The AI agent is flipping the script on software development. What was once a Herculean task of complex execution is now surprisingly straightforward. But the simple judgment calls? Those are getting harder.
We've been so busy automating the deep technical challenges – think multi-file refactors, even whole architecture migrations – that we’ve almost forgotten about the mundane, yet crucial, human elements. These AI agents are spitting out code that works, solving problems that used to take teams months. For instance, JLL Technologies saw an 85% reduction in development cycles by automating requirements, generation, and testing. Google engineers are generating 30% of their new code, boosting velocity by 10%. This is not hype; this is productivity.
But here's the twist that keeps me up at night. While AI devours complexity, it throws a spotlight on the tasks that require human nuance. What’s an optimal naming convention for a new abstraction? How do you define the precise boundaries of an AI-generated solution when it touches user-facing features? These aren't trivial questions, and they're becoming the new bottlenecks. The difficulty hasn't vanished; it's just moved upstream, from the lines of code to the strategic decisions about what code should exist and why. This inversion means our focus has to shift, dramatically.
For engineering leaders, this is a seismic change. We're seeing 3-6x ROI on AI agent development within the first year, not just from cost savings, but from direct revenue generation and elimination of friction. Yet, the ‘hidden costs’ of DIY implementation and the need for specialized talent are real. The real competitive advantage now isn't just faster execution, it’s the clarity of vision and the strategic application of AI. We need to train our teams not just to prompt, but to judge, to strategise, and to define the problem space with impeccable clarity.
This isn't about replacing engineers. It's about fundamentally redefining what engineering value looks like. The AI doesn't think; it executes based on our direction. Our experience and judgment are now more critical than ever to guide this powerful execution.
How are you redefining complexity in your engineering teams?
The code doesn't write itself. Yet.