AI Took the Junior Tickets, and Entry-Level Hiring Halved

Put a junior engineering role somewhere visible and it can draw a thousand applicants, a lot of them fired off in bulk with AI tools. On the other side of the table, entry-level hiring at large tech firms is down roughly 50% from 2019. It shows up in data from SignalFire, LinkedIn and Handshake, so it isn't a quirk of one dataset.

Together that makes the most brutal entry-level market in tech's modern history, and pretending otherwise helps nobody.

Engineers used to learn the same way. You got handed small, well-defined tickets, wrote boilerplate, fixed simple bugs and slowly absorbed the codebase until you could move up. The small ticket, the boilerplate, the simple bug and the first draft of everything are exactly what LLMs now produce in seconds. That was the first rung of the ladder, and companies noticed it had gone.

Seniors with AI tools stopped needing the extra hands

For the most part AI hasn't replaced juniors one for one. What changed is the economics of a senior engineer. With AI tools, a senior now gets through routine work faster than a senior plus a junior used to, with no mentoring overhead. When budgets tightened in 2022, junior pipelines were the easiest thing to freeze. When the tools matured in 2024, they were the easiest thing to leave frozen.

We think this is short-sighted for the industry as a whole. The juniors nobody hires today are the seniors nobody can find in 2030, and firms will rediscover their pipelines once mid-level people get scarce and expensive. But that correction runs on a lag of three to five years, and you can't pay rent with an industry's future regret.

The front door broke, but other routes still work

Applying online with a degree is the path that stopped working. These still do.

Shipped work counts for more than a transcript. Two or three real projects with real users, deployed and documented, now beat a GPA nearly everywhere that matters. The bar moved from "can learn" to "can already ship." The good news is that proving you can ship has never been cheaper.

Open source does the job internships used to. Contributing to a real codebase shows the things interviews can't test: reading other people's code and taking review. Maintainers also refer contributors, so the network you build counts as much as the code.

Use AI where people can see it. You have one real advantage over the people already in the industry, which is that you've got no pre-AI habits to unlearn. Write up workflows where you get AI to deliver work above your experience level. Companies aren't avoiding juniors who multiply themselves with AI. They're avoiding juniors who compete with it.

Look outside big tech. Banks, insurers, retailers, manufacturers, healthcare systems, defense contractors and governments all hire tech people, the competition is less ferocious, and more of them need people who are comfortable with AI. A lot of entry-level tech careers start there now.

Get referred. When a posting pulls 500 applicants for every opening, the application portal is a lottery, and a referral converts at roughly ten times the rate. Build those relationships (alumni, meetup contacts, maintainers of projects you contribute to) before you need them, because referrals are now the main hiring channel.

If you're still picking what to study

Computer science fundamentals still pay off over a career. When AI writes the easy code, understanding what that code actually does gets more valuable. But pair the degree with the things it doesn't give you: products you've shipped, fluency with AI tools, a domain such as health, finance or energy, and public evidence of all of it.

In 2026 the graduate who gets the call is usually the one a hiring manager can Google.