Phoenix.new – Remote AI Runtime for Phoenix (fly.io)

Article summary

Chris McCord, the creator of Elixir's Phoenix framework, has introduced Phoenix.new, a remote AI runtime for Phoenix that allows for collaborative, real-time application development. Phoenix.new provides a fully online coding environment with a root shell and a headless browser, enabling agents to interact with web applications and build software. The system is designed to work seamlessly with Elixir and Phoenix, and can also be used with other languages and frameworks. Phoenix.new aims to simplify the development process and make it more efficient.

Main themes

• Elixir and Phoenix development
• LLMs and code generation
• Package maintenance and ecosystem size
• Productivity and efficiency in development
• AI-powered development tools
• Language and framework adoption

What commenters say

• Some commenters believe that Elixir's relatively small size and lack of maintenance for certain packages may hinder its adoption and productivity.
• Others argue that the quality of Elixir's packages is not necessarily tied to their maintenance status, and that many old packages still work well.
• There is a perception that LLMs may not write Elixir code as well as they write code for other languages, which could be a selling point for Elixir from a developer's perspective.
• However, some commenters have had positive experiences with LLMs like Claude and o3, which they claim can produce high-quality Elixir code.
• The discussion also touches on the idea that the Elixir ecosystem may be limited by its size, making it harder for developers to find maintained libraries and tools.
• On the other hand, some argue that Elixir's size is not a significant drawback, and that the language is still capable of producing high-quality applications.
• The use of LLMs in development is seen as a potential game-changer, with some commenters noting that they have been able to build entire features and applications using these tools.
• However, others express concerns about the potential drawbacks of relying on LLMs, such as the quality of the generated code and the potential for errors or security vulnerabilities.