Vibe Coding: What Founders Need to Know
The promise and reality of AI-assisted development in 2026
I watched a founder demo his app last month. He'd built it entirely with AI assistance over a weekend—no prior coding experience. The UI was polished. The features worked. He was, understandably, thrilled.
Then I opened the network tab in my browser. Every button click was sending the user's data to three different analytics services he didn't know he'd installed. The AI had copied code from somewhere, and that code came with trackers. His users' behavior was being sold to advertisers, and he had no idea.
This is not a story about AI being bad. The AI did exactly what he asked. The problem is that he didn't know what questions to ask.
What Vibe Coding Actually Is
Andrej Karpathy coined the term to describe a new way of programming: you describe what you want in plain language, and AI writes the code. You don't need to understand the implementation. You just need to describe the outcome.
I use these tools every day. They're genuinely transformative for certain kinds of work. But "transformative" and "sufficient" are different things.
The gap between them is where projects go wrong.
What AI Does Well
AI excels at pattern-matching. It's seen millions of examples of how to build a login form, so it can produce a login form quickly. It knows the standard way to connect to a database, structure an API, style a button. For anything that follows a well-established pattern, AI is fast and competent.
This makes it exceptional for prototypes. You can validate an idea in hours instead of weeks. You can explore approaches without committing engineering time. You can show investors something real instead of a slide deck.
It's also useful for experienced developers—not as a replacement for thinking, but as a way to skip typing. I describe what I want, the AI generates boilerplate, I review and modify. The time savings are real.
What AI Doesn't Know
AI has no idea what your business actually needs.
It doesn't know that your payment system needs to handle chargebacks gracefully because your customer support team is already overwhelmed. It doesn't know that your data model needs to support the reporting your investors will ask for in six months. It doesn't know that the architectural decision it just made will cost you $40,000 to undo when you hit scale.
It generates code that matches the patterns it's seen. Sometimes those patterns contain security vulnerabilities that were fine in a tutorial but catastrophic in production. Sometimes they include dependencies that will break when the library updates. Sometimes they're inefficient in ways that don't matter for ten users but crash the server at ten thousand.
The code works. That's not the same as the code being right.
The Taste Problem
Here's what I've come to believe: the limiting factor in software development was never typing speed. It was always judgment. Knowing which problems to solve. Knowing which solution fits the context. Knowing what will matter later and what won't.
AI doesn't have taste. It can't tell you that the feature you're asking for will confuse users, or that there's a simpler approach you haven't considered, or that you're solving a symptom instead of the cause. It gives you exactly what you ask for, even when what you're asking for is wrong.
The founders I've seen succeed with AI tools are the ones who already understand software deeply enough to evaluate what the AI produces. They use it as leverage, not as a substitute for expertise. They know which suggestions to accept and which to reject.
The ones who struggle are the ones who accept everything, because they can't tell the difference.
What This Means for Your Project
If you're building a prototype to test an idea, AI tools might be all you need. Ship it, see if anyone cares, iterate based on feedback. Speed matters more than polish at that stage.
If you're building something that handles real money, real data, or real users at scale, you need someone who can evaluate what the AI produces—and more importantly, someone who can ask the right questions in the first place.
The question isn't whether AI can write code. It's whether anyone involved understands the code well enough to take responsibility for it.
I use AI tools extensively in my work—they make me faster without compromising quality. If you're trying to figure out whether your project needs professional development or can be handled with AI-assisted prototyping, let's talk. I'll give you an honest answer.