A 3-step AI coding workflow for solo founders | Ryan Carson (5x founder)

Summary

In this episode, Ryan Carson, a seasoned founder, shares insights on building with AI, emphasizing the importance of context in product development and the use of AI tools like Cursor to streamline workflows. He discusses the process of creating product requirement docs (PRDs), task lists, and using advanced prompting techniques to make work more efficient. Carson also highlights how AI enables founders to build their companies more independently, leveraging AI for tasks ranging from database queries to front-end testing. The conversation underscores the significance of slowing down, providing clear context, and iterating effectively with AI.

Takeaways

• 😀 Slowing down and providing clear context to AI leads to faster, more effective problem-solving. Rushing through the setup can hinder progress.
• 😀 Many engineers and product managers struggle with breaking down complex tasks, but using tools like PRDs and task lists can significantly streamline the process.
• 😀 Ryan Carson shares that AI tools, like Cursor, can help you manage product requirements and tasks with a structured workflow.
• 😀 AI can be a powerful tool for non-technical founders, enabling them to manage and build products even without deep technical expertise.
• 😀 Starting small with AI and building up from simple tasks to more complex ones helps you grow comfortable with the process.
• 😀 Clear and detailed instructions for AI, like using specific file formats or markdown, improve the efficiency and output of the AI's work.
• 😀 AI's limitations should be recognized—while it can automate a lot, human oversight and checking are necessary for avoiding errors and ensuring quality.
• 😀 Tools like Taskmaster (open source) allow for more detailed task management but may overwhelm users who need simpler solutions.
• 😀 Using advanced features like MCPs (Meta-Cognitive Prompts) in Cursor can enhance front-end testing and task automation, making development smoother.
• 😀 The ability to integrate external tools, like Postgres or browser-based MCPs, into Cursor greatly expands its capabilities for querying databases or automating web actions.
• 😀 Context is crucial when using AI, and tools like Repo Prompt allow for more granular control over the context being provided to the AI, improving the quality of results.
• 😀 A positive attitude and patience when working with AI—treating it like a helpful assistant—often leads to better results, both in development and in managing tasks.

Q & A

What is the biggest mistake that people make when working with AI in the context of product development?

The biggest mistake is rushing through the context without giving the AI enough information. People often lack the patience to properly explain what the AI needs to know in order to solve the problem efficiently.

What does Ryan Carson mention about the role of product managers and engineers in relation to PRDs (Product Requirement Docs)?

Ryan emphasizes that many engineers and product managers get stuck trying to break down a PRD into actionable tasks. He points out that even though he can't replicate the work of a dedicated product manager or CTO perfectly, AI tools help him build his company effectively by streamlining the process.

How does Ryan Carson use Cursor in his product development process?

Ryan uses Cursor, a VS Code fork, to streamline his coding and product development workflow. He creates rules for the AI to follow, such as generating PRDs and task lists. This helps him break down larger tasks into manageable steps that can be implemented more efficiently.

What is the significance of PRDs (Product Requirement Docs) in Ryan's process?

PRDs are crucial as they describe the features Ryan wants to build. He uses AI to generate these documents, making the process faster and more structured. These PRDs are written in a way that a junior developer could understand and implement, ensuring clarity for those working on the project.

What challenges does Ryan highlight about working with AI in product management?

Ryan points out that AI can sometimes introduce small errors or issues that need to be fixed, such as linting errors. He mentions that even with AI assistance, the human in the loop is necessary to check the work and ensure that the results are correct before proceeding.

How does Ryan integrate AI with other tools like Postgres and browser-based MCPs (Modular Command Protocols)?

Ryan integrates AI with tools like Postgres to quickly check database values without having to write SQL manually. He also uses browser-based MCPs to control a headless browser, allowing him to automate front-end testing and perform other tasks directly from within the Cursor environment.

What role does context play in the effectiveness of AI in Ryan's workflow?

Context is essential. Ryan highlights that AI needs the right context to be effective. He uses tools like Repo Prompt to control and manage the context of AI tasks, ensuring that the AI has all the necessary information to perform optimally.

What is the purpose of using MCP servers in Ryan's workflow?

MCP servers like the browser-based MCP and Postgres help Ryan interact with other applications and databases through Cursor. By leveraging these tools, he can perform tasks like navigating web pages or querying databases directly in the Cursor environment, reducing the need to switch between multiple tools.

Why does Ryan prefer working with markdown files for task management?

Ryan prefers markdown files for task management because they provide a simple, readable format that allows him to easily add and track tasks. Unlike more complex project management tools, he finds it easier to manage tasks in markdown files within Cursor.

How does Ryan describe the future of AI in product development and his own startup journey?

Ryan believes that AI is revolutionizing product development by making it possible for him to build his startup on his own. While AI can't fully replace a dedicated product manager or CTO, it enables him to take on tasks that would normally require multiple specialists, making the development process more efficient and accessible.