What Is Vibe Coding? A Founder's Guide for 2026

By Chris Kernaghan 9 min read
What Is Vibe Coding? A Founder's Guide for 2026

Vibe coding is building software by describing what you want in plain English and letting an AI tool write the code. You judge the result, give feedback and repeat. IBM describes it as a loosely defined practice in which people prompt AI tools to generate code instead of writing it by hand. For a founder, that means a working prototype in days rather than months. It also means you still own the quality of what ships.

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TL;DR

  • Vibe coding is prompting an AI to write, fix and refine code, so the person steers the product instead of typing every line.
  • The loop is simple: describe a goal, run what the AI produces, give feedback, repeat in small slices.
  • It suits prototypes, internal tools and idea testing. It is a poor fit for anything handling logins, payments or sensitive data without proper review.
  • The UK National Cyber Security Centre says the amount of oversight should match the risk of what you are building.
  • It is a way of building software, not a settled job title.

Table of Contents

What vibe coding means

The term was introduced by computer scientist Andrej Karpathy in February 2025, according to IBM. It caught on quickly because it named something many people were already doing: typing a request into an AI tool, accepting what came back and moving on.

GitHub’s explainer frames it as users describing ideas in natural language while AI assistants generate, refine and deploy the code. The developer’s role shifts from writing line by line to guiding the AI as a conversational collaborator.

Two things are worth separating:

  • Pure vibe coding: fast, exploratory generation where you mostly judge the output by whether the app behaves as you wanted.
  • Responsible AI-assisted development: the same tools, but with human review and validation built in. Google Cloud’s guide draws this distinction.

Most founders move between the two depending on what they are making.

How vibe coding works, step by step

According to Google Cloud, the process is a conversational loop: describe a goal, let the AI generate code, run it, give feedback and repeat until the code is complete. Grow with Google stresses that it is not a single prompt. It is a structured, iterative process of planning, building in small slices and refining through feedback.

Here is how that looks for a first-time founder.

  1. Write a master plan. Before you build, map how someone will use the app. Grow with Google recommends this so the AI has a blueprint instead of guessing. One page covering who the user is, what they do first and what success looks like is enough.
  2. Start with one slice. Ask for a single screen or one feature, not the whole product. PCMag’s guide recommends small, manageable slices and frequent testing.
  3. Run it and react. Cloudflare explains that you give high-level instructions, receive working code, then use further prompts to refine features, test behaviour and fix bugs.
  4. Keep the context clear. PCMag also advises maintaining clear context for the AI agent as the project grows. In practice, that means restating the plan and what has already been decided.
  5. Describe bugs properly. Replit notes that debugging needs a different skill set: you must describe the problem clearly and give evidence such as error messages or screenshots.
  6. Deploy. Some platforms now offer what Google Cloud calls “vibe deploying”: launching to a live environment through a single click or prompt.

If prompting itself is where you get stuck, our guide to prompting techniques for vibe coding goes deeper on wording requests so the AI does what you meant.

What founders actually build with it

The appeal is speed. Replit points out that for non-technical creators the traditional routes can mean months or years of learning or hiring developers, then weeks to months to build a prototype. Vibe coding compresses that.

Grow with Google lists practical examples such as project-rescue tools, video-storyboard apps and data-storytelling dashboards. For an early-stage founder, typical first projects include:

  • A landing page with a waitlist form to test demand.
  • A clickable prototype to show investors or early customers.
  • An internal dashboard that pulls together numbers you currently track in a spreadsheet.
  • A small tool that automates one repetitive job in your week.

Want to see how this plays out commercially? We looked at five AI-built apps generating serious revenue, and the pattern is consistent: small scope, a clear user and fast iteration.

Prototyping costs are also shifting across other areas of building. Our piece on how AI 3D generation is reducing prototyping costs covers one example.

Unfinished 3D-printed prototype on a printer bed

What people use to vibe code

There are a few types of tool, and the right one depends on how technical you are.

Type of tool Best for What to expect
AI assistant inside a code editor People who can read code Fast suggestions with you in control of every change
Browser-based app builder Non-technical founders Describe an app, see it running, publish from the same place
Terminal or agent-style coding tool Developers handling bigger projects The AI plans and edits across many files
General chatbot Learning and one-off scripts Copy and paste code, then run it yourself

PCMag suggests weighing each model’s strengths, using free trials to test your preferences, and checking how well a tool connects to the place you will deploy. Examples it covers include GitHub Copilot, Cursor, Replit Agent and Google AI Studio.

For a wider view of editors and agents, see our roundup of the best AI coding tools for developers. If you want the human story behind one of the best-known editors, read about the team that built it. And if you have just started, getting the best out of any tool is a sensible next read.

Benefits and limits for a product

MIT Technology Review describes the benefits as speed, accessibility and rapid prototyping, and the limits as security vulnerabilities, “mostly works” results and difficulty with complex, high-stakes systems. New Scientist adds that people with no programming experience can turn ideas into software this way, but the result may be incomplete or error-prone and hard for them to fix.

The practical reading for founders:

  • Use it freely where the cost of a mistake is low: prototypes, demos, throwaway scripts, idea validation. Twilio’s guide calls it best for low-stakes prototyping and rapid ideation.
  • Add review as soon as real users, real data or long-term maintenance enter the picture. Codecademy notes that security and complex, long-lived projects are where the difficulties concentrate.
  • Watch the bills. Replit warns that costs for AI-powered development, hosting and API usage can rise as an application scales, so budget actively. Our comparison of API pricing and the hidden costs of scaling shows how quickly this adds up.

What to check before real users arrive

The UK’s National Cyber Security Centre gives the clearest framework. Its vibe coding spectrum runs from AI autocomplete with full human control, to high-level prompting where the AI decides architecture, modules and tests with little code review.

The NCSC recommends lighter oversight for prototypes and internal tools. It recommends more rigorous review, understanding, vulnerability checks and verification for authentication, sensitive data, credentials and safety-critical code. If your product has a login, stores customer details or takes payments, treat that code as the high-risk end of the spectrum and have an experienced developer review it.

A pre-launch checklist drawn from the sources:

  1. Map the user flows and test them by hand. Grow with Google recommends this before launch.
  2. Try wrong inputs and out-of-order actions. Click things in the wrong sequence, submit empty forms, paste odd characters. PCMag warns that AI can produce apps that look finished but fail under real-world conditions.
  3. Secure the backend settings. Grow with Google lists this as a key step for data security.
  4. Do not assume running means ready. GitHub notes that AI-generated code can be clunky, inefficient or hard to maintain, and that code which runs is not automatically production-ready.
  5. Plan for the gap between demo and product. Red Hat Developer argues that production software still needs technical understanding, specifications, testing and guardrails.

GitHub also says developer experience and judgement, plus knowledge of computer-science principles, matter for shaping AI output and reviewing quality, security and maintainability. That is good news if you hire even a part-time engineer: their time goes further.

Risk is a founder topic beyond code, too. Our guide to risk management for founders covers protecting the rest of your assets.

Is vibe coding a job?

Mostly, no. It is a way of building software rather than a recognised profession. AP News reports that engineers and companies use the term informally and that some practitioners reject it. Software engineer Yoav Tzfati describes it as an activity. Isolated titles such as “vibe-coding engineer” exist, but they do not add up to a standard occupation.

For your career or your hiring, the safer framing is AI-assisted software development. Red Hat Developer says developers should express intent, understand architecture and trade-offs, and validate software with tests. Those are the skills that last whatever the tools are called.

Our perspective

We see vibe coding as the cheapest way a founder has ever had to test an idea. A weekend and a clear plan can now give you something real to put in front of customers, and that changes who gets to start.

What we hear from founders who have done it is consistent: the ones who do well treat the AI as a fast junior colleague. They write down what they want, build in small pieces, test like a sceptical customer and ask for a proper review before anything sensitive goes live.

That is why we focus on practical, peer-driven material rather than hype: tool comparisons, tactical guides and stories from people who have actually shipped. Choosing a tool, controlling costs and knowing when to bring in an engineer are exactly the decisions our curated resources are built to help with.

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FAQ

What do I use to vibe code?

You use an AI coding tool: an assistant inside a code editor, a browser-based app builder, an agent-style tool or a general chatbot. PCMag suggests comparing models’ strengths, using free trials and checking deployment integration. Pick the one that matches your technical level and where you want to host the result.

Can everyone vibe code?

Yes, people without programming experience can turn ideas into working software this way. New Scientist cautions that the output may be incomplete or error-prone and hard for a beginner to fix. Start with low-stakes projects and get an experienced developer to review anything involving users’ data.

Is vibe coding a real job?

Not in the sense of a standard occupation. AP News reports that the term is used informally and that some engineers reject it, though a few job titles use it. It is better understood as an approach within AI-assisted software development.

Is vibe coding safe for a startup product?

It depends on what the code does. The NCSC recommends lighter oversight for prototypes and internal tools, and rigorous review for authentication, sensitive data and credentials. Test edge cases by hand, secure backend settings and have a developer review high-risk areas before launch.

Sources

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what is vibe code

Chris Kernaghan

Owner of We Are Founders, UX designer, husband, and dad. Got something you want to share with us? Reach out at hello@wearefounders.uk.