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Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Beyond Chat: Phoenix Tests, Ruby Agents & the AI Tipping Point

53:05
 
공유
 

Manage episode 485515091 series 3642718
Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Valentino Stoll and co-host Joe Leo kick off The Ruby AI Podcast with a candid deep-dive into what it really takes to ship AI-powered products in Ruby today. From the origin story of Joe’s test-writing automation platform Phoenix to the surge of new Ruby-first agent libraries, the duo explore why the community is approaching a tipping point, how to escape “chat-bot-only” thinking, and where reactive, evaluation-driven tooling is headed next. Along the way they trade war stories about semver mishaps, code-review “LLM tells,” and the projects, meet-ups, and conferences that keep the Ruby-AI scene buzzing.

Takeaways

  • The Ruby AI community is growing and offers valuable networking opportunities.
  • Ruby's syntax is well-suited for AI applications, making it a fun choice for developers.
  • Generative AI tools can increase productivity but also add cognitive burden to developers.
  • The integration of AI tools in Ruby applications presents unique challenges.
  • Developers are relearning how to program with the advent of generative AI.
  • AI frameworks are evolving, and Ruby developers need to stay updated.
  • The importance of evaluating AI tools and their effectiveness in real-world applications.
  • Ruby's flexibility allows for creative solutions in AI development.
  • The future of AI in software development will require continuous adaptation.
  • Emerging AI frameworks in Ruby are promising but require careful evaluation.

Referenced In The Show

  continue reading

12 에피소드

Artwork
icon공유
 
Manage episode 485515091 series 3642718
Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Valentino Stoll and co-host Joe Leo kick off The Ruby AI Podcast with a candid deep-dive into what it really takes to ship AI-powered products in Ruby today. From the origin story of Joe’s test-writing automation platform Phoenix to the surge of new Ruby-first agent libraries, the duo explore why the community is approaching a tipping point, how to escape “chat-bot-only” thinking, and where reactive, evaluation-driven tooling is headed next. Along the way they trade war stories about semver mishaps, code-review “LLM tells,” and the projects, meet-ups, and conferences that keep the Ruby-AI scene buzzing.

Takeaways

  • The Ruby AI community is growing and offers valuable networking opportunities.
  • Ruby's syntax is well-suited for AI applications, making it a fun choice for developers.
  • Generative AI tools can increase productivity but also add cognitive burden to developers.
  • The integration of AI tools in Ruby applications presents unique challenges.
  • Developers are relearning how to program with the advent of generative AI.
  • AI frameworks are evolving, and Ruby developers need to stay updated.
  • The importance of evaluating AI tools and their effectiveness in real-world applications.
  • Ruby's flexibility allows for creative solutions in AI development.
  • The future of AI in software development will require continuous adaptation.
  • Emerging AI frameworks in Ruby are promising but require careful evaluation.

Referenced In The Show

  continue reading

12 에피소드

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