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vibe-coding skill

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This skill helps you build functional prototypes and internal tools with AI, guiding iterative, non-technical creators from idea to testable results.

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---
name: vibe-coding
description: Help users build software using AI coding tools. Use when someone is using AI to generate code, building prototypes without deep technical skills, or exploring how non-engineers can create functional software through natural language.
---

# Vibe Coding

Help the user build software using AI tools and natural language, using frameworks and insights from 3 product leaders.

## How to Help

When the user asks for help with vibe coding:

1. **Understand the goal** - Ask what they're trying to build and who it's for (prototype, internal tool, production app)
2. **Guide the approach** - Help them break down the problem into smaller pieces for iterative AI prompts
3. **Set expectations** - Discuss what vibe coding is good for (prototypes, MVPs) versus when professional engineering is needed
4. **Coach on iteration** - Help them understand how to refine output through follow-up prompts

## Core Principles

### Vibe coding is a new skill
Elena Verna: "I vibe code myself so I would put that as even as a skill on my resume now." This is a distinct, transformative skill for non-technical roles - PMs, marketers, designers - to build functional software using natural language.

### Replace Figma with prototypes
Kevin Weil: "Instead of showing stuff in Figma, we should be showing prototypes that people are vibe coding over the course of 30 minutes to illustrate proofs of concept." Functional code prototypes can be built in the time it takes to create static mockups.

### Build tools to build tools
Alexander Embiricos: "They'll vibe code an animation editor and then they use the animation editor to build the animation." Non-engineers can now build functional software and custom tools without deep technical mastery.

### Go beyond prompt engineering
Vibe coding is not just writing prompts - it's iteratively building functional software through conversation with AI. It requires understanding how to break problems down, test outputs, and refine through follow-up.

### Know the limits
Vibe-coded software is great for prototypes, internal tools, and MVPs. Production-grade systems with complex requirements still need professional engineering review.

## Questions to Help Users

- "What are you trying to build, and who will use it?"
- "Is this a throwaway prototype or something that needs to scale?"
- "Can you break this down into smaller pieces to build incrementally?"
- "What's the simplest version that would let you test your hypothesis?"
- "Have you tried describing what's not working and asking the AI to fix it?"
- "Do you need this to be production-grade, or is it okay if it's rough?"

## Common Mistakes to Flag

- **Trying to build everything at once** - Break complex projects into smaller, iterative builds
- **Not testing the output** - Always run and test what the AI generates; don't assume it works
- **Expecting production quality** - Vibe-coded apps are great for validation but may need engineering for production
- **Unclear specifications** - The clearer your description of what you want, the better the output
- **Giving up after one try** - Vibe coding is iterative; refine through follow-up prompts

## Deep Dive

For all 3 insights from 3 guests, see `references/guest-insights.md`

## Related Skills

- Writing PRDs
- Usability Testing
- Building with LLMs
- Shipping Products

Overview

This skill helps users build functional software using AI coding tools and natural language. It guides non-engineers through iterative prototype creation, clarifies when AI-generated code is appropriate, and coaches users on turning ideas into testable software quickly.

How this skill works

I start by clarifying the goal, audience, and target fidelity (prototype, internal tool, or production). Then I break the problem into small, testable pieces, generate or refine AI prompts, and recommend iterations and tests to validate outputs. I flag limits and advise when to bring in engineering for hardening and scaling.

When to use it

You want a quick, functional prototype instead of a static mockup.
Non-technical PMs, designers, or marketers need a working proof of concept.
You’re exploring product ideas or validating hypotheses fast.
You need to build an internal tool or MVP with constrained scope.
You want to teach a team how to use AI tools to generate working code.

Best practices

Start with a single, smallest testable feature and iterate from there.
Be explicit: describe inputs, outputs, and acceptance criteria in prompts.
Run and test every AI-generated artifact; treat outputs as drafts to refine.
Set clear expectations: use vibe coding for prototypes and validation, not unreviewed production.
Log changes and prompt history so you can reproduce and improve iterations.

Example use cases

Create a clickable prototype that demonstrates a new onboarding flow in 30–60 minutes.
Build a simple internal data dashboard for team use and fast feedback.
Generate a small CRUD app to validate a product hypothesis before hiring engineers.
Assemble a custom editor or automation tool by iteratively composing smaller components.
Refactor or debug AI-generated code by describing failing behavior and asking targeted fixes.

FAQ

Is vibe coding the same as prompt engineering?

No. Prompt engineering is part of it, but vibe coding is a broader skill focused on iterative delivery: breaking problems down, testing outputs, and composing functional software with AI.

When should I stop vibe coding and hire engineers?

Stop when you need scalability, security, performance guarantees, or long-term maintainability. Use vibe coding for validation and prototypes; transition to engineers for production hardening.