Digital.ai CTO Wing To delves into how the way code is written, deployed and managed will fundamentally change in the artificial intelligence (AI) era.

Cutting through the extremes, AI won’t erase entry-level dev jobs, nor will it fully replace senior developers. Instead, it’s changing what both groups focus on. Entry-level devs will need to learn how to effectively prompt, evaluate and refine AI-generated code, while senior devs may shift toward mentoring, reviewing AI-assisted output, and ensuring software quality. The fundamental knowledge of how systems work still matters—AI doesn’t remove the need for strong foundational skills.

But AI does change the coding landscape. Developers are writing less and reading more. Reviewing AI-generated code—often verbose, not elegant—has become part of the job. And while some fear that the code is harder to debug, it may just be different: more mechanical, less idiosyncratic.

From a DevOps perspective, AI introduces new challenges and opportunities. DevOps engineers are facing a surge in code volume and speed—often without a corresponding bump in quality. Automation, golden paths and better processes are essential to handle the influx of AI-assisted code. AI can also help streamline repetitive work: writing scripts, maintaining configurations, generating tests or spotting compliance risks.

Eventually, DevOps teams may evolve into ecosystems of human engineers and collaborative AI agents. That vision’s still emerging, but orchestration between tools and agents is the next hurdle. The goal? To let developers and engineers focus more on creative, value-adding tasks—and less on toil.

Still, AI must be used thoughtfully. It’s not a magic fix. It’s a power tool—one that needs skill, discipline and a good understanding of when (and how) to use it.