The Stack Map Workflows › Vibe Coding — Full-Stack App Development
Engineering & Dev 4 steps 9 tools

Vibe Coding — Full-Stack App Development

Rapidly build full-stack web applications by describing requirements in natural language and iterating with AI. This "vibe coding" approach lets developers and non-developers alike ship production-ready apps 3-5x faster than traditional development.

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Workflow

Step 1
Architecture and planning
Describe the application requirements to an LLM and iterate on a detailed technical specification including tech stack, database schema, API design, and component structure.
Alternatives: ChatGPTGemini
Input: A product idea or problem statement
Output: Technical spec with architecture, schema, and component breakdown
Technical spec with architecture, schema, and component breakdown
Step 2
Scaffold the prototype
Use an AI app builder to generate the initial application from the spec. Non-developers use Lovable for a full working scaffold; experienced devs can jump straight to Cursor.
Alternatives: Boltv0
Input: Technical specification
Output: Working application scaffold with UI, routes, and database
Working application scaffold with UI, routes, and database
Step 3
Feature development
Bring the scaffold into an AI-native editor and implement features by describing them in natural language. Cursor's Composer writes and edits code across multiple files simultaneously.
Input: Application scaffold
Output: Feature-complete codebase
Feature-complete codebase
Step 4
Code review and debugging
Use an LLM for deep code review, explanation, and debugging. Claude Code can run agentic debugging sessions that autonomously identify and fix issues.
Alternatives: GitHub CopilotChatGPT
Input: Feature-complete codebase
Output: Reviewed, debugged, production-quality code

Step Details

Step 1

Architecture and planning

Describe the application requirements to an LLM and iterate on a detailed technical specification including tech stack, database schema, API design, and component structure.

Step 2

Scaffold the prototype

Use an AI app builder to generate the initial application from the spec. Non-developers use Lovable for a full working scaffold; experienced devs can jump straight to Cursor.

Step 3

Feature development

Bring the scaffold into an AI-native editor and implement features by describing them in natural language. Cursor's Composer writes and edits code across multiple files simultaneously.

Step 4

Code review and debugging

Use an LLM for deep code review, explanation, and debugging. Claude Code can run agentic debugging sessions that autonomously identify and fix issues.

🌐 See this workflow on the interactive graph →
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