AI coding assistants make junior devs faster and worse at the same time

A developer has observed that junior engineers using AI coding assistants like GitHub Copilot produce code faster and with cleaner appearance, but often cannot explain or debug the code when it fails. The developer warns that AI-generated code passes superficial review yet contains subtle errors that juniors lack the experience to identify, creating technical debt and security risks. The post calls for teams to require juniors to explain AI-generated code line-by-line and to prioritize debugging practice over pure speed.

Copilot gives juniors the speed of a mid-level dev with the judgment of an intern. That's not a compliment to anyone involved. I have been assessing PRs submitted by junior developers for some time now, and I noticed a change in the last year. The code appears to be more neat. It is delivered more quickly. But when something breaks, the person who wrote it often can't explain what it does. AI programming helpers such as GitHub Copilot are truly amazing. A junior developer can set up the structure of a new feature in a few hours whereas it would have required them a week to implement it two years ago. But speed without understanding is just technical debt with a bow on it. The code gets merged, the ticket gets closed, and nobody notices the problem until production does. Here's the recurring pattern that I've noticed: → Copilot generates subtly incorrect code that passes superficial review → The junior dev can't spot the issue because they didn't write the logic themselves → The senior reviewer skims it because it looks clean and idiomatic → A bug ships that nobody on the team fully understands This isn't hypothetical. It's Tuesday. Research has indicated that AI-suggested code is more likely to contain security errors. That tracks with what I'd expect when the person accepting the suggestion doesn't fully understand what it's doing. The concerning aspect is not the existence of bad code, but the potential of having juniors who've never bothered to learn the fundamentals because the AI just writes seemingly working code for them on the first instance. Why learn how async error handling actually works when Copilot provides you with something that passes the tests? 🤷 Well, the simple answer is that tests cannot cover every single use case and potential issue. And when the thing Copilot wrote fails at 2 AM, you need someone who can actually read the code, not just someone who can prompt for a fix. I worry we're creating a generation of developers who can ship fast but can't debug what they shipped. I rely on Copilot. I enjoy using Copilot. It saves me real time on boilerplate and helps me think through approaches faster. But I already know what good code looks like. I can somehow tell when a recommendation is not quite right. That instinct comes from years of writing bad code myself and learning from it the hard way. Juniors haven't built that instinct yet. And if AI removes the struggle that creates that instinct, we have a real problem. It's akin to handing out a calculator before you understand the concept of multiplication. They will receive responses. They just won't know when the answers are wrong. 🎯 I'm not suggesting AI tools should be off-limits for junior devs. It wouldn't work and might even have the opposite effect. I believe that teams should plan for this to happen. → Require juniors to explain AI-generated code line by line in PR reviews → Pair program on the debugging , not just the building → Create space for juniors to write ugly, slow, manual code sometimes — that's where learning lives → Treat Copilot suggestions like Stack Overflow answers: useful starting points, not gospel The goal isn't slower development. It's making sure the person behind the keyboard is actually growing, not just the codebase. AI assistants aren't going away. They're going to get better. The developers who thrive will be the ones who used AI as a tool to accelerate learning, not a shortcut to skip it. Those students who simply coasted through their initial couple of years by copy-pasting code and not really comprehending what they were doing? They are going to face a formidable obstacle. And they won't have the skills to debug why they're stuck. 😬 How is your team handling AI assistants with junior developers? Are you seeing the same patterns, or am I overthinking this?