In 2025, organizations are reassessing AI’s real impact on software development productivity. Evidence shows that AI tools can slow teams when used without experience, highlighting the continued importance of senior engineering judgment. The strategic advantage now lies not in replacing junior developers with AI but in using AI to accelerate their growth, ensuring long-term capability and resilient technical leadership.
Some institutions have downplayed AI’s impact on software development productivity. A recent METR study found that a sample of open-source developers using AI tools actually took longer to complete tasks.
Why? Think of a chess master. They don’t win by evaluating every move. They win because they know which moves not to consider. Experience trains instinct — a filter that focuses attention only on what matters.
Senior developers operate the same way. They’re not faster because they code faster, but because they instantly sense which solutions won’t scale or align with long-term goals. When less experienced developers use AI assistants, their prompts often leave too many options open. The AI dutifully delivers a solution — but only later does the team realize it doesn’t fit the bigger architecture.
I’ve seen one company let a promising junior developer go, with the CEO stating “Our head of development now has a team of AI agents working for him.” While this may be justified in a cash-strapped startup, in any other circumstance it is just plain short-sighted. One day, the seniors will move on. Without nurturing new talent, the organisation’s so-called AI advantage will evaporate.
The smarter path is to use AI to grow juniors into seniors. Instead of prompting with:
“Create code that does X,”
encourage:
“You are a seasoned software engineer and a trainer in software architecture design patterns.
Here’s my requirement and my design — ask clarifying questions, then identify weaknesses or improvements.”
That turns AI from a task-taker into a coach.
Now, this is obviously not a substitute for a colleague with decades of software engineering experience (a scarce resource in any organisation). But it will avoid many fruitless iterations with the AI, peer review, indeed the entire development cycle, while acquainting the junior developer with new and important considerations.
AI won’t replace experience — but it can accelerate the development of experience. That’s where the true productivity revolution begins.
With over 35 years of professional software development experience, Mike combines deep technical expertise with a strong focus on quality. His areas of specialization include AI and machine learning, data warehousing and business intelligence, as well as scalable enterprise software architectures. As a passionate advocate for software quality, he promotes agile development practices and modern quality assurance techniques, sharing his knowledge in projects and technical articles.