For years, I have had numerous opportunities to speak with high schoolers and undergrads about careers in tech, particularly software engineering. As an option, I found a career in tech, if you are into it, could be liberating, engaging, and rewarding, too. Recently, unfortunately, my optimism has been dampened.
While working on a piece of software is still fun, the opportunity window is getting narrower. The IT job market as a whole has been shrinking for 2 consecutive years. Except for the COVID impact in 2020, this is the first time since the dot-com crash that we have observed such a decline. But the overall size of the job market is 4.2M. Any other time, we'd call this a post-traumatic market correction.
What's different this time is the reduction in entry-level positions and what is happening to the work itself. Big Tech companies that once hired thousands of new grads now take mere hundreds. Big Tech recruitment in this cohort has collapsed by 50% since 2019. Startups aren't doing better at a 30% reduction. Entry-level IT jobs are declining faster than the overall market. It's not just hiring freezes - these are permanent structural changes. Those mundane tasks juniors used to cut their teeth on - writing boilerplate code, fixing simple bugs, building CRUD apps - that's all getting automated away. AI isn't just changing how we work, it's eliminating entire categories of work that used to be the training ground for new developers.
Recent grad unemployment jumped from 3.9% to 5.8% in just over two years. Meanwhile, median IT salaries increased from ~$82,775 in 2016 to ~$100,000 in 2024. It means companies are paying more for fewer, more experienced people. They'd rather pay one senior engineer $150k than three juniors $50k each. Especially when that senior has AI tools that make them as productive as a small team.
The pivotal point
Looking back, 2023 was when everything went to hell.
You had four forces hitting at once:
Interest rates killed easy money: This was the first domino. During COVID, governments worldwide printed money like crazy - stimulus checks, PPP loans, and quantitative easing. All that cash chasing limited goods caused inflation to explode. By 2022, inflation hit 9%, the highest in 40 years. The Fed had no choice but to jack up rates from near-zero to over 5% to cool things down. Suddenly, the free money party was over. VCs couldn't raise funds as easily. Their LPs were getting better returns from boring treasury bonds. The entire startup ecosystem ran on cheap capital - when that dried up, everything changed. "Growth at all costs" became "profit or die" overnight. Companies were instructed to make their money last as long as possible. This meant hiring freezes or even layoffs.
Fear froze everything: The interest rate hikes didn't just kill VC funding - they triggered a full-blown banking crisis. Silicon Valley Bank, which held billions in startup deposits, had invested heavily in long-term bonds when rates were low. When rates spiked, those bonds cratered in value. When panicked VCs and startups tried to withdraw funds en masse in March 2023, SVB couldn't cover it. The bank collapsed in 48 hours, taking startups with it. Credit Suisse imploded. First Republic followed. These weren't random failures - they were direct casualties of the same interest rate shock that killed easy money. Even companies with healthy balance sheets got spooked. Make the runway last - the song continued.
The post-pandemic correction: Tech boomed over the pandemic. Everyone got their stuff online. Working from home lent itself easily when you only need a laptop to work. Tech companies hired aggressively, believing the "new normal" of everyone living online was permanent. Peloton thought people would never go back to gyms. Zoom thought every meeting would be virtual forever. Meta bet the farm on the metaverse. When reality hit, people wanted real life again, these companies found themselves grotesquely overstaffed. The layoffs started in late 2022 and accelerated through 2023.
AI Went Mainstream: Into this already brutal environment, ChatGPT reached its tipping point in November 2022. GitHub Copilot hit critical mass. AI didn't write code, debug, or explain complex systems. But it showed such potential. By mid-2023, every exec was having the same thought: "If AI can do this now, what will it do in two years? Why would I hire juniors today who'll be obsolete tomorrow?" In 2025, AI capabilities indeed have improved leaps and bounds. The writing was on the wall, and LLM wrote it.
Tldr: While companies froze hiring, AI tools got scary good. Senior developers with AI assistance became as productive as whole teams. Short-term thinking beats long-term planning. The pipeline that turned fresh grads into veterans was disrupted.
I felt like I'd seen this before. Then it hit me - this is what happened with housing.
Boomers bought cheap properties decades ago, watched values explode, and now young people are priced out forever. In tech, developers who got in pre-2020 learned when jobs were plentiful, climbed the ladder when companies actually hired juniors, and now sit pretty with six-figure salaries while new grads can't even get interviews.
Homeowners won't sell because "prices only go up." Companies won't hire juniors because "AI makes seniors more productive." Both ignore the obvious: what happens when there's no next generation?
Who's Getting Hit (And Who's Thriving)
Most at Risk:
Junior/Entry-Level Developers - Down 50% and falling.
QA/Manual Testers - AI is better at finding edge cases than humans. Automated testing used to be the specialty; now it's the bare minimum.
Technical Writers - LLM is scarily good at generating documentation from a collection of incoherent notes or directly from code. The few remaining roles are for high-level architecture docs, but that's senior-level work. Entry-level tech writing is extinct.
Basic Frontend Developers - If your skill set stops at HTML and CSS you're competing with AI that can generate entire sites from a description.
Business Analysts - AI can analyze requirements, map user journeys, and generate acceptance criteria. I am not sure if the quality is better, but it's sure easier to review than to write from scratch.
In Transition:
Application/Feature Developers - These folks are on the frontlines of the AI revolution and getting squeezed from all directions. The shift-left movement means they're now responsible for deployment and monitoring - DevOps stuff that used to be someone else's job. On top of that, every feature request now includes "add AI to this" without anyone knowing what that means. And they're under constant pressure to use Copilot, Cursor, or whatever AI tool to boost their productivity. They're simultaneously being replaced by AI and expected to be AI experts. It's exhausting.
Project Managers - The Excel jockeys tracking Jira tickets are done. But if you can navigate complex stakeholder politics and manage AI-augmented teams? Still valuable. For now.
Still Growing:
AI/ML Engineers - Obviously. Someone has to build and tune the AI that's eating everyone else's lunch. Salaries are insane because demand massively outstrips supply.
Security Engineers - AI creates new attack vectors faster than it solves old ones. Plus, adversarial thinking is inherently hard to automate. When AI tries to hack, you need humans to defend.
Software Architects - Complex system design, understanding trade-offs, making decisions with incomplete information - still firmly human territory. AI can suggest patterns but can't make judgment calls.
DevOps/Platform Engineers & SREs - When your systems serve millions and go down at 3 AM, you need humans who understand the full stack. Infrastructure is getting more complex, not less. AI can help write configs but can't debug production outages or design resilient systems.
The pattern is obvious: routine implementation is dead, complex problem-solving is thriving. But people in my generation learned about complex systems from building simple ones. Can one realistically skip the boring part?
Survival Strategies
Look, I could tell you to build a portfolio, contribute to open source, network your ass off. But you already know that shit. Everyone's saying it. Here's what they're not telling you about surviving when AI is eating your lunch:
Become Indispensable at the Human-AI Interface
First, let's be real - if you hate AI, you're fucked. It's like being a developer who kept using punch cards in the 90s. This is the new reality.
But here's your advantage: senior developers are just as new to AI as you are. They might have 10 years of experience, but when it comes to ChatGPT, Claude, or Copilot, you're both starting from zero. This is the one area where you can actually compete on even ground.
Don't just use these tools - master them. Learn their quirks, their failure modes, when they hallucinate. Better yet, go beyond single-tool usage. Build your own multi-agent workflows. Imagine a pipeline where a Jira ticket automatically generates specs, writes code, creates tests, and submits a PR. That's the level of AI productivity that makes companies take notice.
Target AI-Hungry Traditional Industries
Tech companies aren't hiring juniors, but traditional industries trying to adopt AI are desperate for talent. Manufacturing, healthcare, logistics, legal - they have money, they need AI integration, and they don't have the same impossible standards as Big Tech.
The catch? You need to learn their domain. They don't have an army of product managers and business analysts to feed requirements to you on a spoon. In this context, a mediocre developer who understands supply chain logistics is worth more than a brilliant developer who doesn't.
The "Full Stack Plus" Reality
Accept that the bar is higher now. You can't box yourself in an old boundary, like a Backend developer. You need programming + AWS + Docker + basic ML + system design. Might be more, the landscape changes quickly as AI replaces old skills and creates new demands. It sucks that entry-level now requires what used to be mid-level skills, but denying reality won't help.
But here's the harsh truth: even doing everything right might not be enough. The supply/demand imbalance is that severe. You need to be twice as good to get half as far.
The Transition Period
There is a saying that AI will create new jobs, that it'll all work out, net positive for humanity. There's historical precedent for that narrative. When PCs arrived in the 1970s-80s, it took 10-15 years before we saw net job creation. But look what emerged: entire IT departments in every company, business analysts, database administrators, network engineers. Jobs that didn't exist before because the technology didn't exist. The internet revolution? Similar pattern - 5-10 years of disruption before the explosion of new roles. Web developers, SEO specialists, social media managers, DevOps engineers, mobile app developers. With each wave, we've gotten a bit faster at adapting.
The problem is the "transition period". Even if it's shorter this time, say 5 years instead of 10, that's still 5 years where new grads are locked out. With the talent pipeline broken, who will become tomorrow's seniors?
It is hard to put this on the private sector. I work at a startup. We operate in a competitive environment. Any productivity we can squeeze out of AI adoption gives us an edge over our competitors. That is where all the energy and attention go these days. We can't afford to train people for the greater good while our survivability is at risk.
Some governments are starting to get it. Singapore is pumping serious money into reskilling programs. The EU has initiatives. Even in the US, there's talk of apprenticeship programs. It's not enough, and it's not fast enough, but it's something.
History says it'll work out. But history is written by the winners, not by the generations who got sacrificed during the transition.
What Now?
To be frank? I don't know. I feel like the industry, no, the society, got caught in an AI tsunami, and when everyone is busy either struggling to stay afloat or competing for a bigger share of the cake, the drowning kids are forgotten.
It's probably not just software development. Translators, paralegals, customer support, and many more careers are facing challenges to reinvent themselves in this age.
The private sector is for profit. Governments and NGOs mean well (hopefully), but they are painfully slow against the technosocial tides. Just like the housing market, local optimization is sowing the seeds for an uncertain future way way beyond the grasp of any individual.
We're in the messy middle of a major transition. Stay persistent. This isn't permanent, even if it feels like it. If you are struggling with this market, you're not alone, and it's not your fault. You're caught in a historical transition, not a personal failure.
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