Vibe Coding for MVPs: What Works and What Doesn't

Vibe coding—writing software purely by steering AI with natural language—is the highest leverage skill a growth operator can develop today. We are operating in an environment where capital is expensive and engineering cycles are fiercely protected. For a PLG team, vibe coding is the difference between begging for two sprints of engineering time and shipping a functional MVP over a weekend.

I’ve spent the last several months using tools like Cursor, Aider, and Claude 3.5 Sonnet to bypass the traditional growth engineering bottleneck. When you're running experiments across high-volume funnels, speed to market is everything. We aren't building the core banking ledger; we're building onboarding quizzes, pricing calculators, and internal admin dashboards.

Here is the unvarnished truth about using vibe coding to ship MVPs.

Where Vibe Coding Excels

Zero-to-One UIs with Tailwind and React If you need a functional, responsive interface, AI is practically flawless. You can dump a napkin sketch or a competitor's screenshot into v0 or Cursor, and within two prompts, you have a working React component.

In the mortgage space, building a high-converting rate calculator usually requires an engineer, a designer, and a week of back-and-forth. Using Cursor, I was able to vibe-code a functioning calculator MVP with interactive sliders and real-time amortization charts in under two hours. The AI handled the math and the component state; I just provided the product constraints.

Internal Tooling and Admin Panels Growth teams live and die by internal tooling. Vibe coding is lethal for spinning up quick CRUD (Create, Read, Update, Delete) apps. Need a dashboard to visualize loan application drop-offs from your database? Point the AI at your schema, tell it to use Tremor or Recharts, and let it vibe. It excels at boilerplate glue code.

Standardized API Integrations If the API has been documented heavily before 2023 (think Stripe, Twilio, SendGrid), the LLM knows it inside out. When we tested an experiment routing high-intent borrowers directly to loan officers via SMS, vibe coding the Twilio integration took exactly three prompts. You can prompt: "Write a webhook handler for Stripe subscription updates and log them to Supabase." It will give you production-ready code on the first try.

Where the Vibes Break Down

Undocumented or Niche FinTech APIs If you are integrating with a legacy credit reporting API or a niche mortgage pricing engine with a 30-page PDF manual, vibe coding will fail spectacularly. When we tried to wire up an automated valuation model from a boutique vendor with a poorly formatted 2018 Swagger file, we burned four hours in an infinite loop of 400 Bad Request errors. The AI will hallucinate endpoints, invent parameters, and gaslight you about authentication methods.

Complex Global State Management Vibe coding works best in isolated components. The moment your MVP requires complex global state—like tracking a user's loan application progress across 15 different uncoupled components, caching that data locally, and syncing it with a backend—the LLM loses the plot.

The Context Window Trap Once your MVP crosses roughly 2,500 lines of code across multiple files, the AI starts forgetting things. You will ask it to fix a button on the settings page, and it will accidentally break the routing logic on the login screen.

The Practical Rules for AI MVPs

To actually ship something usable, you have to constrain the AI.

Rule 1: Dictate the stack rigidly. Never let the AI choose your database or framework on the fly. Tell it exactly what to use. "We are using Next.js App Router, Tailwind, Shadcn UI, and Supabase."

Rule 2: Scaffold first, logic second. Have the AI build the entire visual shell of the MVP with mock data before you ask it to connect to a real database.

Rule 3: Commit after every win. When the AI writes a block of code that works, commit it to Git immediately. When it inevitably hallucinates and breaks the app on the next prompt, you need a clean restore point.

MVP Layers vs. Vibe Coding Viability

Navigating the Failure Modes

The CSS Death Spiral

You will inevitably encounter a situation where a container isn't aligning correctly. You ask the AI to fix it. It adds a margin. You tell it it's still broken. It changes the display to flex. Suddenly your entire layout collapses. When vibe coding hits a wall on a purely visual bug, stop prompting. Open the developer tools in your browser, find the exact CSS class causing the issue, and tell the AI exactly what to change.

The Phantom Dependency

Sometimes, to solve a complex problem, the AI will confidently import a package that does not exist. It will look real. It will sound like a logical NPM package name. But when you run your install command, it fails. Always verify the dependencies the AI is trying to introduce. Keep your package manifest as lean as possible to reduce attack vectors and bloat.

The Over-Engineering Trap

LLMs love to over-engineer if given vague instructions. If you ask it to "make the lead routing script better," it might decide to rewrite your entire routing engine using an abstract factory pattern that you don't understand and can't maintain. Always prompt for specific, localized changes. "Optimize the API call in line 45 to run concurrently."

Vibe coding doesn't replace the need to understand software architecture. If anything, it shifts your role from a line cook to an expediter. You don't need to chop the onions, but you need to know exactly how the dish should be plated. Lock down your tech stack, constrain your prompts, and use the AI to outpace your competitors' engineering queues.