# Episode 14: Vibe Coding that works!
In this episode, the hosts discuss their development of "slow code," a more intentional approach to coding with AI that contrasts with "vibe coding."
They explore how this methodology creates a structured workflow combining human planning with AI execution, resulting in higher quality code while maintaining the speed benefits of AI assistance.
## Key Themes:
**Understanding Vibe Coding** (00:02:20 - 00:08:00)
* Vibe coding involves speaking instructions to AI and ignoring the underlying code
* Democratizes coding by allowing anyone to build in natural language
* Major downside: potential security issues and poor code quality
**Evolution to Slow Code** (00:08:00 - 00:19:40)
* Hosts developed methodologies through experimentation with AI tools
* Initial frustrations with existing AI coding tools led to refinement
* Slow code combines intentional planning with AI execution
**Three-Phase Methodology** (00:19:40 - 00:25:30)
* Ideation: Using Claude Desktop for exploration and brainstorming
* Planning: Converting ideas to structured documents and roadmaps in Obsidian
* Execution: Having AI implement based on detailed specifications
**Tools and Implementation** (00:25:30 - 00:40:00)
* Using Obsidian for planning and documentation
* Connecting to AI tools via MCP (Model Context Protocol)
* Root Code for implementation with orchestration capabilities
* Benefits of separating environments for different phases
**Multi-Agent Conversations** (00:40:00 - 00:51:00)
* Creating pipelines where multiple AI agents discuss ideas
* Using different models (Claude, Grok) to avoid single-model biases
* Value in seeing how ideas develop through agent conversations
**Benefits of Slow Code** (00:51:00 - 01:01:30)
* Creates reusable, higher quality code versus one-shot vibe coding* Maintains human intentionality and design control
* Still much faster than traditional development
* Parallels the "write drunk, edit sober" approach to creative work
**Future Applications** (01:01:30 - 01:15:00)
* Integration with Goose for continuous development and scheduling
* Creating dedicated AI development environments
* Applications beyond coding (writing, research, analysis)
* Plans to share methodology through tutorials and community
**Contrasts with No-Code Tools** (01:15:00 - 01:26:00)
* Visual no-code tools add unnecessary complexity
* Slow code leverages AI's strengths while maintaining human oversight
* More flexible than constrained visual interfaces
In this episode, the hosts discuss their development of "slow code," a more intentional approach to coding with AI that contrasts with "vibe coding."
They explore how this methodology creates a structured workflow combining human planning with AI execution, resulting in higher quality code while maintaining the speed benefits of AI assistance.
## Key Themes:
**Understanding Vibe Coding** (00:02:20 - 00:08:00)
* Vibe coding involves speaking instructions to AI and ignoring the underlying code
* Democratizes coding by allowing anyone to build in natural language
* Major downside: potential security issues and poor code quality
**Evolution to Slow Code** (00:08:00 - 00:19:40)
* Hosts developed methodologies through experimentation with AI tools
* Initial frustrations with existing AI coding tools led to refinement
* Slow code combines intentional planning with AI execution
**Three-Phase Methodology** (00:19:40 - 00:25:30)
* Ideation: Using Claude Desktop for exploration and brainstorming
* Planning: Converting ideas to structured documents and roadmaps in Obsidian
* Execution: Having AI implement based on detailed specifications
**Tools and Implementation** (00:25:30 - 00:40:00)
* Using Obsidian for planning and documentation
* Connecting to AI tools via MCP (Model Context Protocol)
* Root Code for implementation with orchestration capabilities
* Benefits of separating environments for different phases
**Multi-Agent Conversations** (00:40:00 - 00:51:00)
* Creating pipelines where multiple AI agents discuss ideas
* Using different models (Claude, Grok) to avoid single-model biases
* Value in seeing how ideas develop through agent conversations
**Benefits of Slow Code** (00:51:00 - 01:01:30)
* Creates reusable, higher quality code versus one-shot vibe coding* Maintains human intentionality and design control
* Still much faster than traditional development
* Parallels the "write drunk, edit sober" approach to creative work
**Future Applications** (01:01:30 - 01:15:00)
* Integration with Goose for continuous development and scheduling
* Creating dedicated AI development environments
* Applications beyond coding (writing, research, analysis)
* Plans to share methodology through tutorials and community
**Contrasts with No-Code Tools** (01:15:00 - 01:26:00)
* Visual no-code tools add unnecessary complexity
* Slow code leverages AI's strengths while maintaining human oversight
* More flexible than constrained visual interfaces