What Is Vibe Coding? Definition, Examples & How to Get Started

Vibe coding is a software development approach that lets non-technical users create and change software by describing desired functionality in natural language and letting AI generate the result. Instead of writing every line of code yourself, you tell the vibe coding tool what the software should do, connect your tools, and review what it generates. Then, you refine the result until it works the way you intended.

So, what does vibe coding mean for your business? Conversational AI makes app building much easier and lets translate your valuable business knowledge into the requirements the AI uses to build the app. However, there are pros and cons to keep in mind as you build.

In this article, we explain how vibe coding works, how it compares with other types of coding, benefits and limitations, and how to vibe code an app customized to your process.

Key Takeaways

• Vibe coding lets you build software by describing what you want in plain language, while AI generates the app behind it.
• The term comes from AI researcher Andrej Karpathy, who described handing the build over to AI and choosing to "forget that the code even exists."
• Gartner projects that 75% of enterprise software engineers will use AI code assistants by 2028. Vibe coding brings that same shift to business teams everywhere, not just developers.
• Vibe coding makes software creation fast and accessible to people without a programming background, but it still carries security risks.
• The approach works best when the person building the app already knows the process well enough to catch gaps and make the right calls, not as a replacement for that knowledge.
• Five risks deserve attention before you rely on a vibe-coded app: incorrect or missing data, duplicate actions, unclear permissions, failed external connections, and missing ownership.

How Does Vibe Coding Work?

Prompts are the foundation of vibe coding, meaning you can use natural-language descriptions to tell AI to build software for your workflows. The term was coined in 2025 by AI researcher Andrej Karpathy, who described handing the build over to AI and choosing to "forget that the code even exists."

A vibe coding process typically looks something like this:

• Describe what you want to build: Write a prompt in plain language explaining the app, website, or tool you want.
• Let AI build it: The AI generates the code and creates the app's functionality, interface, database, and other supporting features.
• Test your app: Preview the app and try out its features to see what works and what needs improvement.
• Refine the app: Tell the AI what to change or fix and it updates the app based on your feedback.
• Deploy and share: Repeat the process until the app meets your needs, then publish and share it with your team.

If you manage maintenance work, for instance, you could explain how requests move through your team from the initial report to a completed repair, then tell the AI what you want the software to handle along the way. A maintenance app might need to report equipment problems, assign repair work, track each request's status, and record completed repairs.

You don't need to explain how to program the fields, screens, or rules that make those functions work. Instead, describe what the app needs to do, review what it generates, and give the AI more direction until the app works as intended.

For example, a maintenance manager might notice that an approval step is missing or the app doesn't account for work that can't be completed right away. You share that feedback in the next prompt, and the AI updates the app accordingly.

How Vibe Coding Compares With Coding and No-Code Tools

Vibe coding differs from no-code tools and manual coding in how the app is built. With vibe coding, you describe the app you want in natural language, and AI generates the software. No-code tools require configuring the app through a visual interface, while manual coding requires writing the underlying code.

What's unique about the conversational nature of vibe coding is how directly you can bring your process knowledge into the build. After all, you know your workflows best. Vibe coding processes allow you to explain what you need in basic language and then make any required tweaks to what the AI creates so that it fits your process perfectly. Y

Want to learn more? Read our guide on low-code, no-code, and vibe coding.

Vibe Coding Pros and Cons

By replacing much of the manual coding process with conversational prompts, vibe coding makes software development more accessible to people without programming experience. Gartner projects that 75% of enterprise software engineers will use AI code assistants by 2028, and vibe coding brings that same shift to business teams, not just developers. It helps people turn ideas into working apps faster, but it also comes with limitations around accuracy, security, and long-term maintenance. Here's what to consider.

Vibe Coding Benefits

• Accessible to non-developers: You can build software by describing what you need in plain language without having to learn programming syntax.
• Faster development: The app gets built as you describe it, which helps you turn your idea or process into a working prototype faster.
• Lower barrier to entry and experimentation: You can test ideas, build prototypes, make changes, and explore ideas without committing to a lengthy (and expensive) development process.
• Easy iteration: Your process is bound to change, and vibe coding lets you tweak and change your app quickly and easily adjust features, layouts, and functionality.
• Customized apps based on your business: You can create apps tailored to your specific workflows, business processes, goals, and operational needs in a way that off-the-shelf software can't be configured.
• Lower costs and greater independence: Build tools for everyday work challenges without waiting for developers or paying for expensive custom software.

Vibe Coding Limitations

• Inconsistent results: AI may misunderstand your instructions or produce features that don't work as expected.
• Maintenance challenges: Apps can become harder to update, debug, and maintain as they grow in complexity.
• Data and integration constraints: Connecting to existing tools, managing permissions, and handling sensitive data may require additional expertise and careful configuration.
• Governance and scalability concerns: Apps built without appropriate oversight can lack the security and controls needed for organization-wide use.

The Security Debt: Addressing Vibe Coding Risks

Speed has a cost. Every shortcut gets paid back later if nobody catches it first. Engineers call this technical debt. With vibe coding, this is called "security debt" and refers to the gap between an app that runs and an app you can trust with real data, real permissions, and real consequences.

According to Sonar's 2026 State of Code Developer Survey, only 48% of developers using AI coding tools say they consistently verify the AI-generated output they commit. That gap between generating and verifying is exactly where security debt builds up.

Here are the five main risks to look out for and what to do about them:

Risk 1: Incorrect and Missing Data

The risk: Sample data may not expose the problems your app will face in everyday use, such as blank fields, incorrect values, and unexpected formats.

What to do: Your first trial should include testing the app with synthetic data that deliberately includes edge cases (such as missing, incorrect, or unusually formatted values) instead of relying on only sample data. Test the app with entries that contain deliberate errors or missing information to see how it responds, then adjust your prompts or rules until the app behaves as needed.

Risk 2: Duplicate Actions and Repeated Events

The risk: If a user submits the same request more than once, the app needs to know whether those submissions represent separate tasks or the same task.

What to do: Run repeated submissions and triggering events on purpose. Define what constitutes a duplicate for your specific workflow, then specify how the app should respond.

Risk 3: Unclear Record Permissions and Access

The risk: Different people involved in the process may need different levels of access, so it's important to define clear rules and test permissions before the app is published.

What to do: A role-by-role test can confirm what each person can view or change before you introduce live business data.

Risk 4: Failed External Actions

The risk: An app that connects to external software also needs to account for actions that fail due to upstream or downstream issues. A connection might stop working, a required record might be missing, or a connected service might fail to complete an action.

What to do: Test failed connections to determine what should happen when an external action fails and who needs to handle it.

Risk 5: Missing Ongoing Ownership

The risk: An application that functions as expected at launch still needs attention as business needs change. Workflows shift over time, and changes to connected software can make fields in your app obsolete.

What to do: Before rolling the app out to your team, designate an owner who oversees future app changes and brings in a technically qualified reviewer when those changes could expose sensitive data or disrupt important business operations.

How to Vibe Code Your First App

Chances are you have an annoying, time-consuming, manual process in your head right now that you're thinking might be a good fit for an app. Here's how you can build it:

Step 1: Scope Your Process

Choose a repeatable internal process you already know well. A familiar workflow makes it easier to spot when the AI misunderstands a rule or takes the process in the wrong direction.

Pick something with clear boundaries and an outcome you can check, and know who will use the app before you start. A lower-risk internal process gives you room to learn the build-and-refine cycle before you try it with sensitive information or work that carries bigger consequences.

Before you write a single prompt, answer these questions:

• Users: Who needs to use the app or act on its information?
• Records: What information does the process depend on and do you have data you can import?
• Rules: What should happen under normal and exceptional conditions?
• Expected outcome: What should be true when the process works correctly?
• Systems: Which tools does this process already touch, like a help desk, Slack, or email, and does the app need to read from or write to them?

We talked about a maintenance example earlier. Here's what that looks like answered for that workflow:

• Users: Facilities staff submit requests. A supervisor assigns them. Technicians update status.
• Records: Equipment ID, issue description, priority, assigned technician, status, completion date.
• Rules: Urgent requests notify the supervisor immediately. A request can't close without a completion note.
• Expected outcome: Every request has an owner, a status, and a record of how it was resolved.
• Systems: The help desk ticket for this request needs its status updated when the work is marked complete.

Step 2: Connect Your Tools & Enter Your Prompt

Pave connects to over 350+ tools so your app can read and write between systems. Set up the connection once, and every workflow in the app can use it from then on. Credentials stay encrypted, and the connection runs in the background.

Then enter your single plain-language prompt, the way you'd explain the process to a new hire. The maintenance example above would look something like this:

"Build an app where facilities staff submit maintenance requests with an equipment ID, issue description, and priority. A supervisor assigns each request to a technician. Urgent requests notify the supervisor right away. A request can't be marked complete without a completion note, and when it's marked complete, update the matching ticket in our help desk."

If you have an Excel or spreadsheet file with a ton of data, some tools like Pave allow you to import that data directly. Learn how to convert an existing spreadsheet into an app.

Step 3: Make Your Updates

Pave builds the data, the interface, and the logic from your description, all in draft, so nothing goes live till you're ready to hit that one-click publish. From here, you refine it the same way you'd revise a conversation:

• Keep prompting to add fields, change what a view shows, or adjust a rule
• Use the Direct Edit feature to update tables and fields instantly
• Roll back to an earlier version

Pave will also ask you things your first description didn't cover, like clarifying workflows or how to tell two similar requests apart.

Step 4: Test Your App

Before you publish, run the app through the scenarios your first description didn't anticipate, like a request missing a field, the same request submitted twice, or a user trying to see or edit something they shouldn't. The five risks covered earlier are exactly what to check for here. Catching them now costs you a few minutes, but catching them after your team depends on the app costs a lot more.

Step 5: Publish and Bring Your Team In

When the app behaves the way you expect, publish it, invite your team, and assign each person a role so they see and can do only what their part of the process requires. We all know business processes are constantly evolving. The app stays editable after launch, so you can keep refining it as your process changes.

Explore Pave vibe coding to learn more.

Start Building with Pave

Vibe coding works best when the person who knows the process is the one building it. Pave, an AI app builder from Quickbase, is built for those people. Just describe your workflow in your own words, connect the tools you already use, and Pave builds a custom app around your process.

Ready to try it for yourself?

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FAQs

What is vibe coding?

Vibe coding is building software by describing what you want in natural language and letting AI generate the app, instead of writing the underlying code yourself. You explain the process the way you'd explain it to a new hire, review what the AI builds, and refine it through follow-up prompts until it matches how the work actually runs. The term comes from AI researcher Andrej Karpathy, who described it as "giving in to the vibes" and letting the AI handle the code entirely.

Is vibe coding just coding with AI?

No, vibe coding goes deeper than most AI-assisted coding. Plenty of AI coding tools assist a developer who's still reading and writing code line by line — just faster. Vibe coding removes that requirement: the person directing the build doesn't need to read or write code at all, and works entirely through description and review.

What are the pros and cons of vibe coding?

The main benefit of vibe coding is that it lets someone without programming experience build software tailored to their own process, faster and without waiting on developer resources. The main drawback is that the same speed can outrun the review a piece of software normally gets before a team depends on it like data quality, duplicate actions, access, failed connections, and ownership.

Is vibe coding safe?

Vibe coding is as safe as the guardrails built around it, and that's specifically what Pave is designed to provide. Every Pave app runs on a structured data layer with version history and rollback, so changes stay reversible rather than permanent the moment you make them. Apps stay in draft until you choose to publish, and IT keeps visibility and control over governance, permissions, and access as you build. See how Pave's security and compliance controls work in more detail.

What are the best use cases for vibe coding?

The best use cases for vibe coding are internal processes you already know well, with clear boundaries and an outcome you can check, such as a maintenance request workflow, an approval chain, or an intake and triage process. Starting with a lower-risk, familiar process gives you room to learn the build-and-refine cycle before applying it to anything that touches sensitive data or carries bigger consequences.