Vibe Coding: What Happens When Everyone Can Build Software
AI is making it possible for non-developers to build real software. Here's what that means for builders, businesses, and the future of tech.
Key Points
- Vibe coding (conversational programming with AI) is lowering the barrier to software creation, but it’s not a replacement for engineering judgment
- It’s incredibly effective for MVPs and internal tools, but production systems still require understanding what you’re building
- When everyone can code, the real competitive advantage shifts to product sense—knowing what to build and why
The Rise of Conversational Programming
Andrej Karpathy coined the term “vibe coding,” and it’s probably the most accurate description of how software gets built in 2025. The idea is simple: you describe what you want to an AI, iterate on the output, and ship something that works. No CS degree required. No years grinding through algorithms. Just you, Claude or ChatGPT, and an idea.
I’ve been doing this for months now. I built my entire website rebuild with heavy AI assistance despite not being a full-time developer. I rebuilt Openmark’s core features. I’ve prototyped features for projects that would’ve taken me weeks to plan out. The results are real, working software that users actually interact with.
This feels like a fundamental shift. For the first time, the constraint isn’t your ability to code—it’s your ability to articulate what you want built.
What Vibe Coding Actually Is
Let’s be clear about what we’re talking about here. Vibe coding isn’t about writing elaborate prompts and hoping something magical happens. It’s conversational programming. You’re having a dialogue with an AI that understands code, context, and iteration.
You start with a rough idea: “I need a way to track email sign-ups and store them in a database.” You describe the pieces—what data matters, how they connect, what the user experience should feel like. The AI generates code. You review it, ask for changes, question design decisions, and iterate until it actually does what you want.
The key word is iterate. You’re not passive. You’re actively directing the output, catching mistakes, and making architectural decisions. It’s more like pair programming with someone who’s incredibly fast and never gets tired.
What It Isn’t (And This Matters)
Vibe coding is not a replacement for understanding what you’re building. This is where a lot of people get tripped up.
Yes, you can generate working code without knowing how that code functions. You can prompt an AI, get back 200 lines of React, and paste it into your project. It might even work. But the moment something breaks, or you need to add a feature, or security becomes an issue—you’re stuck. You’ve built something you can’t maintain.
The real power of vibe coding isn’t in the code generation. It’s in amplifying your own judgment. If you understand databases, you can have an intelligent conversation about which database to use and why. If you understand APIs, you can catch when the AI suggests something inefficient. If you understand your users’ needs, you can recognize when a feature request is actually a symptom of a deeper problem.
Understanding matters. The code itself? The AI can handle that.
The Pros: Democratization and Speed
Let’s talk about what actually works here. Vibe coding has real, tangible benefits.
First, it genuinely lowers the barrier to entry. I’m not a software engineer. I’ve built things that work at scale without a CS degree, without spending thousands on bootcamps, without the years-long time investment required to become fluent in multiple programming languages. That’s genuinely new.
Second, it’s phenomenally fast for prototyping. In the time it would’ve taken me to plan out the architecture, design the database schema, and hand off specs to a developer, I can have a working MVP in a few hours. Not a throwaway prototype—actual working software with a real database, real APIs, real users.
Third, it lets operational people build their own tools. At my agency, Rotate, our team members can now build internal tools instead of waiting for developers to prioritize their requests. That’s leverage. That’s what everyone wants.
The democratization angle is real. Technical knowledge used to be a gating function. Now it’s more of an accelerant than a requirement.
The Cons: Technical Debt and Real Risks
But let’s not pretend vibe coding is risk-free. There are some genuine downsides.
Technical debt accrues fast. An AI generates working code, not necessarily good code. It might be inefficient, poorly structured, or missing error handling. Ship enough of that, and you’re maintaining a codebase that’s increasingly difficult to work with. You end up either rewriting it or living with a system that’s harder to improve than it should be.
Security is a real concern. An AI might generate code that’s vulnerable to injection attacks, doesn’t properly validate input, or stores sensitive data insecurely. If you don’t understand the code you’re running in production, you can’t catch these issues. And the blast radius can be significant.
There’s also the issue of maintenance. If you build something with vibe coding and it works great for a year, then your dependencies update and things break, or your data grows and performance tanks—do you understand the system well enough to fix it? Or are you back to prompting an AI, hoping it understands the context of your specific system?
These aren’t showstoppers. They’re just real constraints that matter.
Where Vibe Coding Actually Shines
Here’s my honest take: vibe coding is phenomenal for a specific category of problems.
MVPs. Internal tools. Throwaway prototypes. Quick experiments. One-off scripts. Side projects. Places where the value isn’t in the engineering but in the idea itself. In those contexts, the speed and democratization benefits dramatically outweigh the technical debt concerns.
For those projects, vibe coding is a game-changer. You can validate ideas faster. You can build the things you’ve always wanted to build without being blocked by technical constraints. You can ship things that seemed impossible before.
But for production systems that other people depend on? Systems that handle payment, sensitive data, or critical operations? That’s a different calculation. The AI can handle 80% of the implementation, but that final 20% requires actual engineering judgment. You need to understand your system well enough to defend it, maintain it, and scale it.
Think of vibe coding as an amplifier, not a replacement. It amplifies your abilities and your judgment. But you still need to have judgment worth amplifying.
The Real Competitive Advantage
Here’s the thing that keeps me up at night in the good way: when everyone can code, when technical ability stops being a scarce resource, the competitive advantage shifts somewhere else entirely.
It shifts to product sense. Taste. User empathy. The ability to look at a problem and understand not just how to solve it, but whether solving it actually matters. The ability to prioritize ruthlessly, to say no to feature requests that don’t move the needle, to build the core thing that matters instead of everything that’s possible.
That’s always been the hard part. That’s the part no bootcamp teaches. That’s the part that requires intuition, domain knowledge, user research, and a stubborn belief in a particular vision.
Vibe coding means more people can execute on their ideas. That’s powerful. But it also means execution becomes table stakes. The people who win are the ones who know what to build and why—not the people who can build fastest.
I’ve built things with vibe coding that worked technically but didn’t matter to anyone. I’ve also built things that were technically rough but mattered to my users because they solved a real problem in a delightful way. The difference wasn’t the code quality. It was the clarity of the vision.
What’s Actually Changing
We’re living through a weird transition period right now. The tooling is getting better every month. AI models are getting smarter. Vibe coding is moving from “cool experiment” to “actual way to build things.”
The people who are going to win are the ones who get comfortable with this new paradigm without losing their judgment. Who can iterate with AI tools without blindly trusting the output. Who understand that speed matters but quality matters more. Who can ship things that work today and can still be maintained tomorrow.
If you’re not already experimenting with vibe coding, you should be. Not because it’s going to replace engineers (it won’t). But because it’s going to change what engineering work actually is. And the sooner you figure out how to use it effectively, the more you can build.
The future isn’t about who can code fastest. It’s about who understands what should be built, can articulate it clearly, and can iterate relentlessly until it’s right. The code itself? That’s what the AI is for.
If you’re curious about how to actually implement this in practice, I wrote about the AI tools I use every day and how I think about shipping things quickly and imperfectly. For deeper context on how AI is reshaping what we build, see why every business is becoming a software business.