What is Vibe Coding and How Does It Work?

Development and writing code, as we know it, has always been interpreted as a lengthy process done by software developers with a strong technical background and years of experience. Getting from concept to finished result took months, in some cases even up to a year, depending on the complexity of the project. 

Now, we’re noticing a shift. Enthusiasts and entrepreneurs are coming up with fully functional projects in less than a week. Zero experience, just an idea. How is this possible?

Thanks to vibe coding, a term coined by one of the co-founders of OpenAI, Andrej Karpathy, ideas become reality in a matter of days. But what is vibe coding really, and how is it helping people achieve results at super speeds?

In this blog article, we’ll dive deeper into what vibe coding is, the pros and cons of this approach, and ways to apply it to development processes mindfully.

What is vibe coding?

Vibe coding, chosen as the Collins Dictionary word of 2025, refers to a development approach that relies on the outputs of LLMs, allowing anyone interested (regardless of their experience or level of knowledge) to generate, refine, and debug working code. The developers’ input prompts are usually descriptive, explaining the main ideas and functions they’ve intended for their project; these prompts can be as simple as:

“Make me an app that shows the weather, with a dropdown for a country and C°/F° choice.”

As the term’s author has mentioned, “...the hottest new programming language is English,” meaning the approach eliminates the need to learn specific programming languages to be able to make your ideas come to life.

The name reflects the deliberately reckless approach of fully giving into the vibes by handing over the hard work to LLMs, and shifting the developer's role from manual coding to guiding, testing, and giving feedback prompts to fix any mistakes. 

In simple terms, it is an exploratory approach to coding that lets the developer trust the AI completely, focusing primarily on what the code does in the end, not on how it looks or is structured. Since these LLMs are becoming more powerful with each release, the biggest payoff from vibe coding is speed and efficiency, replacing days of manual work with hours or even minutes of work. 

What are the results of vibe coding?

Vibe coding can take a project from concept to launch in a single night, and for many popular projects, like OpenClaw.ai and RentAHuman.ai, that's exactly how it happened. 

In reality, however, these projects don’t often gain popularity for being innovative or solving real problems. Instead, the weekly news cycle is full of security, accountability, and quality failures from projects exactly like these.

One widely discussed example is the aforementioned OpenClaw AI agent, developed by vibe coder Peter Steinberger, who later joined OpenAI after the project gained popularity. The agent serves as an interface for autonomous workflows across supported services, running locally, and is designed to integrate with existing LLMs, such as ChatGPT, Claude, and others. 

Due to its design, however, it has raised many security and privacy concerns from cybersecurity researchers and technology journalists. The agent requires extensive access to users’ email accounts, calendars, messaging apps, and other sources rich in sensitive, private information. And, unfortunately, after Cisco’s AI security research team tested the project, it was discovered to have extracted data and injected prompts without user awareness. 

Since these projects are rarely checked before or maintained after launch, it becomes hard to identify mistakes in the code, leaving vulnerabilities unaddressed. This example shows how fragile vibe-coded projects can be, with new ones appearing daily, keeping cybersecurity researchers constantly vigilant.

How does vibe coding work?

Vibe coding can be approached in two ways: go all in—fully trusting the LLM, acting as a facilitator and tester—or treat it as one tool within a more deliberate development process. The latter is the approach we'd recommend for anything beyond a throwaway prototype.

In practice, responsible vibe coding looks something like this: 

• Start by defining the project's scope and constraints clearly before touching any LLM. The more specific your initial prompt, the less cleanup you'll do later. 
• From there, build incrementally. Generate one feature or module at a time, test it in isolation, and only move forward once it behaves as expected. 
• Avoid the temptation to generate large blocks of code at once. The more the LLM produces in a single pass, the harder it becomes to trace where something goes wrong.

Security and maintainability checks shouldn't be left to the end. After each meaningful chunk of generated code, review it (or have a developer review it) for obvious vulnerabilities, hardcoded credentials, or logic that makes undocumented assumptions. Treat generated code with the same skepticism you'd apply to code from an unfamiliar contributor.

The right choice of tools depends on your use case: 

• BarkoAgent stands out for agentic workflows where the AI needs to take sequences of actions autonomously rather than simply generating code on request, making it a strong fit for automation-heavy projects. 
• Claude and ChatGPT excel at conversational iteration and explaining generated code, making them well-suited for users who want to understand what they're building. 
• Google AI Studio and Firebase Studio are stronger choices when the project needs tight integration with Google's infrastructure from the start. 
• Cursor and GitHub Copilot are worth considering for those working directly in an IDE who want AI assistance embedded in their existing workflow rather than a separate chat interface.

The common thread across all of them: none are a substitute for knowing what you want to build and being able to verify that what was built actually does it.

Benefits of vibe coding

Before implementing vibe coding into your daily development processes, it’s important to evaluate the “what’s in it for me?” beforehand. Knowing the key benefits and challenges will prepare you to have the right expectations. First, let’s start with the benefits.

1. Faster software development in the early stages

One of the key benefits of vibe coding is the speed at which projects can initially be thought out, designed, built, and released. The bottleneck is no longer how fast you can write code; it's how clearly you can think about what you want. For most projects, that's a dramatic shift in where the real work happens.

The author of the term describes the development approach as best suited for “throwaway weekend projects”—proof that vibe coding can deliver projects to release faster than anything the industry has seen before.

This acceleration stems from bypassing the tedious parts of development, like boilerplate code, API integrations, database schema design, and frontend scaffolding, which traditionally consume days or weeks even for experienced developers. 

2. Vibe-coders don’t require extensive knowledge

Developers don’t need to know, or even understand, code or technical aspects before beginning their projects. All it really takes is a concrete understanding of how the results should look, as well as the ability to check for mistakes. 

This opens the door to software development by removing traditional barriers. Anyone, even without a computer science degree or programming experience, can describe their idea in plain language and get functional code. A medical researcher who understands a problem inside out but can't write a line of Python can now build a working tool to solve it. This isn’t just a convenience, it's a fundamental shift in who gets to build solutions.

3. The tech needed for vibe coding is easily accessible

Vibe coding LLMs are available to virtually anyone with an internet connection. Because these tools are easy to use, widely popular, and available for free, any person with an idea and a few hours can start building something real.

The popularity of these tools also means every common question has been answered in public forums, YouTube tutorials, and documentation. If you get stuck, someone else has likely already solved your problem and shared the solution online. 

4. Vibe coding comes with low upfront costs

Even when free versions don’t seem like enough, subscriptions start at just €15 to €25 a month per person, which doesn’t even begin to compare with all the upfront costs of those who wanted to start coding just 10 years ago, including courses, certifications, development tools, and years of study.

There's no need to purchase expensive development environments, server infrastructure, or licenses. Cloud deployment options remain affordable and even free for small projects. The cost of being wrong used to be a year of your life and thousands in education. Now it's a weekend and a cancelled subscription. That changes how boldly people are willing to experiment.

Challenges of vibe coding

Although all the benefits of vibe coding create seemingly infinite opportunities and high hopes, it’s important to also look into the negatives and challenges of vibe coding. As good as it sounds, there are always two sides to every coin, so let’s look at the other side.

1. Slower software development in the later stages

Because vibe coding relies entirely on the LLM's outputs, it can introduce security vulnerabilities, maintainability issues, and other bugs. Although projects can take only days to build, fixing the mistakes often takes much longer. This erases the initial speed advantage once integration and testing begin.

When projects are created quickly, without much attention to detail, issues start to accumulate. Most of the time, these issues only surface once the software is already in use. Moreover, a function that appears to work in isolation may silently make incorrect assumptions about the systems it interacts with. These assumptions can be (and often are) wrong, creating conflicts between systems.

2. Fixing problems will require expertise you likely don’t have

Issues in vibe-coded projects, security vulnerabilities, performance bottlenecks, or architectural flaws, can only be effectively resolved by experienced developers. You can't simply ask the LLM to fix these issues. You must understand the underlying principles to evaluate whether the solution is actually correct. 

This creates a paradox: vibe coding technically promises to democratize development and make it more available by reducing reliance on senior developers, but it actually concentrates expert labor in the debugging phase, where it's least efficient. An expert must reverse-engineer unfamiliar code to understand the model's implicit assumptions before they can even begin fixing problems. 

This shifts the burden from the beginning of development—where anyone can write requirements—to the end, where only experts can untangle the mess. The result is that vibe coding doesn't reduce the need for expertise, it instead defers it to the most expensive and disruptive phase of the project.

3. High maintenance costs and labor

Vibe-coded projects incur significantly higher maintenance costs than traditionally developed software because the code lacks the intentional design and clarity that make systems easy to modify and support. 

Every bug fix, feature addition, or infrastructure upgrade requires expert developers to spend time understanding unfamiliar code before making changes, adding overhead to even routine maintenance tasks. 

The accumulated technical debt from rushed generation means that simple updates often trigger cascading failures in other parts of the system, requiring developers to audit and potentially rewrite multiple modules. Maintenance becomes a constant firefighting operation rather than planned, scheduled work.

4. Not applicable to all projects

The challenges of vibe coding are context-dependent and don't universally apply across all software development scenarios. For short-lived projects like prototypes, proofs of concept, or internal tools that will be used once and discarded, the maintenance burden and long-term technical debt are irrelevant concerns. 

Similarly, vibe coding works well for one-off scripts, data processing tasks, or automation tools that operate in isolation without complex dependencies or security requirements. 

The real problems emerge in projects designed for longevity—production systems with evolving requirements, codebases that multiple teams will inherit, or software handling sensitive data or critical business logic. Projects operating under strict compliance or security standards cannot absorb the risk of hidden vulnerabilities that vibe coding introduces.

The question isn't whether vibe coding is good or bad; it's whether the project type can survive its specific weaknesses. 

5. Vibe coding produces unpredictable results

Vibe coding introduces fundamental unpredictability into the development process because LLM outputs are non-deterministic. Namely, the same prompt can generate different code on different runs, with varying quality, security implications, and performance characteristics. 

This makes it impossible to reliably estimate project timelines. For example, a feature that generates correctly on the first attempt might require five regenerations the next time you need something similar. 

The debugging phase becomes equally unpredictable, because you can't know in advance which generated functions contain subtle bugs or whether those bugs will emerge immediately or only under specific edge cases encountered weeks later in production. 

Unlike traditional development, where careful planning and incremental testing provide visibility into progress and remaining work, vibe coding offers no predictive model. A project that seems 80% complete can suddenly reveal critical issues that require extensive rework.

Wrapping up on the vibe

Vibe coding isn't a revolution in software development, it's a redistribution of effort. The objective shifts from writing code to knowing what to ask for from building to debugging, from upfront investment to ongoing maintenance. For the right projects, that trade-off is genuinely worth making. For the wrong ones, it creates more problems than it solves.

The honest truth is that vibe coding is a powerful tool with a narrow ideal use case—and a much wider actual use case. Most people using it are pushing it beyond what it handles well, often without realizing it until something breaks in production. That's not an argument against using it, it's an argument to go in with eyes wide open. Understand what you're trading, build in the checkpoints, and don't mistake speed at the start for simplicity at the end.

The developers who will get the most out of vibe coding are the ones who treat it as a collaborator to be verified, not a solution to be trusted. The ones who forget that distinction are the ones keeping cybersecurity researchers busy.