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Content provided by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
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Beyond Chat: Phoenix Tests, Ruby Agents & the AI Tipping Point

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Manage episode 485515091 series 3642718
Content provided by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/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

2 episodes

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Manage episode 485515091 series 3642718
Content provided by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Valentino Stoll, Joe Leo, Valentino Stoll, and Joe Leo or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/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

2 episodes

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