Picture is of Moroccan Couscous, It’s not consciously related to the post….
I still invest in junior developers. Most companies aren’t. They’re cutting juniors out, replacing them with AI tools that can spit out production-ready code in seconds. On paper, it looks efficient. In practice, it’s fragile.
Because what you gain in speed, you lose in depth. Juniors who never learn to debug, reason through complexity, or question design decisions don’t become seniors; they become operators pressing buttons. That’s dangerous for long-term reliability.
The Trap of Easy Output
AI doesn’t think. It predicts. It can write code that looks flawless, passes tests, and still hides subtle landmines. The worst part is, if you don’t understand how it works, you won’t see them until it’s…
Picture is of Moroccan Couscous, It’s not consciously related to the post….
I still invest in junior developers. Most companies aren’t. They’re cutting juniors out, replacing them with AI tools that can spit out production-ready code in seconds. On paper, it looks efficient. In practice, it’s fragile.
Because what you gain in speed, you lose in depth. Juniors who never learn to debug, reason through complexity, or question design decisions don’t become seniors; they become operators pressing buttons. That’s dangerous for long-term reliability.
The Trap of Easy Output
AI doesn’t think. It predicts. It can write code that looks flawless, passes tests, and still hides subtle landmines. The worst part is, if you don’t understand how it works, you won’t see them until it’s too late.
When something breaks, you won’t know where to look: your logic, the AI’s pattern-matched guess, or a dependency it quietly imported. Those mistakes compound quickly. Before long, you’re maintaining a codebase no one actually understands.
Why Mastery Still Matters
Every senior developer I’ve worked with got there by grinding through the hard stuff: tracing bugs, reading stack traces, and learning how systems fail. That pain builds intuition. You can’t outsource it.
That’s why I’d rather take a junior who’s hungry to learn than rely on AI to fill skill gaps. The goal isn’t to avoid the hard parts; it’s to use AI after you’ve earned your foundation.
How AI Can Actually Help You Learn
Used well, AI can make learning faster than ever. It’s an instant feedback loop. You can ask why something works, explore multiple approaches, and see failure modes in minutes instead of weeks.
The key is to engage with it critically. Don’t just copy what it gives you. Challenge it. Break it. Ask it to explain every choice. The more you push back, the faster you’ll develop real understanding.
Balancing Growth and Reliability
At my companies, I let juniors use AI, but under discipline. They still need to reason through bugs, performance, and architecture. AI is there to help them think faster, not think less.
This balance matters. Reliability depends on engineers who understand the systems they’re building. You can’t fake that with a prompt.
The Takeaway
AI can make you faster and sharper, but it only multiplies what’s already there. If you haven’t built the foundation yourself, it’ll just multiply your blind spots.
Use AI to explore, not to escape thinking. Ask it to explain, not to replace. Read what it gives you until you own it.
Real skill is still earned the old way, by wrestling with complexity until you understand it from the inside out.