AI Coding: The Great Skill Revealer
I've been watching something fascinating unfold in the development community lately. As AI coding tools have become mainstream, they're revealing something unexpected: who actually understands what they're building.
The Two Paths
When developers pick up AI assistants, they seem to split into two distinct camps. The first group treats AI like a supercharged pair programming partner. They know what they want to build, can spot when something's off, and aren't afraid to tear things apart and restructure them. They're using AI to move faster, not to think for them.
The second group? They're playing a different game entirely. It's prompt roulette—keep spinning until something appears to work. Ask them why it works, and you'll get blank stares. Watch them try to debug when things break, and you'll see real struggle.
It's Not About Gatekeeping
Before anyone grabs their pitchfork, this isn't about keeping people out of software development. I've seen lawyers and business owners build genuinely useful internal tools with AI that would've cost them six figures to outsource. One guy mentioned burning through $150k with a dev team that couldn't deliver an MVP, then building it himself with AI in two weeks for $250.
That's legitimately amazing.
But here's the thing: those successful "vibe coders" usually understand their problem domain deeply. They know the business rules, they know what good looks like, they know when AI is giving them garbage. They might not know React hooks from fishing hooks, but they know whether the solution actually solves their problem.
The Learning Paradox
The debate about juniors is interesting. Some people think AI makes learning harder because you can always find a quick solution without struggling through the problem. Others argue it's the best learning tool ever—better than dusty textbooks and StackOverflow threads.
They're probably both right.
The difference is intent. If you're using AI to avoid learning, you won't learn. If you're using it to accelerate learning—asking it to explain concepts, break down complex code, generate examples—it's incredible. The tool doesn't decide. You do.
The Overhead Problem
One developer made a great point about the mythical man-month applying to AI code. You can generate 20,000 lines of code really fast, but if you don't understand it, you've just inherited a massive maintenance burden. It's like diving into an unfamiliar open-source project—you're starting from scratch trying to understand someone else's mental model, except that "someone" is an AI with no mental model.
The code might work beautifully, but you're the one who has to maintain it.
What Actually Matters
After reading through dozens of perspectives on this, a few things seem clear:
Understanding beats memorization. Nobody cares if you can write a perfect for-loop from memory anymore. But understanding when to use different data structures? That still matters.
Decision-making is the hard part. AI writes code. It doesn't decide what to build, how to architect systems, or what tradeoffs to make. Those decisions are still on you.
Communication matters more than ever. One person mentioned their most valuable skill is "communicating without coming across like a defensive, insecure asshole." Funny, but true. Working with AI, working with teams, understanding stakeholders—that's not getting automated.
The Real Question
Should people bother learning to code "properly" if AI keeps getting better?
I think that's the wrong question. The right question is: do you want to be someone who directs AI tools, or someone who hopes AI tools can save them from their own lack of understanding?
The developers who understand systems, architecture, and fundamentals aren't scared of AI. They're using it to build things they couldn't have built before. They're moving faster, exploring more ideas, automating boring work.
The people who are worried are usually the ones who realize they've been copy-pasting StackOverflow code for years without understanding it, and now AI is just a faster version of the same pattern.
Final Thought
AI isn't going to make technical knowledge obsolete. If anything, it's making it more valuable by letting people who have it move faster while exposing those who don't.
It's not a substitute for understanding. It's an amplifier.
And amplifiers make everything louder—both the signal and the noise.