Monday Myth: Everyone Can Have a Dream Job in IT

For more than two decades, the technology industry has sold one of the most seductive narratives in modern economic life.

Learn to code. Join a start-up. Work from anywhere. Change the world. Accumulate stock options. Retire early.

The message implied that software offered an almost guaranteed path to meaningful work, personal freedom, and financial success.

For a fortunate minority, that promise materialised.

For many others, the reality proved far less glamorous.

The dream often gave way to fragile organisations, inflated titles, repeated reorganisations, and a persistent feeling that much of the industry had drifted away from engineering and towards theatre.

The Myth

Anyone can build a dream career in IT.

With sufficient enthusiasm, a few certificates, and the right employer, meaningful work and prosperity will naturally follow.

The Reality

The most rewarding careers in technology remain possible, but they have become increasingly rare.

Large parts of the industry now operate on hype, financial engineering, and fashionable narratives rather than on the disciplined industrialisation of software.

When Computing Attracted Engineers

The early decades of computing drew heavily from mathematics, physics, and electrical engineering.

Pioneers such as Alan Turing, Claude Shannon, John von Neumann, and Grace Hopper approached computing with scientific rigour.

They worked under severe constraints. Memory measured in kilobytes, processors ran at modest frequencies, and failures carried tangible consequences. Every design choice demanded precision.

Software emerged as an engineering discipline rooted in logic, discipline, and respect for reality.

Cheap Money and the Gold Rush Illusion

For much of the period between the global financial crisis of 2008 and the inflation shock of 2022, historically low interest rates flooded the market with inexpensive capital.

Money that once required disciplined allocation became abundant. Investors searched aggressively for yield, and technology absorbed a disproportionate share of that capital.

Under these conditions, companies could postpone reality for surprisingly long periods. Losses appeared acceptable. Unit economics received less scrutiny. Headcount expanded rapidly. Growth itself became a substitute for proof.

The resulting dynamic resembled a modern gold rush.

A few prospectors found extraordinary fortunes. Their stories travelled around the world and inspired millions to join the search. Yet, as in every gold rush, the overwhelming majority never struck gold.

Some earned a respectable living. Many worked long hours in uncertain conditions. Thousands disappeared quietly, leaving little behind except investor decks, obsolete code bases, and fading employer brands.

The mythology of the dream job in IT emerged from this environment. It relied heavily on survivorship bias, highlighting the rare successes while concealing the statistical norm.

The Great Narrative Expansion

As capital flooded into the sector, the industry changed.

Technology remained transformative, but a parallel ecosystem emerged in which storytelling often outpaced substance. Valuations rose on expectations rather than proven economics. Titles expanded faster than responsibilities. Organisations promised to disrupt entire industries while struggling to deploy reliable software.

The term "unicorn" captured the imagination of a generation. In practice, it also encouraged the belief that extraordinary valuations represented operational excellence.

The underlying statistics tell a more sobering story. Numerous studies suggest that around 90 percent of start-ups fail, and even venture-backed companies face high attrition rates. The rise and subsequent collapse of companies such as Frontier Car Group, once celebrated as high-growth success stories, illustrate how impressive valuations and ambitious narratives can conceal fragile fundamentals. History offers many other examples, from the spectacular implosion of WeWork to the disappearance of hundreds of heavily funded start-ups that briefly appeared destined to reshape entire industries.

The mythology persisted because a handful of spectacular successes such as Amazon, Google, Netflix, and Meta obscured the quiet disappearance of thousands of forgotten ventures.

The lesson extends beyond start-ups. Even in a winner-take-most industry, only a small number of companies combine technical excellence, operational discipline, and genuine economic durability. The visible winners became the template. Their rarity often went unmentioned.

25 Years of Increasing Fragility

The evidence extends beyond anecdotes.

Research from Accelerate by Nicole Forsgren, Jez Humble, and Gene Kim, together with the annual DORA reports, repeatedly shows that elite software organisations deliver more frequently, recover faster, and maintain lower change failure rates. The uncomfortable implication is that, despite access to cloud computing, automation, and AI-assisted tooling, most organisations still operate far below known best practices.

The broader productivity paradox remains difficult to ignore. The industry accumulated extraordinary tools, yet many teams continue to struggle with lead times measured in weeks or months, brittle deployments, and chronic unpredictability.

We automated the machinery without fully mastering the discipline.

When Everyone Becomes an Engineer

During the same period, software became central to almost every industry.

One might have expected delivery practices to mature along the lines of aerospace, automotive engineering, or medicine.

Instead, many organisations normalised conditions that would appear unacceptable in other engineering disciplines.

The barriers to entry also shifted dramatically. Intensive boot camps and short certification programmes created the impression that a few weeks of training could substitute for years of disciplined practice. Many talented people entered the field, but the industry increasingly treated software engineering as a commodity skill rather than as a craft requiring sustained study, experimentation, and technical depth.

Projects launched without clear ownership. Architectures accumulated layers of accidental complexity. Teams optimised for velocity metrics rather than customer outcomes. Reorganisations multiplied whenever structural problems remained unsolved.

The result was a widening gap between the strategic importance of software and the average level of engineering maturity.

No one expects a bridge to be designed by someone who completed a three-week boot camp. No airline entrusts flight controls to teams guided primarily by slogans. Yet software now underpins hospitals, banks, logistics networks, and governments, often without the professional standards traditionally associated with engineering.

Despite unprecedented tooling, many companies still struggle with the same issues they faced a quarter of a century ago: unclear accountability, unstable priorities, excessive dependencies, chronic reinvention, and an enduring shortage of true engineering craftsmanship.

The paradox remains striking. An industry devoted to automation often fails to industrialise its own production system.

The Financialisation of Technology

At its best, venture capital allocates resources to promising ideas.

At its worst, it can amplify a speculative cycle in which capital, branding, and narrative create the appearance of inevitability long before a durable business exists.

This does not imply criminal intent. It reflects a structural tendency to reward growth stories over operational fundamentals.

The scale of the phenomenon remains considerable. According to CB Insights, 38 percent of start-ups fail because they run out of cash or cannot raise additional funding, while 35 percent fail because no real market need exists. Startup Genome has repeatedly estimated that roughly 70 percent of start-ups scale prematurely, expanding teams and infrastructure before achieving stable product-market fit. Harvard Business School professor Shikhar Ghosh suggested that as many as 75 percent of venture-backed companies fail to return investors' expectations.

Revenue may lag behind valuation. Unit economics may remain fragile. Teams may scale before the product achieves stable adoption.

The history of the sector offers striking examples. WeWork reached a private valuation of 47 billion US dollars in 2019 before its governance and economic weaknesses became public. Frontier Car Group raised hundreds of millions of dollars and operated across emerging markets before ultimately collapsing and being dismantled. Theranos, once valued at 9 billion US dollars, became an emblem of what happens when narrative outruns technical reality.

When capital conditions tighten, the underlying weaknesses surface quickly.

Lay-offs follow. Programmes disappear. Titles evaporate. In 2022 and 2023 alone, hundreds of thousands of technology workers lost their jobs as financing conditions changed and companies reassessed growth assumptions.

Engineers who believed they had joined the future sometimes discover that they were supporting a story rather than a system.

Post-Modern Management

The industry also absorbed a growing number of management fashions.

Some brought useful insights. Others prioritised language over substance.

Organisations increasingly invested in symbolic programmes, elaborate terminology, and moral positioning while neglecting foundational disciplines such as product-market fit, technical excellence, cost control, and operational reliability.

This disconnect matters because businesses survive only when they remain anchored in reality. In practical terms, this usually means one of two things.

The first path involves solving a painful and recurring problem so effectively that customers willingly pay and continue paying. The second involves creating a level of dependency or integration that makes the product operationally difficult to replace. The most durable companies often combine both: they deliver indispensable value while embedding themselves deeply into customer workflows.

When neither condition exists, narratives rarely compensate for weak fundamentals. Growth slows, customer acquisition costs rise, churn increases, and investors eventually question the underlying economics.

The history of technology contains numerous cautionary examples. WeWork expanded globally before proving a sustainable model. Theranos attracted prestigious investors without validating its core technology. Quibi raised nearly 2 billion US dollars and shut down within months of launch. Jawbone, once valued at more than 3 billion US dollars, collapsed under operational and competitive pressure. Frontier Car Group assembled an impressive international footprint yet ultimately failed to convert scale into a durable business.

In such environments, discussing values becomes easier than confronting defects.

The result often resembles a post-modern organisation: rich in narratives, poor in structure, and remarkably resistant to objective feedback.

Customers, however, remain indifferent to internal rhetoric.

They reward products that solve real problems reliably, integrate deeply, and operate at a sustainable cost.

Title Inflation and the Human Cost

The dilution of technical depth coincided with a parallel inflation of titles.

Senior Engineer, Staff Engineer, Principal Engineer, Architect, and even CTO increasingly describe roles with vastly different levels of mastery and accountability.

This resembles monetary inflation. As titles become easier to obtain, they lose their signalling power. When everyone carries an elite designation, the designation no longer distinguishes craftsmanship from exposure.

For many professionals, the gap between promise and reality created a profound disillusionment. They entered the field hoping to master a demanding craft and contribute to meaningful systems.

Instead, they encountered cycles of hype, superficial transformations, and organisations that celebrated innovation while tolerating mediocrity.

The dilution of language compounded the problem. The title of "engineer" gradually expanded to encompass roles requiring widely varying levels of technical depth. In many cases, a few weeks of training and a superficial familiarity with frameworks sufficed to secure positions that carried the same designation once reserved for practitioners with years of study and deliberate practice.

This observation does not diminish the intelligence or potential of newcomers. Every profession needs entry points. The difficulty arises when organisations confuse exposure to tools with mastery of engineering principles such as abstraction, systems thinking, reliability, performance, and disciplined problem solving.

Talented engineers consequently spend increasing amounts of time in meetings, navigating politics, and rebuilding the same foundations that previous generations should have standardised, often while mentoring colleagues who received the title without having yet acquired the corresponding mindset.

The emotional toll can prove considerable.

What began as a vocation sometimes deteriorates into a sequence of increasingly polished disappointments.

Why the Dream Still Exists

None of this diminishes the extraordinary potential of software.

Technology continues to reshape medicine, transportation, manufacturing, science, and education.

The most satisfying careers in IT remain deeply rewarding.

They simply tend to emerge in organisations that treat software as engineering rather than performance art.

These companies share recognisable characteristics.

They respect truth. They measure outcomes rather than activity. They invest in craftsmanship. They confront structural problems instead of masking them with slogans.

Most importantly, they understand that durable systems demand discipline.

The Real Dream

The real dream in technology never consisted of beanbags, inflated titles, or paper valuations.

It consisted of building useful systems with capable people, solving meaningful problems, and leaving behind something that worked better because you were there.

Do not chase the myth of effortless success. Seek environments where reality matters, craftsmanship receives respect, and engineering once again resembles engineering.

That dream remains attainable. It simply requires far more discernment than the industry once suggested.

In a world increasingly dominated by narratives, this may constitute the rarest and most rewarding dream job of all.

The dream of IT was real. The mythology surrounding it was not.

Additional Reading

• The Phoenix Project, by Gene Kim, Kevin Behr, and George Spafford.
• Accelerate, by Nicole Forsgren, Jez Humble, and Gene Kim.
• The Lean Startup, by Eric Ries.
• Zero to One, by Peter Thiel and Blake Masters.

Selected References

• Startup Genome, Startup Ecosystem Report.
• CB Insights, Why Startups Fail.
• Shikhar Ghosh, Harvard Business School, research on venture-backed failure rates.
• Martin Campbell-Kelly and William Aspray, Computer: A History of the Information Machine.
• Fred Brooks, The Mythical Man-Month.
• Christophe Dejours, Travail, usure mentale.
• Donella Meadows, Thinking in Systems.
• Christopher Alexander, Notes on the Synthesis of Form.
• Nassim Nicholas Taleb, Antifragile.