The Next.js Security Wake-Up Call for Vibe Coders Everywhere

It’s Monday morning. You’ve barely opened your eyes and suddenly remember that you promised to build a brand-new app by the stakeholder meeting this afternoon. In any sensible world, this would be a recipe for disaster. But now, we have something different — something called “vibe coding.”

You simply mutter your wish for “a frictionless e-commerce platform with user-authentication and real-time chat,” and poof, like magic, the AI generates the entire codebase.

Need a fancy UI? With another passing thought, another chunk of polished code appears. After all, who has time to worry about syntax when you can vibe your way to a finished product?

But here’s the catch: as the excitement around “vibe coding” continues to grow, an unsettling question surfaces — what happens when we no longer truly understand the inner workings of our code?

This worry recently became all too real with the discovery of a significant security vulnerability in Next.js, a hugely popular React framework.

Astonishingly, a single, deceptively simple HTTP header could disable critical middleware checks entirely — turning thousands of meticulously crafted websites into open targets overnight. The loophole boiled down to mismanaging how Next.js tracks repeated calls to its middleware, effectively allowing any attacker to trick the system into skipping security checks.

If you’re running a Next.js application, here’s how to fix or mitigate the risk right now:

1. Upgrade to the latest version, which should be >=15.2.3

2. If you can’t update right away, temporarily block the vulnerable header at your web server level like this:

Let’s be clear, this vulnerability wasn’t caused by “vibe coding”. It was a case of an honest mistake... unfortunately just in a widely used framework.

However, all developers should take note:

When a popular framework like Next.js ships with a major vulnerability, it underscores the dangers of shipping code we haven’t deeply inspected. Even if the problem is in a third-party library, we need people who truly understand how that library works — or at least have the diligence to spot something that looks suspicious.

Therefore, if we embrace a coding style that relies on AI to handle the nitty-gritty without truly understanding those details ourselves, who makes sure our house of cards doesn’t come crashing down in the future?

In this newsletter:

• We’ll first explore how “vibe coding” burst onto the scene — tracing its origins, celebrating its playful spirit, and examining early success stories that captivated developers everywhere.

• Next, we’ll examine cautionary tales, highlighting the pitfalls of trusting automated code without knowing the specifics of what it does.

• Finally, we’ll circle back to discuss the real limitations of “coding by vibes,” underscoring why strong foundational knowledge has become more critical than ever in today’s rapidly evolving AI-driven landscape.

Let’s get started.

What exactly is “vibe coding”?#

Imagine if coding were like cooking a gourmet meal. Traditionally, you’d meticulously follow a detailed recipe, measuring every ingredient precisely. But now, picture telling an expert chef, “I’m feeling something spicy with a touch of sweetness,” and having them whip up an extraordinary meal without needing to give further instructions. That’s precisely the spirit behind vibe coding.

The term was recently coined by Andrej Karpathy, a prominent computer scientist and AI pioneer who co-founded OpenAI and former head of Tesla’s AI team. Karpathy described vibe coding as a new, AI-driven approach where you essentially “forget that the code even exists.” In his viral tweet, he explained that you simply describe features or changes in everyday language, letting advanced language models handle the heavy lifting, generating entire codebases with minimal human effort.

Think of it as having an ongoing conversation with your personal coding assistant: you throw out ideas, and the AI conjures the code. Karpathy humorously confessed to just hitting “Accept All” on the AI’s suggested code changes, even letting the AI handle bug fixes... though occasionally, that involves random tweaks when the AI gets stuck. In his experience, vibe coding is incredibly effective for quick, throwaway projects – fun, fast, and excellent for prototyping – but it doesn’t yet replace the careful, detail-oriented work required for robust software engineering.

What are the early success stories of vibe coding?#

Despite its freeform nature, vibe coding has rapidly proven itself for quick prototyping and creative development. For example, imagine having a turbo-boost button that turns ideas into functional demos in hours rather than weeks.

• Pieter Levels demonstrated these advantages by using Cursor, an AI-powered IDE, to create a simple yet engaging web game. Now, here’s the kicker: Levels is no one-hit-wonder — he’s founded over 40 startups, many of which are not only operational but profitable. As Levels put it, “I had the idea at breakfast, and by dinner, it was live with 5,000 users.” That particular game reportedly earned $50,000 in monthly revenue within just a few weeks. That’s the dream: a fleeting thought in the morning becomes a real, income-generating product by sundown.

• It’s not just solo developers. Startups – especially those in programs like Y Combinator – also embrace vibe coding to ship MVPs at breakneck speed. In one YC batch, roughly 25% of the startups had almost entirely AI-generated codebases. This compresses what once took months into mere days — sometimes just a few carefully phrased prompts away from a working prototype.

• Another exciting element is how vibe coding empowers non-programmers. Individuals who once found coding daunting can now build functional software by simply describing their ideas to an AI assistant. It’s a big step toward democratizing the development process.

So far, it sounds like a fairytale: code magically appears, freeing you to focus on strategy, creativity, and user experience. That’s the powerful allure behind vibe coding.

Where do we run into trouble with vibe coding?#

The promise of vibe coding is exciting and powerful, but it’s not a magical solution — at least not yet. While it has captured widespread attention since Andrej Karpathy introduced the term, it’s important to recognize what vibe coding truly entails versus what it doesn’t. Vibe coding isn’t just any programming assisted by AI; it’s specifically coding by fully trusting AI to handle almost everything without reviewing or even fully understanding the code it produces.

Here’s why seasoned software engineers aren’t handing over their keyboards just yet:

• When projects grow beyond simple prototypes, vibe coding can quickly spiral into a tangled mess. AI-generated codebases can rapidly become large, disorganized, and difficult to maintain. Even the AI can lose track of essential details like dependencies and imports — or worse, hallucinate functions or APIs that don’t actually exist. Without careful human oversight, your codebase can become a confusing, tough labyrinth to manage.

• Relying on AI-generated code without proper review can unintentionally introduce serious vulnerabilities into your projects, such as SQL injection points, unsecured APIs, or missing authentication. Vibe coding’s “set it and forget it” mindset might make you overlook crucial security checks, potentially releasing dangerous and flawed software into production.

• Vibe coding feels magical when it works... but when issues inevitably arise, debugging quickly becomes a nightmare. Without understanding the code’s underlying logic, solving even simple bugs can feel impossible. Debugging often reduces to frustrating guesswork, randomly prompting the AI for fixes and hoping something sticks.

• For simple demos and quick prototypes, vibe coding is fantastic. However, once complexity increases, AI tends to falter. Nuanced tasks requiring deep domain knowledge or clear, detailed instructions often trip up AI assistants. It's like asking a genie for a wish without being precise: you’ll receive something, but probably not exactly what you envisioned.

Remember, responsible software development has always been more than just typing code. It involves writing maintainable, understandable, secure, and efficient solutions. AI can do the grunt work, but an experienced developer must review, test, and ensure everything holds up under real-world conditions.

This leads us to a key principle: “vibe coding” should mean “I know how this works, but I’m letting AI handle the routine parts,” not “I have no idea how this works, and maybe AI will figure it out!”

If you’re comfortable with the underlying tech stack, letting AI handle boilerplate can boost your productivity enormously. But ignoring fundamental architecture and security concerns is a recipe for the kind of wide-scale fiasco we saw with Next.js’s middleware flaw.

How to vibe code responsibly#

Let’s say I’m the CEO and co-founder of Educative (which, as it happens, I am!), and I decided to “vibe code” a brand-new product for our platform. First reaction: “But wait, I’ve got a whole company to run! Am I really going to trust AI to do all that coding?” The short answer: partly, yes — but with some important guardrails. Let me show you how:

1. Before you jump into any coding, know what you’re actually building. I start with GPT (my go-to LLM these days) and keep refining a PRD until it’s crystal clear. A neat trick? I ask GPT to format it so even a junior engineer can follow along. That forces the document to be more thorough and explanatory. Think of it as giving your ideas a reality check before you fling them at an AI IDE.

2. Now that I have a well-defined PRD, I hand it off to my AI assistant. Whether it’s Cursor, Windsurf, or Claude Code, the principle is the same: the AI gets the plan, then generates the initial code. This is like telling your personal chef, “Here’s my grocery list — now whip me up a feast!”

3. Inevitably, AI hits snags. That’s when you treat it like a pair programmer: you step in, write some code yourself, or clarify the prompt. Don’t be shy about starting over if things get messy. We’re here to preserve the vibe, not wrestle with a tangled codebase that even the AI forgot how to handle.

4. You don’t want it guessing your tech stack. The more precise you are, the better the output (and fewer regrets later). If you imagine a stunning 3D game (e.g., that airplane demo web game example we talked about) tell your AI coder explicitly, “Use Three.js for rendering!” or “Pull in these specific libraries.”

5. Resist the temptation to type a single monster prompt (“Build me a website, please — bye!”) and hope for magic. Instead, break down your instructions.

6. Once you have a chunk of code, run it by a second LLM or tool, e.g., Claude, ChatGPT, or even a static analysis tool. These AI assistants can spot oddities or potential security flaws you might miss. Just be mindful of context window limits (especially if your codebase grows large), and feed each chunk in for a thorough inspection. However, good testing (e.g., unit testing) remains crucial, especially with AI-generated code, so don’t forget that!

Solid fundamentals are more important than ever#

Now, here’s the reality check: no matter how slick your vibe-coding routine becomes, solid engineering know-how remains your safety net.

You need to grasp at least the basics of what your code should be doing — enough to spot weirdness or vulnerabilities. Think of vibe coding as a turbo boost for your workflow... not an autopilot that flies the plane without you in the cockpit.

When you combine healthy skepticism, domain expertise, and a clear plan (thorough PRD!) with the creative power of AI coding tools, you get the best of both worlds: speed, efficiency, and enough rigor to avoid shipping a giant security hole to production. That’s the vibe we’re aiming for.

You can learn more about web security, coding with AI, and working with Next.js with one of our courses below: