Hiring a great software developer was always hard. In 2026 it''s hard in a new way: artificial intelligence already writes a huge share of the code —more of it, and better, every day— and that changed what you look for in a person.

At Avanzia we live it daily. Our conclusion is simple: AI replaces the typing-the-code part, not your judgment for designing systems or your ability to ask the right questions of the right person. Here''s the picture with data, and what it means whether you''re hiring or still studying.

AI already writes a huge share of the code

This isn''t marketing hype. On Alphabet''s October 2024 earnings call, Sundar Pichai said more than a quarter of all new code at Google is AI-generated — reviewed and accepted by engineers. By 2026 the figure Google cites publicly is around 75%. Microsoft says 20-30% of its code is written by software (Satya Nadella, 2025). Adoption is massive: GitHub Copilot passed 20 million users and is used by 90% of the Fortune 100.

These tools make writing a block of code faster than ever. That''s the mirage — and the trap.

But you can''t delegate everything

This is where the easy narrative falls apart. The 2025 data is uncomfortable for anyone who believed AI could already code on its own:

Security: Veracode''s 2025 report found that about 45% of AI-generated code introduces a security vulnerability — and, crucially, newer models write functionally correct code but not more secure code.
Invented dependencies: a USENIX Security 2025 study showed that nearly 20% of the packages models recommend don''t exist. Attackers already register those fake names with malware (they call it slopsquatting).
"Almost right, but not quite": in Stack Overflow''s 2025 survey, 66% of developers said their biggest AI frustration is that solutions are "almost right, but not quite," and 45% said debugging AI code takes them more time.

There''s a rule that sums it up, from Google engineer Addy Osmani: the "70% problem." AI gets you fast to 70% of the solution; the remaining 30% —edge cases, security, integration, being maintainable in production— is as hard as ever and demands human judgment.

And one finding should give anyone pause: a 2025 METR experiment measured experienced developers working in their own mature repos, and with AI they were 19% slower — even though they believed they were 20% faster. AI helps least exactly where the work is most complex.

That''s why you still need humans — but different ones

None of this means "AI is useless." It means someone has to supervise and correct it constantly: read what it produces, catch the subtle bug, decide the architecture, and —above all— ask the right questions before a single line is written. That work is more human than ever.

The market already reflects it. Per SignalFire, new-grad hiring at Big Tech fell more than 50% versus 2019, and new grads were just 7% of hires. Indeed measured junior postings down 34% while senior only 19%. SignalFire''s conclusion is blunt: the bottleneck has moved from writing code to reviewing it.

And yes: many still love to code

An important nuance. Many developers love writing code — it''s what made them fall for the craft. That doesn''t disappear, but it moves: the value is no longer in how much you type, but in what you decide to build and how you judge it. In fact, healthy skepticism is growing: in 2025, for the first time, more developers distrust (46%) than trust (33%) AI''s accuracy — and only 3% "highly trust" it. The most skeptical are seniors, the very people accountable for what ships.

Which skills are worth more now

If AI writes the code, why do they pay you? For what it does badly:

Architecture and system design. AI writes functions; it designs systems poorly. The World Economic Forum (Future of Jobs 2025) ranks analytical thinking as the #1 skill, valued by 69% of employers.
Judgment to review. Reading and evaluating code faster than you write it. With 84% using AI but only 3% fully trusting it, the human filter is the job.
Asking the right questions. Directing AI is a communication task: vague intent, vague code. Knowing what to ask, and whom, is gold.
Solid fundamentals. Without them you can''t tell correct code from confident garbage.
Human skills. WEF and LinkedIn agree: creativity, adaptability, communication and continuous learning rise in value exactly as the technical gets automated.

If you''re a university student, prepare like this

The good news: it''s never been clearer what to build. If you study CS, start today with this:

Make AI an explicit skill. Learn prompting, context, and tool orchestration. It''s the fastest-growing skill per LinkedIn.
Learn to read and review code faster than you write it. The bottleneck moved to review.
Master CS fundamentals. Data structures, algorithms, networks, databases: your lie-detector against AI.
Treat AI code as untrusted input. Learn security (OWASP Top 10) and threat modeling.
Build end-to-end projects, especially the hard 30%: finish, deploy and maintain something real. Worth more than a thousand tutorials.
Practice communication and spec-writing. Directing AI is writing clearly.
Specialize. Generic work (one more CRUD) is exactly what AI commoditizes; deep domain isn''t.
Show you learn fast. You''re hired for learning velocity, not only for what you already know.

The bottom line

Hiring in 2026 stopped being about finding the fastest typist. It''s about finding whoever thinks, asks good questions, and knows how to leverage AI without delegating judgment. AI replaces writing code; it doesn''t replace your architecture experience or your ability to ask the right question of the right person.

At Avanzia we''re betting on exactly that profile. If you''re in Puebla, speak English, and want to learn to build with AI on real projects, take a look at our 2026 Trainee Program or get in touch.

The Challenge of Hiring Software Developers in 2026