensable, easier to hire and fire in cycles.
The Bureau of Labor Statistics predicts 11% growth for the sector by 2033, but that’s cold comfort to the “starry-eyed” students who bought into the limitless promise of tech. “Learn to code” became an article of faith—an all-purpose solution, unmoored from economic reality.
Coding Is Not Reading or Writing: The Dangerous Myth of Universality
At its peak, “Learn to code” was presented as the new literacy. Some thought every American, from teachers to electricians to nurses, would soon be programming daily. That premise, if accepted, made a 1,000% surge in CS grads seem logical. But tech remains a niche career—only about 2.3% of the U.S. workforce even with generous estimates—far less than the 7 million unemployed “Learn to code” was supposed to save.
Even in a world building ever-smarter AI and endless apps, someone still has to manufacture keyboards, fix broadband, and manage all the offline infrastructure that digital transformation overlooks. Worse, tech is volatile—AI today, some new disruption tomorrow. This generation’s endless tech boom was an anomaly, not a guarantee.
Real Skills, Real People: Coding Isn’t for Everyone
Beyond economics, “Learn to code” ignored a simple truth: human variety. Some people thrive at complex problem-solving under pressure—many simply don’t, or don’t want to. Not everyone wants to sit in front of a monitor, or collaborate on Scrum boards, or hack away into the night. If you swapped in any other job—welding, nursing, epidemiology—the absurdity becomes clear. The soundbite was seductive, but in practice exploitative: it boiled everyone down to interchangeable labor, promising that anyone—from a single parent working two jobs, to a layoff survivor, to a privileged 18-year-old—could emerge as a six-figure developer after 12 weeks.
Reality was much harsher. Single parents found no support for their needs in high-intensity bootcamps. Contractors and other career-changers were told coding was “so easy” only to struggle, internalizing blame for not catching up with classmates who already had a head start. Many graduates found only a $20,000 debt, lost wages, and a resume line that—far from impressing future employers—worked against them. Some did find success, only to be laid off in the next contraction, disposable regardless of their effort or credentials.
What Actually Matters: Adaptability, Not Trends
“Learn to code” was never a magic fix for economic insecurity. Just as “learn to service wind turbines” or “learn occupational therapy”—fields projected to grow much faster than software—coding is simply one of many good careers. Labor markets are fickle; everyone is subject to their tides. The best strategy? Diversify your skills, emphasize adaptability, and invest in timeless abilities like problem-solving and creative thinking.
That’s why educational tools like Brilliant (today’s sponsor) are so valuable: they go beyond Python or JavaScript syntax and help you sharpen real-world, high-level thinking, fostering strategies that last well beyond the lifespan of any single programming language. Their engaging, interactive courses—from logic puzzles and data analysis to scientific thinking—aim to nurture your most versatile asset: curiosity and critical reasoning.
If you want to try Brilliant for free for 30 days (and get 20% off a premium annual subscription), check out the link at brilliant.org. Explore what truly interests you, and focus on skills that will endure no matter where the labor market swings next.
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