Build Better Apps with AI Using This One Simple Document (PRD Guide)

Summary

In this video, the creator discusses the process of building a blog with an AI co-pilot and a product requirements document (PRD). They demonstrate how feeding a clear PRD to an AI tool like Claude helps streamline development by clarifying features, tech stack, and backend requirements. The video explores the benefits of using tools like Bolt, Claude Code, and PocketBase for deployment and backend management. Through hands-on examples, the creator shows how AI-driven tools can efficiently generate code, deploy to platforms like Netlify, and overcome common challenges like database integration and deployment issues.

Takeaways

• 😀 Having a solid Product Requirements Document (PRD) is crucial for efficient AI-powered development, especially when using AI co-pilots like Claude, Bolt, and Cursor.
• 😀 Lack of documentation leads to confusion, making the coding process harder and requiring potential restarts, but a well-prepared PRD can guide the AI and improve results.
• 😀 The key to successful AI-assisted coding is clearly defining the project’s tech stack, which in this case includes Astro, Netlify, and PocketBase for deployment and back-end functionality.
• 😀 A good PRD should include core features like an admin dashboard, newsletter subscription, archives, and proper SEO structures such as tags, categories, and permalinks.
• 😀 It’s important to keep the PRD flexible, adjusting details based on the evolving needs and feedback from the AI co-pilot during development.
• 😀 When creating a PRD, it’s essential to address the database schema early on to avoid discrepancies between front-end and back-end, preventing future headaches.
• 😀 User roles and permissions should be clearly outlined in the PRD, including distinctions between admins, editors, and contributors to ensure smooth content management.
• 😀 Interaction with AI tools like Claude should be conversational, with frequent clarification questions to ensure the AI is on track and not making incorrect assumptions.
• 😀 Using tools like Sonnet or Claude over Gemini can save time, as these models are more agentic and take action autonomously, while Gemini requires more user intervention.
• 😀 While tools like Bolt can quickly generate results, potential issues like deployment dependencies and environmental variable setup may require manual adjustments for deployment success.
• 😀 Even after a successful PRD creation, iterating on the final details (like font choices or database schema) is necessary, and tools like Claude can assist in refining these aspects as you go.

Q & A

What is the main problem when vibe coding without documentation?

The main issue is the lack of clear direction, which can lead to confusion and inefficient progress. Without documentation like a PRD, the AI might not understand your requirements, leading to messy or incomplete results.

Why is creating a Product Requirements Document (PRD) beneficial for AI-powered coding?

A PRD helps provide clear guidance to the AI co-pilot, ensuring better outcomes. It outlines the project’s goals, tech stack, features, and other crucial details, preventing misinterpretation and improving the accuracy of the AI’s output.

What are the essential components of a PRD mentioned in the video?

The key components include: a project overview (like the product you're building), the tech stack (e.g., Astro, Netlify, PocketBase), key features (admin dashboard, SEO, etc.), and any clarifications needed for user roles or functionality.

How does the AI interact with the PRD to help build the project?

The AI uses the information in the PRD to generate a detailed project plan and even starts writing code based on the specifications. It might ask clarifying questions but ultimately builds the project step-by-step according to the given instructions.

What’s the difference between using Sonnet in Claude versus other models like Gemini?

Sonnet in Claude is more proactive and efficient. It takes the initiative to write and adjust the PRD and doesn’t wait for excessive clarification like other models, such as Gemini, which tend to ask a lot of questions before proceeding.

Why is user role clarification important when creating a blog with AI?

Clarifying user roles, like admin, editors, or contributors, ensures that the AI understands the permissions and functionalities for different types of users. This allows for accurate generation of features like content management and user access control.

What are the potential problems if the backend and frontend do not match during development?

If the backend and frontend aren’t aligned (e.g., mismatched database schema or APIs), it leads to integration issues that are time-consuming and difficult to fix. A PRD helps maintain consistency across both, ensuring smooth integration.

How does feeding a PRD help streamline deployment on platforms like Netlify?

By specifying deployment settings in the PRD, the AI can automate the setup of the project, including configuring deployment paths, build commands, and necessary environmental variables, leading to quicker and more reliable deployments.

What are the advantages of using PocketBase over Supabase for the backend of a blog?

PocketBase is simpler and more lightweight compared to Supabase. It’s open-source, easy to set up, and keeps the project cleaner and more manageable for small projects like a blog, whereas Supabase is more feature-rich but might be overkill for simple needs.

Why is it important to have a database schema defined early in the process?

Having a database schema early ensures consistency and clarity in the project’s data structure. This prevents issues where the frontend might not align with the backend’s data, which can lead to data retrieval problems or errors down the road.