Vibe Coding 101: From Idea to Deployed App with Replit AI

What is Vibe Coding?

"Vibe coding" is the practice of instructing AI agents to write code using natural language, transforming the very nature of creation. As AI researcher Andrej Karpathy eloquently put it: "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."

This revolutionary approach represents a paradigm shift in how we approach technology development. For decades, a significant barrier has existed between great ideas and their technical implementation. With 82% of businesses reporting a shortage of developer talent, this gap has become a critical bottleneck to innovation. Vibe coding directly addresses this challenge by lowering the barrier to entry, effectively democratizing application development.

Whether you're an entrepreneur with a brilliant idea, a product manager wanting to prototype quickly, a designer looking to bring visions to life, or an educator teaching technology concepts, vibe coding empowers you to focus on the what and the why rather than getting lost in the technical how.

To truly learn vibe coding, the best approach is to build a tangible, real-world application. A perfect example is creating a minimalist, interactive map that visualizes the parks, public spaces, and natural formations of San Francisco. This tool allows users to explore the city's green spaces and discover new places—turning a simple idea into a useful utility.

The Human Element: Planning and Research

While modern AI models are incredibly powerful, their value is unlocked by people who know what to use them for. The most effective vibe coders are not passive observers; they are active directors who guide the AI with their unique, domain-specific knowledge. This human expertise is the true differentiator in the age of AI.

Before writing the first prompt, a crucial research phase informed the project's direction and ensured a higher likelihood of success:

1. Framework Identification: Leveraging prior knowledge that Leaflet is a popular and effective JavaScript framework specifically designed for creating interactive maps.
2. Data Source Discovery: Researching and identifying Open Street Map as a premier open-source data platform containing exactly the kind of geographical information needed.
3. Data Exploration: Using tools like the "Open Street Browser" to explore the types of data available within Open Street Map, discovering key categories like "natural formations" and "leisure" locations.

Crafting the Perfect Initial Prompt

This human-led research culminated in a clear, specific, and highly effective initial prompt provided to Replit Agent:

"Help me create a minimalist maps application to visualize San Francisco's parks. You should use Leaflet for map visualization and fetch data from Open Street Map. Include the following Open Street Map data types for San Francisco: natural formations (woods, beaches, islet, cave entrance) and leisure (park, gardens)."

This prompt is effective because it contains several key components:

• Clarity of Goal: Clearly states the high-level objective
• Technical Direction: Provides explicit guidance based on research
• Specific Data Requirements: Lists exact data types discovered during exploration
• Visual Guidance: Includes a mockup screenshot for visual direction

Once the main application structure is in place, it's time to switch from Agent to Replit Assistant. Assistant is the ideal tool for the refinement phase, specializing in faster, more lightweight, and targeted edits. This is the stage of iterative refinement, where you polish the app's look, feel, and features through conversational back-and-forth.

Step 4: Making Stylistic Changes

The first refinement was improving the map's visual style. A simple prompt to Assistant:

"Can you use a more minimalist style for Open Street Map, specifically Cardo Light?"

Here again, human domain knowledge was key. Knowing that "Cardo Light" is a specific, clean theme for Leaflet maps guided Assistant to a high-quality outcome, instantly improving the application's aesthetic.

Step 5: Adding Features and Iterative Refinement

Next, a dark mode feature was added—a process that illustrates the realistic trial-and-error nature of vibe coding:

1. The Request: Ask Assistant to add a dark mode toggle using the "Cardo Dark" map theme.
2. The First Attempt: A toggle button appears and correctly changes the map style, but the button disappears after being clicked.
3. The Correction Loop: Engage in conversational feedback:
   • "The toggle theme button works for the map but it disappears when clicked..."
   • "Now there are two toggle theme buttons... make them into one..."
   • "Use @sidebar... you should probably read this file"
   • "Now the dark mode toggle in @sidebar does not toggle the map to Cardo dark"
4. The Philosophy: This iterative process shouldn't be seen as failure but as the core of the AI development experience. These are "happy little accidents." Embracing this cycle of prompting, observing, and refining is fundamental to successful AI-driven development.

Pro Tip: Using the @ symbol is powerful for managing the AI's context window. It explicitly directs the AI's attention to specific files, ensuring it bases decisions on the most relevant code.

One of the biggest advantages of vibe coding with Replit is affordability. Unlike traditional development requiring expensive developer hiring, Replit offers flexible pricing options for every budget:

Replit Pricing Tiers

• Free Plan: Perfect for getting started with vibe coding. Includes basic Replit Agent access and full Replit Assistant capabilities. Great for learning and building simple projects.
• Replit Pro: Enhanced limits and faster deployments. Ideal for active builders who need more resource allocation and priority support.
• Teams & Enterprise: Custom solutions for organizations building multiple applications or collaborating across teams.

The beauty of vibe coding with Replit is that you can start building immediately at zero cost, then scale your plan as your needs grow. This is dramatically different from traditional development where upfront costs are substantial before any product is even built.