Over the last two years, development and technology teams have changed more than in the previous decade.
AI coding assistants, generative tools, and automation platforms have moved from curiosities to everyday infrastructure. It’s now normal for developers to ship code with the help of AI pair programmers, auto-generated tests, and AI-accelerated documentation.
On the surface, this looks like a pure efficiency story: faster output, leaner teams, shorter cycles.
But under the surface, something more complex is happening — especially around how teams are structured, who gets hired, and what this means for the next generation of talent.
If we’re not careful, we may be heading toward a future talent gap that will be very hard to fill.
The classical picture of a development team junior, mid-level, and senior engineers working through tickets is being quietly rewritten.
Here’s how many teams have adapted to AI over the last couple of years:
AI tools can now handle a significant chunk of boilerplate code, standard patterns, and repetitive tasks. As a result, human developers spend more time on decisions and architecture, and less time on pure implementation.
Senior engineers are increasingly focused on:
The job is becoming more about judgment and oversight than manual line-by-line coding.
With AI boosting individual productivity, many organisations feel they can run smaller teams with more senior engineers. Why hire three juniors when one strong senior plus AI can produce similar output?
This has led to:
In the short term, this feels efficient. In the long term, it’s risky.
We’re also seeing the rise of hybrid roles:
The competencies expected inside a “tech team” are broadening well beyond classic frontend/backend titles.
All of this has a very real human consequence: it’s getting harder for junior developers to get started.
Many teams are asking:
“If AI can write basic code, do we still need juniors?”
The answer is yes but it requires a more deliberate strategy.
Right now, the ecosystem is feeling the effects of:
Juniors historically learned by:
If AI absorbs most of the simple work and we don’t redesign how juniors learn, we risk cutting off the natural training pipeline for future mid-level and senior engineers.
In the short term, AI plus senior-heavy teams can feel like a win: more output, fewer people, less overhead.
But think about the medium to long term:
You can’t “AI” your way out of a missing generation of talent.
AI is powerful, but it still relies on:
Those people don’t appear magically. They are grown, over time, through experience.
If the industry creates a multi-year gap where fewer juniors are hired and trained, we will feel that pain later as a shortage of experienced engineers, just as systems become more complex and AI more deeply embedded into core infrastructure.
The answer is not to ignore AI or pretend the old model still works. It’s to redesign how we develop people inside AI-augmented teams.
A few practical ideas:
Junior developers can:
They might write less boilerplate code themselves, but they can still gain exposure to all the fundamental concepts.
Instead of leaving juniors to “figure it out” with AI in the mix, create structured learning:
This way, they don’t just become “prompt operators” — they become real engineers who use AI as a tool.
If seniors are always firefighting, they won’t mentor.
Organisations will need to explicitly budget time for mentoring and coaching as part of senior roles — and recognise that growing talent is itself a strategic investment, not a distraction from “real work”.
The most competitive organisations will use AI to multiply the impact of both seniors and juniors, rather than using AI as an excuse not to build a pipeline.
But that only works if you still have humans with growing expertise at the core.
The next few years will separate companies that treat AI as a quick way to cut costs from those that treat it as infrastructure for long-term advantage.
Short-term thinking says:
“We don’t need juniors; AI can handle the simple stuff.”
Strategic thinking says:
“We’ll use AI to make our teams more productive and invest in the next generation, so we still have strong talent five years from now.”
If the industry doesn’t address this, we may end up with:
And that’s not a future any serious technology organisation should want.
AI is reshaping how tech teams work mostly for the better.
But as we redesign our workflows, hiring plans, and team structures, we cannot forget the basics: every senior engineer was once a junior, and every resilient organisation is built on a pipeline of people who grow over time.
The challenge for 2025 and beyond is clear:
If we get that balance right, we’ll have development teams that are not just more efficient today, but also more sustainable, skilled, and resilient in the years to come.
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