Vibe Coding: What It Is, Where It Works, and Where It Falls Apart

Vibe coding is the practice of describing what you want in natural language and letting an AI agent write the code. The term went from Twitter joke to industry vocabulary in a matter of months, and it now describes everything from "build me a to-do app" prompts to agents that provision entire production stacks. This guide separates the marketing from the mechanics: what vibe coding actually is, where it earns its keep, and where it quietly falls apart.

What is Vibe Coding? Beyond "Describe Your App"

At its simplest, vibe coding means turning intent into working code without hand-typing every line. You describe a goal; a large language model generates the implementation. But that definition hides a spectrum.

At one end is prompt-based generation: you ask, the model produces a snippet, you paste it. At the other end is agent-driven development, where the model reads your codebase, follows your conventions, applies structured changes, and even provisions the services your app depends on.

The term exists now because the tooling finally caught up. Models like Claude can hold large contexts, follow multi-step instructions, and edit files in place. Editors like Cursor made iteration local and fast. Agents matured from autocomplete into something that can reason about architecture. "Vibe coding" is shorthand for that shift.

The Real Difference: Vibe Coding vs. No-Code Builders

No-code builders aim at people who don't read code. Vibe coding assumes you do. That single distinction explains most of the confusion in the market.

Tools like Lovable, Bolt, and Replit are excellent at generating a UI from a sentence. Where they struggle is the plumbing layer — the integration work between services that isn't clever but eats weeks. A generated login screen is easy. A signature-verified, idempotent Stripe webhook that agrees with your database is not.

Vibe coding wins in three places: working inside existing codebases, wiring integrations across services, and handling edge cases that a template can't anticipate. It fails, or at least needs a human, at pixel-perfect UX, complex state machines, and anything where "looks plausible" is not the same as "is correct."

How Vibe Coding Actually Works in Practice

The reliable pattern is an interview loop. The agent gathers requirements, generates code, and you iterate. Instead of one giant prompt, you have a conversation: What's your domain model? Which billing tiers? What auth scope?

The best results come when the agent has something to read. Folder structure, type hints, and a conventions file give it a map. Without one, an agent adds a fourth way to fetch data the moment it finds three — not because it's dumb, but because it has no reason to prefer yours.

There's also a meaningful difference between free-form code generation and deterministic patches — automated, repeatable changes applied to a known starting point. Free-form output is creative and unpredictable. Deterministic patches reshape a codebase to your answers in a way you can review and reproduce.

Constraints make agents reliable. Strict TypeScript catches hallucinated APIs at compile time. Documented patterns give the model a single correct choice instead of five plausible ones.

The Stack That Enables Vibe Coding

Some stacks are simply more agent-friendly than others. Nuxt, Supabase, and Stripe happen to combine well because each one rewards consistency.

Supabase's row-level security is a machine-readable contract: access rules live in the database and are enforced at query time. Stripe's model treats webhooks as the source of truth for billing state, which is exactly the kind of explicit, documented behavior an agent can follow. Nuxt's folder conventions give the agent predictable places to put things.

What breaks agents is the opposite: undocumented side effects, magic strings, and implicit state that only lives in someone's head. If a human has to "just know" that changing one file requires editing four others, the agent won't know either. This is the whole argument behind why every boilerplate ships the stack but the wiring is the real work.

Vibe Coding for SaaS: Where It Saves Weeks

SaaS is where vibe coding pays off most, because SaaS is mostly plumbing. The framework debate is over in an afternoon; the wiring between pieces is what actually eats your launch.

Consider what a competent agent has to handle for a real product:

• Billing edge cases: idempotent refunds, subscription state transitions, and EU consent laws like the German withdrawal waiver encoded into the pay button.
• Multi-tenant auth: row-level security expressed as policies the agent can read and extend.
• Payment as source of truth: your checkout success page should not touch billing state — the webhook is the record.
• Transactional email and consent tracking: the unglamorous flows every paid product needs on day one.

This is the premise behind BoiledPlate: the agent doesn't just write code, it provisions Stripe products and webhooks, a Supabase database with RLS, and Google sign-in in a single session.

Vibe Coding Limitations (An Honest Take)

Agents are not magic. They struggle with UX debugging and CSS refinement, where the feedback loop is visual and subjective. They make plausible architectural choices that are subtly wrong. And they hallucinate — confidently inventing an API method that doesn't exist.

Complex business logic still needs human review. The hallucination risk in architecture decisions is exactly why a conventions contract exists: it narrows the agent's choices to the ones you've already blessed. Knowing when to say "no, I'll write this myself" is a skill, not a failure.

Vibe Coding Tools Tested: Capabilities vs. Reality

The market is crowded, so it helps to compare tools by what they actually do rather than what they advertise.

Cursor is superb for local iteration but doesn't provision services. Lovable and Bolt produce UI fast and stall at integrations. Replit gives you an environment but no billing or auth defaults. Claude, given a codebase with a conventions contract, can run interviews, apply deterministic patches, and set up services — the difference is the scaffold, not just the model.

Building With Agents: Patterns That Work

A few habits separate productive vibe coding from frustrating chaos.

Write specific, convention-following prompts. Vague prompts get vague code. Point the agent at your patterns.

Keep code review discipline. Agents produce plausible output. Plausible is not correct. Read every diff as if a fast, tireless junior wrote it.

Iterate one loop per major feature. One interview per billing flow beats one 2,000-word prompt trying to build everything.

Use version control and semantic release notes so updates stay agent-readable and you can trace what changed and why.

The Anti-Plumbing Stack: Choosing Tools for Agent Compatibility

Framework choice matters less than consistency. Pick tools that expose explicit, documented contracts:

• Supabase: RLS is machine-readable security; agents respect policies they can read.
• Stripe: webhooks as the source of truth — a model agents get right when told to.
• Resend: transactional email without heavy vendor lock-in.
• Nuxt: folder conventions an agent can follow without guessing.

The precise wiring each of these demands is covered in detail in what it actually takes to wire up a Nuxt, Supabase and Stripe SaaS.

Vibe Coding in Production: Real-World Edge Cases

Production is where the honest work shows up. A few examples worth prompting for explicitly:

• Webhook failure handling and idempotency, so a retried event doesn't double-charge or double-provision.
• Refund flows and billing dispute workflows.
• Multi-plan subscription logic — the five decisions behind Stripe subscriptions — plus usage tracking.
• Consent withdrawal and GDPR data deletion.
• Rate limiting on agent-generated API calls.

These are exactly the flows a template glosses over and a real launch cannot.

Vibe Coding vs. Traditional Development: The Real Trade-Offs

The trade-off is speed to MVP versus review overhead. Vibe coding collapses weeks of plumbing into a session, but you pay it back in code review. Agent-driven setup gets you to a running product fast; deep, unusual customization still favors hand-coding.

Vibe coding is worth it for SaaS, multi-service provisioning, and integration-heavy work. Traditional coding still wins for bare-metal performance, custom DSLs, and performance-critical paths where every allocation matters.

Getting Started With Vibe Coding: A Practical Workflow

1. Set up your environment: an agent like Claude, a codebase it can read, and a conventions contract.
2. First interview: nail the domain model, billing tiers, and auth scope.
3. Second pass: integrations and edge cases — webhooks, RLS, email.
4. Continuous: refine prompts based on the quality of what comes back.
5. Know your escape hatches: when to hand-code and when to override the agent.

If you want a free place to practice the loop, BoiledPlate Lite is an MIT-licensed Nuxt + Supabase starter you can clone and wire yourself.

The Future of Vibe Coding

Deterministic patches will stop being a bespoke trick and become standard practice. Agents will increasingly act as service provisioners, not just code writers. Edge cases — billing, compliance, webhooks — will become first-class prompts rather than afterthoughts. And we'll start measuring agent-written code the way we measure human code: on readability and maintainability, not just whether it compiles.

Vibe coding won't replace developers. It shifts the work from typing plumbing to reviewing it — and, if you set up your conventions well, that's a much better place to spend your time.