Software
August 3, 2025 1:05 PM
VentureBeat/Ideogram
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As AI continues to take on more and more new competencies, junior coding, as we knew it, is rapidly becoming a thing of the past. Tasks that used to be the bread and butter for junior developers — such as repetitive scripting, HTML layout or simple DevOps setups — are now being reliably handled by AI assistants like ChatGPT, GitHub Copilot and Amazon CodeWhisperer.
This is not just an upgrade to speed and efficiency — we are looking at a serious structural change here. So where does that leave entry-level developers? And, speaking more broadly, where does it leave the software industry as a whole?
The vanishing beginner level
For decades, software engineering as a field had a fairly predictable pathway: Begin with the basics, build some landing pages, write test cases, troubleshoot minor bugs. As your skills grow, you can move toward architectural thinking and product ownership.
But now AI is vastly changing how the bottom end of that ladder operates, since it can do most junior-level tasks on its own.
As a result, beginners entering the industry are increasingly being asked to contribute at a level that used to require years of experience. It is not just about writing code anymore — it is about understanding systems, structuring problems and working alongside AI like a team member. That is a tall order. That said, I do believe that there is a way forward. It starts by changing the way we learn.
If you are just starting out, avoid relying on AI to get things done. It is tempting, sure, but in the long run, it is also harmful. If you skip the manual practice, you are missing out on building a deeper understanding of how software really works. That understanding is critical if you want to grow into the kind of developer who can lead, architect and guide AI instead of being replaced by it.
The way I see it, in the near future, the most valuable people in tech won’t be the ones who write perfect code. They will be those who know what should be built, why it matters and how to get an AI system to do most of the work cleanly and efficiently. In other words, the coder of tomorrow looks more like a product manager with solid technical expertise.
Teams are changing, too
Based on everything we covered above, I also feel the need to point out that it is not just individuals who need to rethink their roles. Entire teams are shifting. Where we once had clearly defined roles — front-end developer, back-end specialist, DevOps engineer, QA tester — we will soon see one developer managing a whole pipeline with the help of AI.
AI-augmented developers will replace large teams that used to be necessary to move a project forward. In terms of efficiency, there is a lot to celebrate about this change — reduced communication time, faster results and higher bars for what one person can realistically accomplish.
But, of course, this does not mean teams will disappear altogether. It is just that the structure will change. Collaboration will focus more on strategic decisions, product alignment and making sure AI tools are being used responsibly and effectively. The human input will be less about implementation and more about direction.
AI is creating a new career path
If we look five to seven years ahead, I suspect that the idea of a “developer” as we know it today will have changed into something else entirely. We will likely see more hybrid roles — part developer, part designer, part product thinker. As already mentioned, the core part of the job won’t be to write code, but to shape ideas into working software using AI as your main creation tool. Or perhaps, even as a co-creator.
Being technically fluent will still remain a crucial requirement — but it won’t be enough to simply know how to code.
You will need to understand product thinking, user needs and how to manage AI’s output. It will be more about system design and strategic vision.
For some, this may sound intimidating, but for others, it will also open many doors. People with creativity and a knack for problem-solving will have huge opportunities ahead of them.
The landscape is shifting, yes — there is no escaping that fact. But for those willing to adapt, one could argue it is shifting in their favor. The end of junior coding is not the end of learning. It is a sign that we need to reconsider what kind of talents we grow, how we structure teams and what makes someone a great developer.
To my mind, instead of mourning the loss of basic tasks, the industry as a whole should focus on building the skills that cannot be automated. At least, not yet. That means implementing a hybrid approach and learning how to work with AI as a partner rather than a competitor.
Roman Eloshvili is founder of ComplyControl.
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