Remix V3's Fatal Flaw

Key Concepts

• Remix V3: A proposed reimagining of the Remix framework, built on a fork of Pact.
• AI Integration: The proposal to build AI-enabling features directly into the Remix V3 framework.
• Innovation Flow: The typical pattern of innovation on the web, moving from applications to libraries to frameworks to the platform.
• Framework-First vs. Application-First: The debate over whether AI features should originate in the framework or the application.
• API Support: The need for frameworks to provide flexible API support for various payload types, streams, SSE, and WebSockets to support AI applications.

Remix V3 Proposal

• Remix V3 is presented as a significant departure from V2, potentially not backwards compatible with V2, React Router, or even React.
• The core idea is to create a faster, simpler framework closer to the web itself, built on a fork of Pact.
• The proposal emphasizes performance and alignment with web standards.

The "Fundamental Flaw": AI Integration

• The main concern is the proposal to develop abstractions within the framework for applications to use AI models.
• This means baking features into the framework to support the next generation of AI apps.
• Ryan Florence confirmed that this interpretation is accurate.

Innovation Flow and the Web Tech Stack

• The traditional flow of innovation on the web is: Application -> Libraries -> Frameworks -> Web Platform.
• Applications are where innovation typically starts, driven by the need to solve specific customer problems.
• Successful solutions are then abstracted into libraries and, eventually, may be integrated into frameworks or the platform.

Framework-First vs. Application-First

• Remix V3's proposal suggests an AI feature innovation model that bubbles up from the framework to the application, which is a framework-first approach.
• The argument is that AI is evolving too rapidly for frameworks to keep up.
• Baking in specific AI features could quickly become outdated and require developers to work around them.

AI Chat as an Example

• The evolution of AI chat is used as an example of why a framework-first approach is problematic.
• Initially, AI chat involved streaming requests and responses through the server.
• Libraries like Vercel's AI library and LLM UI emerged to simplify the client and server-side streaming logic.
• However, OpenAI's new agents mechanism allows for text and voice chat to be handled on the client, eliminating the need for server-side streaming.
• If Remix V3 had baked in support for the traditional streaming method, it would already be obsolete.

Framework Requirements for AI Apps

• Frameworks should focus on providing flexible API support for AI applications.
• This includes the ability to return any type of payload, streams, SSE, and WebSockets.
• Server functions and on-demand components are nice-to-haves but not essential.
• Existing frameworks already provide adequate API support for building AI applications.
• SSR and SSG can sometimes hinder fully dynamic AI applications.

Conclusion

• The flaw in Remix V3's proposal is the attempt to integrate AI features directly into the framework.
• Frameworks should remain the stable foundation upon which applications are built.
• The AI aspect could be removed from the proposal without significantly impacting its potential.
• Remix V3 could still succeed as a performance-focused framework, competing with SolidStart, Qwik, and Fresh.