One of the recent graduates who is a part of our team was able to author a PR with 400 lines of code in just one afternoon. The changes were clean, all tests were passing and the PR was ready to be shipped. Then all of a sudden production had a memory leak. No dialog box, no autocompletion, just a graph going up and a very stressed junior.
The thing nobody wants to say out loud
A viral post on r/ExperiencedDevs about a coworker being fired for using AI instead of learning the code spawned massive arguments. It hit 1000+ comments discussing if AI is silently destroying the way juniors are meant to learn. Both sides are half right. And both sides are dodging the real problem. We didn't recruit engineers that are AI users. We recruited operators for a prompt and are surprised they can't think through a system without it.
The data caught up to the vibes
A study by Anthropic in January 2026 titled "How AI assistance impacts coding skills" found that AI users averaged 50% on comprehension quizzes. The hand-coding group averaged 67% (Cohen's d=0.738, p=0.01). The most significant difference was not about syntax or style, but rather related to debugging questions.🧠
The situation deteriorates for the heavy users. Those in the "AI delegation" group who consistently depended on AI scored less than 40 percent. They were the quickest in completing the tasks yet demonstrated "less independent thinking and more cognitive offloading."
Simply put by Anthropic's researchers: "If junior engineers' skill development has been stunted by using AI in the first place, the productivity benefits may come at the cost of skills necessary to validate AI-written code."
Twice the reading is required. The individuals supposed to evaluate the AI are those who lacked the strength to evaluate anything in the first place.
The codebase is rotting quietly too
GitClear analyzed 211 million lines of code created from January 2020 to December 2024. Refactorings decreased from 25% of commits in 2021 to fewer than 10% in 2024. In 2024, the percentage of duplicate code blocks increased by 800% unexpectedly! It was also the year when the amount of copy-pasted code surpassed that of refactored code. This is not an issue of skills. It's about a system that is getting clogged up over time because there is no one person overseeing the entire operation.
Why debugging is the wall
Generating code and understanding a system are different sports.
→ Writing code is local. You need one file and a clear goal.
→ Debugging is global. You need hundreds of files living in your head at once.
→ AI is great at the first. It falls off a cliff on the second.
Have you seen SWE-bench, the benchmark full of bugs from real GitHub repos? Generalist models such as GPT-4 and Claude 2 didn't even get over 5%. They don't solve anything for the same reason our junior hesitated. Actual glitches require an entire mental image of hundreds of interconnected documents, and there is no instruction manual that gives you that.
So whose fault is it?
We didn't fall into the trap. We set it up and led them into it. We rewarded speed over understanding. We praised the fast PR and never asked anyone to explain the logic behind it. In April 2025, Om Moolchandani, CISO/CPO at Tuskira, stated: "Junior resources have less problem-solving acumen, lack deep system-level understanding (e.g. the ability to dissect and resolve issues in language compilers/ interpreters, operating systems), and the concepts are ultimately formed based on the level they enter the industry. Many can generate functional code snippets but struggle to explain the logic behind them or secure them against real-world attack scenarios."
That is the essence of it. Create, perhaps. Justify, no. We outsourced the learning curve, then acted surprised the learning didn't happen.
What I'm actually doing about it
I no longer judge junior team members based on their pull request speed. In our tiny team, fast code integration is insignificant if you cannot take the time to explain and discuss the implementation with me. The solution is not to prohibit AI but to ensure that people deserve the quick workaround.
→ Explain the diff out loud before it merges. No "the AI wrote it."
→ Debug one gnarly thing a week with the autocomplete off.
→ Read old code that isn't yours until the system stops feeling like magic.
AI can speed up things amazingly well provided you already have a framework to speed up. But it's not at all a substitute for creating that framework in the first place. The junior developer who panicked and froze is not defective. They're just the one who was never before asked to do the hard thing, and then the hard thing showed up in their real work. My question is, if your top junior had no tools due to AI for a week, would they still be your top junior?
Top comments (1)
The weak spot is the handoff from code generation to fault isolation. If a junior can produce a PR but cannot explain the memory graph, the team has bought speed in the easiest part of the task and debt in the part that decides whether the change is safe.I would make AI use visible in review. Ask for the failure hypothesis, the files they ruled out, and the smallest test that would prove the leak is gone. That trains debugging without pretending autocomplete is going away.