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

• Phoenix by DefMethod – https://www.phoenix.love/
• OpenAI Ruby SDK – https://github.com/openai/openai-ruby
• Sublayer – https://github.com/sublayerapp/sublayer
• CrewAI – https://github.com/crewAIInc/crewAI
• Active Agent – https://github.com/activeagents/activeagent
• Raix – https://github.com/OlympiaAI/raix
• Shopify Roast – https://github.com/Shopify/roast
• LangChain.rb – https://github.com/patterns-ai-core/langchainrb
• Hugging Face smolagents – https://huggingface.co/docs/smolagents/index
• Building Code Agents with Hugging Face smolagents – https://www.deeplearning.ai/short-courses/building-code-agents-with-hugging-face-smolagents/
• V's side project, NowReading.dev – https://nowreading.dev

In this episode of the Ruby AI podcast, hosts Landon and Valentino discuss the exciting developments in the Ruby AI community. They explore three key gems: Ruby OpenAI, Raix, and Langchain.rb, highlighting their features, use cases, and the importance of evaluation methodologies like RAGAS in AI systems. The conversation emphasizes the collaborative spirit of the Ruby AI community and the potential for innovation in AI applications using Ruby.

Takeaways

• The Ruby AI community is vibrant and growing.
• Ruby OpenAI is essential for integrating OpenAI's capabilities.
• Raix gem offers an object-oriented approach to AI in Ruby.
• Langchain RB normalizes AI provider integrations in Ruby.
• RAGAS provides a framework for evaluating AI outputs.
• Community engagement is crucial for Ruby AI's growth.
• Documentation is key for developers using these gems.
• Collaboration among developers enhances innovation.
• AI systems require robust evaluation methodologies.
• Ruby is at the forefront of AI development.

Sound Bites

• "This is gonna be really exciting."
• "Join the Ruby AI Builders Discord."
• "There's so much cool stuff out there."