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The Ruby AI Podcast

Author: Valentino Stoll, Joe Leo

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The Ruby AI Podcast explores the intersection of Ruby programming and artificial intelligence, featuring expert discussions, innovative projects, and practical insights. Join us as we interview industry leaders and developers to uncover how Ruby is shaping the future of AI.

8 Episodes
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In this episode, Valentino Stoll and Joe Leo unpack the widening gap between headline-grabbing AI salaries and the day-to-day realities of building sustainable AI products. From sports-style contracts stuffed with equity to the true cost of running large models, they explore why incremental gains often matter more than hype. The conversation dives into the messy art of benchmarking LLMs, the fresh evaluation tools emerging in the Ruby ecosystem, and new OpenAI features that change how prompts...
Veteran Rubyist and investor Chad Fowler sits down with hosts Valentino Stoll and Joe Leo to unpack why generative AI is less a magic trick and more the next big layer of abstraction. From his days rewriting Wunderlist in multiple languages to today’s LLM-driven code generation, Chad explains how small, well-typed modules, strong conventions and agent-based workflows could let humans design systems while machines write the code. The trio debate Python vs. Ruby, micro-services vs. monoliths, c...
Evaluating LLMs with Leva

Evaluating LLMs with Leva

2025-08-2601:00:00

In this episode of the Ruby AI Podcast, host Valentino Stoll talks with special guest Kieran, a prominent figure in the Ruby AI space. Kieran recently gave a talk at the San Francisco Ruby Meetup about his new gem, Leva, which focuses on LLM evaluations in Ruby. Kieran discusses his background, his passion for AI and Ruby, as well as his journey in building AI products, including his tool Cora, which helps manage email inboxes by categorizing and summarizing emails using AI. Together, Valenti...
Ruby legend Obie Fernandez joins hosts Valentino Stoll and Joe Leo to unveil Roast—the new open-source Ruby framework for declaring reliable AI workflows—and celebrate the 1.0 release of its engine library, Raix. The trio dig into agent swarms, prompt-engineering best practices, code-base refactors, and why unleashing creativity matters more than ever in an AI-driven future." Show Notes Obie’s book — https://leanpub.com/patterns-of-application-development-using-aiRoast (GitHub) — https://gith...
Seventeen-year Ruby veteran Justin Bowen joins hosts Valentino Stoll and Joe Leo to unveil Active Agent—a Rails-native framework that treats every agent like a controller and every prompt like a view, letting you weave LLMs, vector search, and business logic straight into MVC. The crew also digs into the real-world mechanics of shipping AI: defining ground-truth datasets, replay-ready evaluation harnesses, and tight retry logic that keeps hallucinations out of production. You’ll hear a candid...
Scott Werner—author of the Works on My Machine newsletter and creator of the Sublayer AI-agent framework—joins Valentino and Joe for a fast-moving conversation on how Rubyists are bending large-language models to their will. We unpack Sublayer’s “generators + actions” architecture, the delightfully chaotic Monkey’s Paw prompt-driven web framework, and Phoenix’s AI-generated test suites, all while debating what remains uniquely human in an age of code that writes itself. If you care about Ruby...
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 m...
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 gr...
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