The vanishing developer: How we can stop AI from killing the next generation of Engineers

In the rush to automate everything, the tech industry is in danger of quietly dismantling the very foundation that made it great: skilled human problem-solvers.

Artificial Intelligence, often seen as the cure for developer shortages and rising costs, is also a silent threat, if applied in the wrong way. It produces code at record speed, but it’s brittle, insecure, and opaque. And worse, it’s eliminating the opportunities that teach real engineers how to think, debug, and build systems that last.

AI tools like ChatGPT-based assistants churn out code that looks right but often isn’t. Anecdotal stories are now being confirmed by empirical data, outlining that 45% of AI generated code samples introduce known security vulnerabilities.

So, how can we turn the ship before too much damage is done?

AI isn’t all bad… but it’s no substitute for real skills

I have said for a while now, that AI is a great starting point. It takes out the boilerplate churn. Agentic AI even allows a discussion to be had, empowering developers to ask the question ‘why?’. But blindly relying on AI rots true understanding. Every time you ask for another edit, it’s accepting code without the comprehension, reasoning, and care that comes with true accountability – which you get from skilled human professionals.

Every great senior developer started as a junior; finding the bug in a stack and trying to figure out why race conditions only occur in production. This baptism of fire was the developer’s rite of passage. Proof that experience conquers all.

The problem is, that pathway is vanishing. Companies facing budget pressure are replacing junior roles with AI tools, believing they’ve found a cheaper substitute. “Why hire and train someone for a year when AI can generate code instantly?”

But that’s short-term thinking. AI doesn’t learn from experience, doesn’t mentor peers, and doesn’t evolve its judgment. Humans do. By skipping the junior layer today, we’re ensuring no seniors tomorrow.

What AI could mean for the future of software

If we don’t correct course now, then in five years, we’ll look around and realize there’s a gaping hole: no one who truly understands how the systems work. No one who’s learned to reason about complexity, trade-offs, or edge cases. Just maintainers of machine-generated code that no one can fully explain.

Replacing entry-level developers with AI might seem efficient – fewer salaries, faster code. But what’s happening is technical debt outsourcing: trading human understanding for machine output.

The long-term cost is enormous:

• Maintainability plummets – no one knows how the code really works.
• Security incidents rise – vulnerabilities multiply unseen.
• Team capability erodes – fewer people able to mentor or architect.
• Innovation stagnates – because creativity requires comprehension, not autocomplete.

Companies aren’t saving money; they’re hollowing themselves out.

The AI security vantage point

Security is one area where vigilance and human involvement is most critical. So with that in mind, it isn’t just about writing “secure” code snippets. It’s about understanding systems. Their boundaries, their assumptions, their failure modes.

AI doesn’t understand context or intent. It doesn’t know that a particular regex exists to mitigate an input sanitisation risk, or that a certain caching strategy protects against DDoS load. It just reproduces patterns.

Without human developers trained to spot and reason about vulnerabilities, organizations are effectively blind. They’re deploying opaque systems built by machines and reviewed by no one. Security, which should be a forefront mindset, becomes an afterthought.

The dystopian, ‘worst case’ future scenario could look a bit like this:

A handful of senior engineers hold legacy knowledge, AI tools generate code that no one fully understands, and there are no juniors who ever learned how to think like engineers.

At that point, every bug will be a crisis. Every incident, a mystery. Every system, a black box.

When those last seniors leave or retire, the lights go out.

Luckily for us, we’re not too far gone

In fact, we’re at a pivotal point and need to make smart, future-ready decisions.

The solution is still well within our grasp, and it’s simple. We must use AI to augment, not replace. To teach, not to eliminate teaching.

The greatest danger isn’t ‘bad AI’ – it’s losing the human capacity to build, reason, and care about quality. Software doesn’t rot because the code changes; it rots because the people stop understanding it.

If we let AI take the place of understanding, we’re not building faster or better, we’re building our own obsolescence, and gaining nothing. If we build an effective, symbiotic relationship between developers and AI, with the control in human hands, then we can continue to innovate while taking advantage of the efficiencies that AI offers.