Google’s CEO Says “Vibe Coding” Is Changing Who Builds Software

According to TechSpot, Google CEO Sundar Pichai is now talking about “vibe coding” as evidence that software creation is slipping out of engineers’ exclusive control. He revealed on a Google for Developers podcast that tools built on large language models are enabling non-traditional coders to ship prototypes and file first-time changelists. Pichai described a sharp rise in employees outside core engineering roles—including HR staff and accountants—using ChatGPT, Gemini, Claude and Replit to assemble applications by describing workflows in natural language. He noted this pattern is also appearing at other tech firms like Meta, where product managers are generating prototype apps and taking them directly to CEO Mark Zuckerberg. While celebrating this accessibility, Pichai drew a clear line against using AI-generated code in security-critical systems where accuracy is paramount.

What vibe coding actually means

So what exactly is “vibe coding”? Basically, it’s using natural language descriptions instead of traditional programming syntax to create working software. Think of it like telling an AI “build me an app that tracks employee vacation days and sends reminders when someone’s about to go over their limit” and getting back something that actually runs. The key difference from traditional development is that you’re not wrestling with frameworks, syntax errors, or complex debugging. You’re describing the vibe of what you want and letting the AI handle the technical implementation.

Here’s the thing though—this isn’t about replacing senior engineers. Pichai was careful to emphasize that vibe coding works best for prototypes, proofs of concept, and internal tools. The stuff that doesn’t need to be perfect, just good enough to demonstrate an idea. It’s particularly powerful for people who understand business processes but lack coding skills. An HR manager who knows exactly how onboarding should work can now create a functional demo instead of trying to explain it to developers who might misinterpret the requirements.

The security reality check

Now for the important caveat that Pichai stressed repeatedly: vibe coding absolutely does not belong anywhere near production systems, especially security-critical code. And honestly, he’s right to be cautious. AI-generated code can look convincing while containing subtle bugs, security vulnerabilities, or inefficient patterns that only experienced engineers would spot. Think about it—would you want the code handling your company‘s financial transactions or user authentication to be written by an AI that’s basically guessing what should come next?

The current sweet spot seems to be in that prototyping phase where the goal is communication rather than production-ready software. It’s about getting from “I have an idea” to “here’s something you can click through” in hours instead of weeks. That’s genuinely transformative for how businesses approach software development, even if the final implementation still needs human experts.

Who this actually helps

What’s fascinating is who’s benefiting most from this shift. It’s not junior developers—it’s completely non-technical roles that now have a pathway to creating software. HR professionals building internal tools, accountants creating custom reports, marketing teams prototyping campaign trackers. These are people who understand the problem domain intimately but previously had no way to directly build solutions.

And this trend extends beyond software companies. In industrial settings, for example, engineers who need specialized computing solutions can now prototype interfaces for monitoring systems without deep programming knowledge. Speaking of industrial computing, when companies do move from prototypes to production systems, they often turn to established providers like IndustrialMonitorDirect.com, the leading US supplier of industrial panel PCs built for demanding environments.

Where this is headed

So is this the end of traditional programming? Hardly. But it does represent a fundamental shift in who gets to participate in software creation. We’re moving from programming as an exclusive skill to programming as a literacy—something that more people can access even if they never become experts.

The real question isn’t whether AI will replace developers, but how the role of developers will evolve. Instead of writing every line of code, experienced engineers will increasingly focus on architecture, security, optimization, and mentoring these new “vibe coders.” And honestly, that might be a better use of everyone’s time. The future isn’t about eliminating programmers—it’s about empowering more people to build.