Washing Out Our Future Leaders in the Name of False AI

There is a word for what is happening to the tech workforce right now. The industry prefers to call it transformation. The more accurate word is fabrication.

Companies overhired through a decade of cheap money, then spent even more on AI capital expenses, and now need to lay people off. Rather than face shareholders and admit they wasted money on excess hires, they promote the idea that AI is replacing junior workers, that the workforce is being optimized for the future, and that all of this is inevitable and even exciting. It borders on a coordinated lie of omission. Meanwhile, junior and mid-level engineers pay the price as their careers become collateral damage in a financial cleanup.

This piece traces how we got here, why the narrative doesn't hold up, and what is already starting to crack. We've already written about what this same mistake costs crypto firms specifically. This is the wider story: the lie underneath the entire wave.

The hiring boom had nothing to do with what AI is taking credit for

The automation tools arrived early. IFTTT launched in 2010. Zapier followed in 2011, born out of Y Combinator. Airtable, Bubble, and no-code platforms of every kind spread through the 2010s. By the middle of the decade, a smart non-coder could wire together a dozen APIs and automate what used to be a junior role's daily work. The tools were there. And companies were still aggressively hiring the entire time. The two ran in parallel.

That parallel matters because it destroys the narrative. If automation were the real driver of job cuts, the hiring boom never would have happened. What actually drove the boom was the zero-interest-rate policy, ZIRP, which ran roughly from 2008 through 2021. Cheap capital flooded into tech. Venture money flowed without constraint. Some companies nearly doubled their headcount between 2019 and 2022. Google grew from 24,400 employees in 2010 to more than 182,000 by 2023. Meta peaked at 87,300 in 2022, a 28% increase in a single year. Microsoft, Alphabet, and Facebook all saw headcount rise by more than 20% year over year at their peaks.

None of it reflected fundamental demand for that many engineers. It was cheap capital chasing growth narratives. The same dynamic that built WeWork built the tech hiring boom. When rates rose, the logic collapsed.

Marc Andreessen put it plainly in a March 2026 interview: “Essentially, every large company is overstaffed. It's at least 25% overstaffed. I think most large companies are overstaffed by 50%. I think a lot of them are overstaffed by 75%.” He attributed the real cause directly: zero interest rates during COVID, combined with the complete loss of hiring discipline when companies went virtual.

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Now they all have the silver bullet excuse: Ah, it's AI.Marc Andreessen, March 2026

The capex switch and who is paying for it

When rates rose, capital needed somewhere to go. It went to AI infrastructure. The correlation between the capex explosion and the layoff wave is direct and confirmed.

Combined Big Tech capital expenditure rose from $107 billion in 2020 to $256 billion in 2024, growing at an average annual rate of 72% since Q2 2023. Amazon, Microsoft, Alphabet, and Meta have committed approximately $700 billion to capital expenditure in 2026 alone, nearly double 2025 levels, most of it directed at AI compute, data centers, and networking. By late May, tech layoffs had reached 142,000. Meta's internal communications described its May 2026 layoffs explicitly as enabling the company to offset the cost of AI investments. The company's free cash flow is projected to fall from $43.6 billion in 2025 to $8.5 billion in 2026 as AI capex absorbs operating cash. Meta is now spending roughly $315 to $370 million per day on infrastructure.

The mechanism is not subtle. Capex must be funded. Junior and mid-level engineers are the narrative cover for most of it.

The mechanism: cheap money builds the headcount, the capex pivot needs it gone, and AI takes the blame.

Oxford Economics concluded that firms “don't appear to be replacing workers with AI on a significant scale,” adding that attributing cuts to AI “conveys a more positive message to investors” than citing weak demand or past overhiring. Deutsche Bank analysts wrote in January 2026 that “AI redundancy washing will be a significant feature of 2026.” According to Challenger, Gray & Christmas, AI was cited in only 4.5% of total layoffs in 2025, fifth on the list behind market conditions, restructuring, closures, and plain cost-cutting.

OpenAI CEO Sam Altman acknowledged the same thing from the inside.

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Almost every company that does layoffs is blaming AI, whether or not it really is about AI.Sam Altman, May 2026

The market is drinking the Kool-Aid

The broader financial context makes this more alarming, not less.

The S&P 500's technology sector weighting has reached a record 34 to 36%, surpassing the previous peak set in 2000. The top 10 companies now account for nearly 41% of the entire index's weight, up from a stable 18 to 23% between 1990 and 2015. The Shiller CAPE ratio has reached 39 to 42, a level last seen just before the dot-com crash. Five tech stocks account for nearly half the index's total returns.

Three companies are now preparing IPOs with combined valuations approaching $3 trillion. SpaceX is targeting a valuation of $1.8 to $2 trillion. OpenAI is heading toward $852 billion. Anthropic closed a $65 billion Series H at a $965 billion post-money valuation. Michael Burry observed in a May 2026 post that, adjusted for inflation, just these three IPOs could raise as much capital as roughly 300 internet and technology IPOs did during the entire dot-com boom of 2000. His point was not that these companies are worthless. The internet changed the world. So might AI. His point was about price and timing: the market's concentration of hype and capital has become extreme.

The dot-com bubble was also built around a real technological revolution. Investors just priced it too aggressively before the economics were proven. We have been here before.

The agents are not ready

The lie inside the narrative is not just about the layoffs. It is about what AI can actually do.

AI agents are everywhere in corporate decks and keynote speeches in 2026. In production, they remain unreliable, brittle, and heavily dependent on human supervision. They are not autonomous employees. As one widely cited analysis put it, they are closer to junior staffers who work quickly, confidently, and often incorrectly, requiring constant review and cleanup.

Productivity growth has not accelerated in any way consistent with widespread labor replacement. The gap between the demo and the deployment is still wide enough to drive a truck through.

Which raises the question nobody asking CEOs to justify these cuts seems to want to ask: who guides and aligns these agents going forward? Who learns this technology deeply enough to become a future leader in it? The senior architects that companies are currently paying $270,000 to $300,000 to acquire? The ones they are already struggling to hire? The ones whose pipelines they are actively draining by eliminating the juniors who would have become them?

The industry is betting that Bryan Johnson will keep its senior engineers alive forever. The math does not work.

The cracks are already showing

The bills are starting to come due.

Uber encouraged its staff to use AI tools as aggressively as possible, ranking internal usage on leaderboards. The company's CTO revealed in April 2026 that Uber had blown through its entire annual AI budget in four months. Uber has since instituted a $1,500 monthly cap per employee on agentic coding tools. “AI ROI has so far remained a largely theoretical phenomenon that everybody hopes will eventually materialize,” TechCrunch noted.

Klarna is the case study. Between 2022 and 2024, the Swedish fintech eliminated approximately 700 positions, partnered with OpenAI, and declared publicly that “AI can already do all of the jobs that we, as humans, do.” The company celebrated $10 million in savings. By 2025, it was quietly rehiring human staff. CEO Sebastian Siemiatkowski admitted: “Cost, unfortunately, seems to have been a too predominant evaluation factor. What you end up having is lower quality.” Over half of UK business leaders who rushed to replace human jobs with AI now say they regret it.

IBM is tripling entry-level hiring in the US in 2026, explicitly arguing that younger workers are a better investment during technological upheaval. IBM's own CHRO acknowledged internally that displacing entry-level workers would create a shortage of middle managers down the line, endangering the company's leadership pipeline. Companies that eliminated junior roles in 2023 and 2024 are already reporting difficulty staffing senior positions as their existing senior talent ages out.

The industry has seen this pattern before. The hiring freeze after the 2008 financial crisis created a gap in the experience curve. By 2012, companies struggled to find engineers with three to five years of experience because so few had been hired as juniors during the freeze. The market corrected. This time the correction is priced at high rates and a far larger training bill. Do the math: who pays for it when capex has been drained to zero on AI builds?

The seed corn problem

There is an old idea in farming. You open the canopy, cut the small trees, and the coffee improves. In the short term, yields rise. The sun gets in, filtered perfectly to produce the best coffee. But in the long run, there are no small trees left to grow into the canopy that protects and produces the best crop. The cycle breaks.

The tech industry is eating its seed corn. The junior engineers being cut today are not just filling entry-level roles. They are the mid-levels of 2027 and the seniors of 2030. They are the people who will understand this new technology in depth, beyond what can be learned from documentation. They are the ones who will guide the agents, detect hallucinations, build verification layers, and eventually architect the systems that the next generation of products runs on. It takes time to grow that, and the window to start is now, not after the correction forces everyone to be honest.

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You cannot hire for that experience later. You grow it.

Cutting juniors and mid-levels to fund a capex cycle and calling it AI innovation is not a strategy. It is a short-term balance sheet move dressed up in a narrative that investors have not yet decided to challenge. When they do, and the Klarna precedent suggests the timeline is shorter than the boardrooms think, the companies that kept building their pipeline through the hype will be the ones positioned to move.

Turbin3 is building the pipeline anyway

The developers who survive this cycle with real skills will be the ones who did not wait for the narrative to catch up to reality.

The data is already pointing in one direction. Companies that cut their junior pipeline in 2023 and 2024 are reporting difficulty staffing senior roles today. The experience curve does not pause because the market decided it was inconvenient. The engineers who will guide, align, and verify AI systems in production need to have built something real first. There is no shortcut around that.

The SVM and blockchain space compounds this further. AI tools are structurally undertrained on SVM-specific patterns. The depth required to build production-grade programs on Solana, to work with Token-2022 extensions, to understand the low-level internals that institutional clients are now paying for: that depth does not come from a model. It comes from reps. From building, breaking, and rebuilding real programs under real constraints.

Turbin3 has been building that pipeline through the hype and through the cuts. The Builders Cohort is where high-performing developers enter the stack: production-grade Solana programs, real capstones, the hands-on context that compressed junior employment used to take years to accumulate. Accelerated Builders is where fundamentals become depth. The SVM, Pinocchio, and AI Agent cohorts are where depth becomes the kind of technical leadership the market will need when the correction forces everyone to be honest about what AI can and cannot do.

The window will open. The engineers who used this period to go deep will be the ones standing in front of it.

References

1. Pragmatic Engineer: The End of 0% Interest Rates, June 2024
2. Axios: The Hard Questions Raised by the ZIRP Era, Feb 2024
3. Taskade: Automation History Timeline
4. SurgeGraph: Google Employee Count, Jan 2025
5. SQ Magazine: Meta Employee Count, Sep 2025