Ryan Carson’s 3-file System for structured vibecoding

AI Generated youtube notes:

• This video features Ryan Carson, a five-time founder, sharing his structured AI coding workflow using Cursor, which helps solo founders build effectively. He emphasizes the importance of providing clear context to the AI to avoid rushing and ensure better results [10:40].

Here’s a summary of his 3-step workflow with actionable steps:

1. Create a Product Requirement Document (PRD) with AI:

• Use a specific prompt in Cursor to instruct the AI to create a PRD for the feature you want to build [05:11].
• Tailor your prompt to specify the audience for the PRD (e.g., junior developer) to guide the AI in providing appropriate levels of detail [05:41].
• Answer any clarifying questions the AI asks about the PRD to provide necessary context [07:30].
• Organize your PRDs in a dedicated folder within your project (e.g., “tasks” folder) [08:51].

2. Generate a Task List from the PRD:

• Use another specific prompt in Cursor to generate a detailed, step-by-step task list based on the PRD you just created [11:10].
• Review the generated tasks and subtasks to ensure they are logical and actionable [13:35].
• Utilize a prompt that structures the task list in a manageable format, such as a markdown file with checkboxes, for easy tracking [11:53], [12:24].

3. Iterate Through the Task List with AI Assistance:

• Use a specific rule or instruction in Cursor to guide the AI in working through the generated task list one subtask at a time [16:40], [17:02].
• After the AI completes a subtask, review the changes and ensure they are correct [20:22].
• Mark completed subtasks as done in your task list (e.g., by checking the markdown checkboxes) [17:08].
• Instruct the AI to proceed to the next subtask after you’ve reviewed the previous one [17:14].
• Commit your code changes to a version control system (like Git) at logical points, such as after completing a parent task or when the app is in a workable state [19:03].

Bonus Tips and Tools:

• Cursor Rules Folder: Organize your specific AI instructions (like PRD generation and task list creation) in a dedicated folder for easy access [04:58].
• Taskmaster: Explore the open-source Taskmaster tool as a more powerful command-line interface alternative for task management with AI [09:27].
• MCP (Machine Code Protocol) Servers: Utilize Cursor’s MCP integrations (like Browserbase and Postgres) to allow the AI to interact with other applications and data sources, streamlining workflows like frontend testing and database queries [21:51], [24:55].
• Repo Prompt: Consider using Repo Prompt (a Mac tool) for more precise control over the context you provide to language models, especially for complex tasks, by allowing you to select specific files and craft detailed prompts [26:52], [27:38].
• Iterative Refinement: Remember that creating effective prompts and rules is an iterative process of trial, error, and refinement [12:06].
• Human-in-the-Loop: Maintain a human-in-the-loop approach by reviewing the AI’s output after each step to catch errors and ensure the desired outcome [20:15].

By following these steps and leveraging the tools mentioned, solo founders can bring structure to their AI-assisted coding process, leading to more efficient and reliable development [00:10].

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