The “Learn to Code” movement in the early 2010s encouraged people to learn computer programming in an economy increasingly reliant on technology. Many students chose computer science majors and workers enrolled in coding bootcamps, all because they were sold on the idea that it provided a stable future. This was fueled by the rapid growth of technology companies and their demand for software engineers.
For two decades, Learn to Code reflected the needs of capital. But when in crisis, capital seeks new avenues for profit. What was once touted as one of the best careers to pursue, now has some of the highest unemployment rates while tech companies are making record-breaking profits. “Learn to Code” reminds us that labor does not move independently of capital. As the industry is shifting, we are seeing the end of “Learn to Code.”
From Dot-Com Dreams to Big Tech
To understand how AI is reshaping the tech sector, we must trace the rise of the modern tech economy. The internet wasn’t always refined or seamlessly woven into all aspects of daily life. It was noisy, slow, and scattered with primitive websites. The internet was a strange, digital wilderness where every new website promised to change the world. This new technological breakthrough had yet to reach its full commercial potential.
The commercialization of the internet in the 90s created enormous opportunities for investors. Venture capitalists invested enormous amounts of capital for stakes in small companies that they speculated to be worth billions. This longstanding view postponed short-term profits for the opportunity to reap massive returns in the long term. Venture capitalists wrote million dollar checks to founders with nothing more than an idea, a domain name, and a give ‘em hell attitude.
Investors continued to pour money into these companies with the expectation that their rapid growth would lead to profits. However, as these heavily-funded companies failed to generate sufficient revenue, investor confidence began to dwindle. As optimism faded, a bearish investment outlook emerged and investors pulled out, ultimately leading to the burst of the dot-com bubble. The tech-heavy Nasdaq Composite Index lost nearly 80 percent of its value from its peak.
The crash taught investors that speculation alone couldn’t build a lucrative company. The next boom would require something different: companies that could actually make money. The ones that survived, which would later become the tech giants that we know today, did so by solving discernible problems. Amazon made buying goods online more convenient. Google made all the websites searchable and generated revenue serving ads. Apple made the devices millions of Americans carry in their pocket. In doing so, they quietly built the foundations of the modern digital economy. Meanwhile, high-speed broadband internet replaced dial-up, search engines became fundamental, and smartphones became extensions of ourselves. The internet evolved from a technological novelty into an essential part of our everyday lives.
By the mid-2000s, the economy had mostly recovered from the dot-com crash. The low interest rates meant to counter the dot-com bust fueled a new bubble. Not in tech, but in housing. Banks handed out mortgages with extreme ease, if you had a pulse you could probably qualify for a loan. The incentive is clear: the more loans issued, particularly higher-interest loans given to “riskier” borrowers, the more revenue is generated for banks. But what borrowers hadn’t expected was that home prices would stop rising. As prices plateaued, precarious borrowers were unable to refinance their mortgages. As “teaser” interest rates started to expire and the full high-interest mortgage became due, borrowers began to default altogether.
Millions of people lost their homes to foreclosure, unemployment grew, and a global recession followed. To mitigate the effects, the Federal Reserve, again, reduced interest rates to nearly zero to stimulate the economy and encourage investors to reinvest in new businesses. This ultimately set the stage for the massive tech boom as cheap capital flooded the tech sector. The dot-com crash exposed the contradictions of speculative capitalism. The 2008 financial crisis exposed the instability of an economy driven by profit. As capital searched for new sources of revenue, technology became its new frontier. Together, they laid the foundation for the rise of Big Tech.
The Age of Big Tech
In the mid-2000s there was a massive influx of capital into the tech sector. Technology companies expanded at an impressive pace. With that, companies hired aggressively and software engineering became the golden opportunity that promised a high payout right out of college. Young developers working on beanbags, playing ping-pong, and eating endless snacks became the defining image of Silicon Valley. Behind this image, they were building software that would affect billions of people and generate massive profits for investors. This is where “learn to code” was coined.
“Learn to Code” was a series of campaigns that promoted the development of computer programming skills. It aimed to emphasize the importance of programming in a tech-driven economy. It wasn’t just career advice, it symbolized a broader shift in how labor was expected to respond to economic change. As manufacturing declined, globalization expanded, and automation took over, masses were left unemployed in the changing economy. “Learn to Code” was advertised as a golden ticket to a comfortable middle-class life. Rather than confronting the structural causes of stagnant wages or the increasing economic precarity, workers were encouraged to retrain and adapt to the changing demands of the labor market as the solution to their financial insecurity.
The demand for software engineers was observed through an excessive hiring campaign. Computer-related fields accounted for a majority of the fastest growing fields throughout the 2000s. Companies continued to hire at increased rates up until 2021. Cheap capital disappeared as interest rates rose with inflation. Investors began demanding higher revenues and profits. Their priorities changed. Companies went from asking, “How fast and far can we grow?” to “How can we grow with fewer people?” Mass layoffs and hiring slowdowns in the tech sector have increased significantly throughout the last few years, meanwhile Big Tech has made record profits.
Then in late 2022, AI entered the mainstream. Almost overnight it became the answer to every question. It entered at a time when venture capital was slowing down. The largest companies have already captured much of the digital economy. There’s a smartphone in everyone’s hand, search engines and social media have become a fundamental part of people’s lives. The market has become saturated. The rapid growth that occurred in previous years was getting progressively harder to sustain. If revenue could no longer grow at the pace it once had, maintaining profits meant looking elsewhere. One option was to reduce the cost of production.
Labor is one of the largest expenses in tech, and engineers represent a significant share of that cost. This does not mean companies suddenly don’t need engineers. Still, tech companies face more pressure to produce more with fewer people. Long before AI was integrated into the labor sector, companies were already seeking higher productivity from a leaner workforce. The shift from “Learn to Code” to “prompt AI to write the code for you” reflects a much greater transformation.
For a generation of workers, software engineering was presented as a lucrative career path that provided financial security. And for a time, it did. High salaries and good benefits created a false sense of isolation from the economic instability affecting other workers. But as revenue has begun to plateau, the same workers who were once encouraged and rewarded in a tech driven economy now face the harsh reality of the current crisis of capitalism. Layoffs and pushes towards automation show that “highly skilled” workers are not independent of the forces that shape the broader working class. Their lives are still determined by the decisions of the capitalist class and their endless pursuit of profit.
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