Vibe Coding Explained: What It Actually Is, What It Is Not, and Why It Matters

Everyone has an opinion about vibe coding. Half the internet thinks it is the future of programming. The other half thinks it is a recipe for unmaintainable disasters. Both sides are partially right, but most people debating it cannot even agree on what the term means.

So let us fix that. Here is a clear, no-hype explanation of what vibe coding actually is, where it came from, how it works in practice, and (most importantly) when it is appropriate and when it is not.

At CODERCOPS, we have used vibe coding approaches for rapid prototyping and we have also seen vibe-coded production systems that cost clients tens of thousands of dollars to fix. We have strong opinions, and they are all based on experience.

Vibe coding changed the conversation about what “programming” means. The conversation needed changing. The details, however, matter enormously.

The Origin: What Karpathy Actually Said

In February 2025, Andrej Karpathy (co-founder of OpenAI, former head of AI at Tesla, one of the most respected figures in machine learning) posted a tweet that defined a movement:

“There’s a new kind of coding I call ‘vibe coding,’ where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.”

He described a process where he would talk to the AI, see results, run the app, copy-paste error messages back to the AI, and iterate until things worked. He was explicit that he did not review the code deeply. He accepted the vibes.

This was not meant as engineering advice. Karpathy was describing his process for weekend projects and throwaway prototypes. But the internet, being the internet, heard “you do not need to understand code anymore” and ran with it.

By early 2026, Karpathy himself was already moving past the term. He introduced the concept of “agentic engineering”: using AI agents to write code while maintaining human oversight, quality standards, and architectural judgment. The emphasis on “engineering” was deliberate. It acknowledged that professional software development requires discipline that “vibing” does not provide.

The Spectrum: From Vibe Coding to Agentic Engineering

Most discussions about vibe coding treat it as binary: either you vibe code or you do not. In reality, there is a spectrum:

The AI-Assisted Development Spectrum

Level 1: Traditional Coding
├── You write every line manually
├── AI used for reference (Stack Overflow, documentation)
└── 100% human understanding of the codebase

Level 2: AI-Assisted Coding
├── You write code with AI autocomplete (Copilot, Cursor)
├── You review and understand every suggestion before accepting
├── AI handles the typing; you handle the thinking
└── 90-95% human understanding of the codebase

Level 3: AI-Augmented Engineering
├── You describe tasks; AI generates implementations
├── You review the output carefully before committing
├── AI handles implementation; you handle architecture and review
└── 70-85% human understanding of the codebase

Level 4: Agentic Engineering (Karpathy's 2026 term)
├── Autonomous agents execute multi-step tasks
├── You define objectives and constraints; agents execute
├── Human role is oversight, review, and architectural decisions
└── 50-70% human understanding of generated code (with review)

Level 5: Pure Vibe Coding (Karpathy's original term)
├── You describe what you want in natural language
├── You accept the output without deep review
├── You iterate by describing problems, not reading code
└── 10-30% human understanding of the codebase

Most professional developers in 2026 work at Levels 2-4. Level 5, pure vibe coding, is used for prototypes, personal projects, and demos. Using it for production code is the mistake that generates all the horror stories.

How Vibe Coding Actually Works

Here is a practical demonstration of what vibe coding looks like at each level of complexity.

Simple Example: Building a Landing Page

The prompt:

Build a landing page for a SaaS product called "ProjectPulse" —
a project management tool. Include a hero section with a headline
and CTA, features section with 3 features, pricing table with
Free/Pro/Enterprise tiers, and a footer. Use modern design,
dark mode, and animations on scroll.

What happens: An AI builder (v0, Bolt.new, Lovable) generates a complete, visually polished landing page in 30-90 seconds. The HTML/CSS/JS is clean. The design is professional. The page works on mobile.

Should you vibe code this? Yes. A landing page has no security implications, no complex business logic, and no database interactions. If the design looks good and the content is correct, ship it.

Medium Example: Building a CRUD Dashboard

The prompt:

Build an admin dashboard for managing users. Include:
- Login page with email/password
- User list with search, filter by role, and pagination
- User detail page with edit form
- Role management (admin, editor, viewer)
- Use Supabase for auth and database

What happens: The AI generates a working dashboard with authentication, database integration, and all the specified features. It looks good and works on the happy path.

Should you vibe code this? Partially. The UI and CRUD logic are fine to accept with light review. But the authentication flow, role-based access control, and database security policies need careful human review. In our testing, AI-generated RBAC has subtle bugs about 30% of the time: conditions that look correct but allow privilege escalation.

Complex Example: Building a Payment System

The prompt:

Add Stripe subscription billing to the existing app. Support
monthly and annual billing for three tiers. Handle upgrades,
downgrades, cancellations, and failed payments. Send email
notifications for payment events.

What happens: The AI generates a Stripe integration that handles the checkout flow and basic subscription creation. But the webhook handler for processing asynchronous events (payment failures, subscription changes, disputes) is either incomplete or incorrect. Idempotency is usually missing. Edge cases around proration, trial periods, and tax calculation are not handled.

Should you vibe code this? No. Payment processing has legal and financial implications. A bug in payment handling means either you lose revenue or your customers get charged incorrectly. This requires an experienced developer who understands Stripe’s event system and can handle every edge case.

Where Vibe Coding Genuinely Excels

We are not anti-vibe coding. Used appropriately, it is one of the most powerful productivity tools available:

1. Rapid prototyping and validation. Before you spend weeks building a product, spend 2 hours vibe coding a prototype to test with users. If the concept does not work, you have wasted 2 hours instead of 2 months.

2. Internal tools. Your team needs a simple dashboard to monitor deployments? A script to process CSV files? An internal form for submitting time off requests? Vibe code it. The stakes are low and the time savings are high.

3. Learning and exploration. Want to understand how WebSockets work? Want to see what a recommendation engine looks like? Describe it to an AI, get working code, and study how it works. This is a phenomenal learning tool when used intentionally.

4. Client demos and presentations. Need to show a client what their product could look like? Vibe code a demo in an hour. It does not need to be production-ready. It needs to communicate the vision.

5. Hackathons and side projects. Any context where speed matters more than long-term maintainability is a good fit for vibe coding.

Where Vibe Coding Will Destroy You

1. Anything that handles money. Payment processing, billing, financial reporting. A single bug can cost thousands and damage trust.

2. Anything that handles sensitive data. Healthcare, legal, HR systems. AI-generated code routinely has security vulnerabilities that would violate HIPAA, GDPR, or SOC 2 requirements.

3. Anything that needs to scale. Vibe-coded applications optimize for “it works” not “it works under load.” The first time 1,000 users hit your app simultaneously, every performance assumption the AI made will be tested.

4. Anything multiple developers will maintain. Code that nobody understands is code that nobody can fix. If you vibe code a system and then hand it to a team, you have given them a codebase-shaped puzzle with no documentation and no institutional knowledge.

5. Anything with regulatory requirements. Financial services, healthcare, government contracts. Regulators do not accept “the AI wrote it” as an explanation for compliance failures.

Our Framework: When to Vibe and When to Engineer

At CODERCOPS, we use this simple decision framework:

Question	If Yes →	If No →
Will real users’ data flow through this?	Engineer it	Vibe it
Does it handle money or payments?	Engineer it	Vibe it
Will more than 100 people use it?	Engineer it	Vibe it
Will someone need to maintain this in 6 months?	Engineer it	Vibe it
Are there regulatory or compliance requirements?	Engineer it	Vibe it
Is this a prototype or demo?	Vibe it	—
Is this an internal tool with <10 users?	Vibe it (with basic review)	—

If any of the first five questions is “yes,” the code needs proper engineering, even if AI generates the initial implementation. The AI draft is a starting point, not a finished product.

The Skills That Matter in the Vibe Coding Era

Whether you embrace vibe coding or not, the skills that make developers valuable have shifted:

More valuable than ever:

• System architecture and design
• Security thinking and threat modeling
• Code review and quality assessment
• Writing precise specifications
• Understanding performance characteristics
• Debugging complex, distributed systems

Less valuable than before:

• Memorizing syntax and APIs
• Typing speed
• Writing boilerplate from memory
• Knowledge of one specific framework (AI can write in any framework)

New and valuable:

• Prompt engineering and specification writing
• AI tool orchestration (knowing which tool to use when)
• Evaluating AI-generated code quickly and accurately
• Understanding when to trust AI and when to override it

The Bottom Line

Vibe coding is real, it is useful, and it has permanently changed how software gets started. It has not changed how good software gets finished. The gap between “it works” and “it works correctly, securely, and at scale” is where engineering skill lives, and that gap has not gotten smaller.

Use vibe coding for the right things. Engineer the things that matter. And never ship code you do not understand, regardless of who or what wrote it.

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Want to Learn More?

At CODERCOPS, we combine AI-powered development speed with professional engineering rigor. If you are exploring how vibe coding fits into your development process, or if you have a vibe-coded prototype that needs production hardening, we would love to chat.

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This post was written by humans with the assistance of AI tools, which seems appropriate for the subject matter. Updated May 2026.