If you’ve been following tech news over the past year, you’ve likely encountered vibe coding somewhere. Your team might be discussing it. You might have seen it demonstrated at an event or saw it featured in Super Bowl commercials. You might have even tried one of these tools yourself and thought, “is building software actually this easy now?”
The short answer is yes. But also no.
Vibe coding tools produce impressive results, but it’s difficult to discern what’s real capability from what’s effective marketing. So, what is vibe coding? How does it work? And does the value it creates outweigh the risks it introduces? We’ll explore all these questions in this blog!
What is vibe coding?
Let’s start with some history, because vibe coding didn’t get to be what it is overnight.
The groundwork was laid when GitHub Copilot launched in 2021 and changed how developers worked. It was used as an “AI pair programmer” or autocomplete for coding – writing chunks of code for you as you work. Humans (developers mostly) were still very much “in the loop” by utilizing the autocomplete tooling and reviewing the suggestions the AI offered. In the following years, large language models (LLMs) got better and better at predicting what individual snippets of code should look like, and began writing entire functions, classes, and even full applications from natural language prompts.
In 2025, Andrej Karpathy gave what was happening a name. The OpenAI co-founder and former Tesla AI director famously tweeted about “a new kind of coding I call “vibe coding,” where you fully give in to the vibes, embrace exponentials, and forget the code even exists…” The term gained popularity because people were already doing exactly that: describing what they want the software to do (or the vibe of their intended outcome), letting the AI handle the coding and engineering, iteratively refining based on output, and ultimately using the end result.
Today, vibe coding tools are everywhere and are used by millions daily. So what exactly happens when someone is vibe coding? Is it just the AI helping out with coding?
Vibe coding vs. AI-assisted development
With vibe coding’s explosion in popularity, it’s frequently convoluted with AI-assisted development as if they’re the same thing. They’re not, and the distinction between them is really important:
Vibe coding follows a simple, outcome-focused process with no coding or software development experience necessary on the users part. The process begins where the user describes to the AI the outcome or intent for what they want the AI to create in natural language. Next, the AI model then analyzes the input and determines the necessary code structure and logic to achieve the outcome and generates the code. Then, the user then runs or tests the AI-generated code to observe its behavior and assess whether or not it functions and looks as intended. If it happened to do this on the first try, the process could end here – but almost never does. Assuming the output doesn’t work quite how the user envisioned (yet), they iterate on the outcome by additional prompting – continuing the process until it does. Or is close enough. In short, the AI is acting as the developer for the user and the focus of this process is on the outcome: does it do and does it look like what you asked for?
In contrast, AI-assisted development follows a very similar workflow on the surface, but with critical differences in philosophy and execution. The first distinction is the intended user. AI-assisted development is designed for developers or engineers who possess the underlying technical expertise to review code. Likewise, what happens before and after the AI generates the code are different from vibe coding. In AI-assisted development, rather than the AI just diving right in, includes structured planning before any code is written. This could be architecture, design documents, or technical specifications that guid the output of the AI. Likewise, after the AI generates the code the user themself reviews it for correctness, security vulnerabilities, and architectural fit. They verify it meets established standards and they test it beyond just “does this work?”
Summing the differences up: In AI-assisted development the role of the AI is that of an entry level developer or intern on a software team, who is managed and guided by a more senior mentor – that is, the user. In contrast, in vibe coding the AI is the development team, and the user acts more as a Product Owner, focused on the “what,” and not the “how.”
Both vibe coding and AI-assisted development are great tools when applied in the right conditions. The key is knowing where each approach makes sense for you and your business. That said, this blog is about vibe coding, which has some really exciting benefits (even for professional teams) when applied in the right context, so lets move on!
The strategic value of vibe coding
Vibe coding brings many advantages when it’s used responsibly. The benefits it brings can create organizational value that compounds across teams, projects, and business functions. Here are the three core benefits we believe make vibe coding a strategic tool:
1. Condensed time from idea to functional software. The most defining characteristic of vibe coding is speed. Not just coding faster, but collapsing the entire cycle from concept to working software. Individuals or teams can build functional prototypes in hours instead of weeks. Because the building of the prototypes has become a lighter lift, teams and organizations can afford to test more variations and explore more possibilities.
2. Democratizing who can contribute to software creation. Vibe coding opens the door of software creation to almost anyone. Product managers, business analysts, and operations specialists can now create functional tools without waiting for developer bandwidth. Non-software developers are able to turn their ideas into functional applications through vibe coding.
3. Accelerating learning and exploration. When developers come upon unfamiliar frameworks, libraries, architectural patterns, etc. vibe coding provides instant scaffolding for exploration. Instead of spending hours reading documentation or setting up development environments, they’re able to generate sample implementations, test different approaches, and build intuition through hands-on experimentation.
These three benefits have a multiplier effect when vibe coding is used strategically. Speed enables more experimentations, democratization unlocks capacity, and exploration reduces uncertainty. Together, these let organizations test ideas faster and make better-informed decisions. However, we believe it’s important to apply vibe coding conditionally, which means using it where rapid iteration and learning are the most important factors, and not using it as a replacement for disciplined engineering on production systems.
The risks vibe coding introduces
As we previously discussed, vibe coding’s approach to software creation makes it available to individuals who aren’t technical, and the output is accepted and deployed when it functions as described. However, this approach to software development introduces some risks that shouldn’t be overlooked:
1. Security vulnerabilities from unverified code. Because the LLMs that vibe coding utilizes are trained on mixed data, they can reproduce insecure code without necessarily recognizing that it’s unsafe (and more importantly, telling the user it might be unsafe). When users rely on the AI to deliver a product without inspecting or understanding the code, the results can contain vulnerable patterns like outdated libraries, unsafe API usage, input-validation errors, insecure dependencies and more.
2. Loss of code quality, maintainability, and technical debt. The speed of vibe coding is its strongest benefit, but it also is one of the risks. The vibe coding process encourages quick generation and iterations of working code without the structure and discipline of software development best practices (like secure coding methods, documentation, testing, architectural standards, intentional design decisions, and more). When you develop software in this way, over time the codebase tends to accumulate technical debt, while simultaneously becoming more difficult to scale and maintain.
3. Provenance and ownership ambiguity. Vibe coding platforms generally don’t provide source citations for the code or creative assets they use in their output. Because of this, it’s difficult (if not impossible) to verify whether the outputs were derived from copyrighted works, incorporated licensed material, and much more. This creates legal and compliance risks, especially if vibe coded products move into commercial production.
The risks don’t mean that you should avoid vibe coding entirely, but they do require thoughtful consideration, especially when using the approach for commercial purposes. We recommend understanding the risks – and taking specific action to mitigate them – before you adopt vibe coding into your organization.
Closing thoughts
Vibe coding, like AI, isn’t just a trend that’s going to disappear once the novelty wears off. It’s a tool that offers real and tangible value for teams and organizations, particularly when it’s applied to prototyping, expanding who can contribute to software creation, and enabling different approaches to learning and exploration. That said, like any powerful tool, vibe coding requires thoughtful and intentional implementation. Organizations bear the responsibility of due diligence to define (and constrain) the acceptable use of vibe coding within their company.
Vibe coding is just one example of how AI is reshaping the way companies operate. The world has seen AI make enormous advancements over the past few years (some good, and some bad), and we see them continuously evolving.
With so much change happening so quickly, it’s increasingly difficult to discern which AI technologies are genuinely applicable and valuable for your specific team, company, and objectives. If you’re exploring where AI can become an asset for your organization, beyond the latest commercials and trends, we’d love to talk! Email info@calavista.com and get the conversation started.