We’re Automating Ourselves Into Stupidity
In the rush to embrace AI in development workflows, we’re unintentionally burning the ladder future experts are supposed to climb. The same tech that’s making junior coders and analysts faster is also making them dumber. If we don’t course-correct soon, we’ll end up with a generation that can deploy AI-generated code but has no idea how it works.
Right now, junior devs are told to “just use AI.” Stuck on something? Ask ChatGPT. Need to write boilerplate? Copilot will do it. Confused about syntax or a bug? Paste it into your favorite LLM and wait for salvation.
On the surface, it’s amazing. Speed is up. Confidence is high. Management loves the velocity. But we’re not producing engineers anymore – we’re producing prompt monkeys.
The Lost Grind That Made Engineers
The junior developer used to be the grunt writing tedious code, debugging garbage, learning through repetition, and slowly building the mental models that make someone senior. That hard, boring work is where intuition is born. It’s how you get to the point where you can:
- Spot a bug in 200 lines of logic just by skimming,
- Recognize when performance will tank just by reading an algorithm,
- Know when something “smells wrong” even if it compiles and runs.
You don’t learn to engineer by pasting snippets. You learn by bleeding in the trenches. They’re earned through years of grinding. And AI has made that grind optional. Which sounds like progress, until you realize it’s also made deep understanding optional.
Analysts Aren’t Safe Either
It’s not just coders. Same story with junior analysts. Feed them vague requirements? The LLM will reword them for Jira. Need user stories from stakeholder chaos? Just prompt the model. Need a flowchart? Autogenerate it.
Automation isn’t the villain. Forgetting why the work mattered is: It’s that it used to be how people learned. We’re gutting the entry-level trenches and expecting seniors to magically appear in 5 to 10 years. But guess what? No juniors grinding through ambiguity today means no experts tomorrow.
The Pipeline Is Breaking
This is the real long-term threat. Not AI replacing humans, but AI eroding the pipeline that produces people who understand systems deeply.
You can’t become a senior engineer if you never:
- Wrote your own loop instead of pasting one,
- Debugged someone else’s terrible logic without a linter,
- Sat with a crashing app and figured it out line by painful line.
- Spent 4 hours chasing a memory leak caused by one misplaced character.
Those scars make seniors valuable. AI smooths over the pain, but that means no scars, no lessons, no depth.
Duct Tape and Black Boxes
Fast-forward 10 years, and we’ll be running systems duct-taped together with black-box models, third-party APIs, and AI-generated code written by people who couldn’t explain what a thread lock is if their job depended on it. Spoiler: it will.
The short-term gain is massive. The long-term brain drain is terrifying. And when the black box fails? No one left who can even open it.
So What’s the Fix?
We need a new kind of apprenticeship. Juniors shouldn’t be cut; they should be retrained. Yes, they should use AI. But they should also be mentored, code-reviewed, and forced to touch the ugly internals. Give them broken code. Give them impossible specs. Make them suffer a little. They’ll thank you later.
AI isn’t the problem. The problem is how we’re letting it replace thinking instead of enhancing learning.
Because if we keep going like this, we’ll wake up in a decade with no one left who understands the machinery. Just prompt engineers and system babysitters. And when something breaks? Good luck finding anyone who knows where the duct tape even was.
Conclusion
Use AI. But teach the next generation to build with it, not through it.
Otherwise, we’re not training engineers. We’re training parrots.
