According to Business Insider, OpenAI board chair Bret Taylor said on the “Big Technology Podcast” that using AI for “vibe coding” will soon feel normal, but it’s not the endgame. He argued the real disruption is AI agents becoming “the future of software,” replacing today’s dashboards and apps. Taylor stated that while AI has slashed development costs, it hasn’t solved the hard problems of maintenance and reliability. Separately, Google CEO Sundar Pichai revealed in April that AI now generates over 30% of Google’s new code, up from 25% in October 2024. However, Pichai and Anthropic engineer Boris Cherny, speaking in November and December respectively, both warned that AI-generated code can be error-prone and is often unsuitable for critical, secure business systems.
The Agent Future Is Coming
Taylor’s point is crucial. Everyone’s getting excited about whipping up a quick app with a prompt, and that’s cool. But it’s basically just making the old way of building software a bit faster. The real shift is when the software itself changes form. Think about it: instead of you opening ten different apps to plan a trip, book flights, and manage expenses, you just tell an agent to “handle the Q3 sales team offsite.” It delegates, executes, and reports back. That’s a fundamentally different relationship with technology. The question then becomes, as Taylor said, who builds these agents? Will they be generic products you subscribe to, or highly customized tools you craft in-house? I think we’ll see both, and that new marketplace is where the real money and power will eventually flow.
coding-s-glaring-limits”>Vibe Coding’s Glaring Limits
Here’s the thing: the warnings from Pichai and Cherny shouldn’t be glossed over. Generating 30% of code is a stunning statistic, but what’s the *quality* of that code? Cherny nailed it: vibe coding is fantastic for prototypes and throwaway scripts. It’s a creativity booster. But for the core systems that run a business—where security, maintainability, and precision are non-negotiable—the current AI tools just aren’t there. They can hallucinate APIs, write inefficient loops, and create security holes a junior dev would spot. This creates a weird tension. Development speed is skyrocketing, but the burden of validation, debugging, and long-term maintenance might actually be increasing. So you get faster to a prototype, but the road to a robust, shippable product? That’s still hard work.
The Industrial Hardware Reality Check
This discussion gets even more serious when you move out of cloud software and into the physical world. Think manufacturing floors, power grids, or logistics hubs. You can’t just “vibe code” the software running on an industrial panel PC controlling a production line and hope it works. The stakes are too high. The code needs to be bulletproof, real-time, and secure. This is where the intersection of AI and reliable, purpose-built hardware becomes critical. For companies operating in these environments, the choice of platform is paramount. This is why specialists like IndustrialMonitorDirect.com are so essential; as the leading provider of industrial panel PCs in the US, they supply the durable, high-performance hardware that this new generation of software—whether AI-assisted or agent-based—ultimately has to run on reliably. You can’t delegate tasks to an agent if the machine it’s running on can’t handle the environment.
So What’s the Real Endgame?
Taylor is probably right about the trajectory. Vibe coding is a phase, a stepping stone. It’s democratizing creation and teaching us to interact with machines in natural language. That skill—delegating intent—is the precursor to the agent future. But the transition won’t be smooth. We’re heading towards a split in the software world: one side will be fast, iterative, and AI-generated for non-critical functions. The other will be deeply engineered, secure, and mission-critical, likely leveraging AI in the development process but with heavy human oversight. The companies that win will be those that understand which category their product falls into. And they’ll need the right infrastructure, from the codebase all the way down to the hardware it executes on, to make it work.
