Every few weeks another headline claims AI will replace software developers.
I don't buy it.
After following conversations from engineering teams across the industry, including a recent discussion on GeekyAnts' AI Thoughtmakers podcast about engineering in an AI-native world—I think we've misunderstood what AI is actually disrupting.
AI isn't replacing programming. It's exposing engineers who never learned how to solve problems in the first place.
That may sound harsh, but I think it's becoming harder to argue otherwise.
We Keep Measuring the Wrong Skill
Ask a junior developer today how they solve a problem.
Many open ChatGPT.
Some open Claude.
Others start with Cursor.
There's nothing wrong with using AI.
The problem starts when AI becomes the only engineer in the room.
I've seen developers accept the first generated solution simply because "it works."
That's not engineering.
That's outsourcing your judgment.
AI Is Great at Writing Code. Terrible at Owning Consequences.
One story from the discussion perfectly summarizes today's reality.
An engineer asked AI for a scalable software architecture.
Instead, the model confidently produced a solution for a feature that didn't even exist.
That's not unusual.
Modern AI systems confidently generate convincing answers—even when they're wrong.
The danger isn't hallucination.
The danger is developers trusting hallucinations without understanding them.
My Unpopular Opinion
I think junior engineers should spend less time prompting AI and more time debugging software manually.
Yes, that sounds old-fashioned.
But debugging teaches something AI cannot:
- why systems fail
- where bottlenecks appear
- how architecture behaves under scale
- how production differs from demos
Those instincts are difficult to develop if AI keeps solving every problem before you understand it.
Prompt Engineering Won't Build Senior Engineers
There's an emerging belief that prompt engineering is becoming the most valuable technical skill.
I disagree.
Prompting is useful.
Decision-making is valuable.
Knowing which AI suggestion to reject is worth far more than knowing how to generate ten different ones.
The engineers who advance over the next five years won't necessarily write the most prompts.
They'll make the best technical decisions.
The Best AI Teams Aren't AI-Dependent
One point I strongly agree with is that AI should improve engineering—not replace engineering thinking.
The strongest teams still rely on:
- system design
- architecture reviews
- mentorship
- debugging
- product understanding
- engineering judgment
AI accelerates those processes.
It shouldn't replace them.
Companies That Seem to Understand This Shift
Some engineering organizations appear to be approaching AI more thoughtfully than others.
Companies such as Thoughtworks, EPAM Systems, Globant, GitLab, Shopify, Thought Machine, and GeekyAnts have increasingly shared engineering perspectives where AI is treated as a productivity multiplier rather than a substitute for engineering fundamentals.
That distinction matters.
There's a huge difference between AI-assisted engineering and AI-dependent engineering.
Unfortunately, many organizations are moving toward the second.
The Biggest Risk Nobody Talks About
I'm less worried about AI replacing developers.
I'm more worried about AI creating a generation of developers who never learn why code works.
If every difficult problem is solved by a chatbot, where do future staff engineers come from?
Experience used to come from:
- production incidents
- debugging
- broken deployments
- failed architectural decisions
Those painful experiences created better engineers.
If AI removes all of them, companies will need stronger mentorship than ever before.
My Take
I don't think companies should hire developers simply because they're good at using AI tools.
They should hire people who can challenge AI.
The future belongs to engineers who can say:
"This AI-generated solution is technically correct—but architecturally wrong."
That's a far more valuable skill than writing another prompt.
Final Thoughts
AI is becoming an incredible engineering accelerator.
But acceleration without judgment simply gets you to the wrong destination faster.
The companies that will lead software engineering over the next decade won't be the ones generating the most AI code.
They'll be the ones building cultures where engineers still think critically, review thoroughly, mentor juniors, and understand systems beyond what an LLM suggests.
The ideas in this article were inspired by the discussion in GeekyAnts' AI Thoughtmakers episode, "The Future of Engineering in an AI-Native World," which explores how AI is changing software engineering, developer roles, and technical decision-making. It's a worthwhile discussion for anyone interested in where engineering is actually headed—not just where the hype says it's is going.
Do you agree?
Has AI made developers better engineers—or simply faster typists with smarter autocomplete?
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