The Ruby AI Podcast

Valentino Stoll, Joe Leo

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.

  1. CRMs Don’t Have to Suck: Rebuilding Business Software with AI and Ruby with Thomas Witt

    10 MRT

    CRMs Don’t Have to Suck: Rebuilding Business Software with AI and Ruby with Thomas Witt

    Many “AI startups” today are little more than thin wrappers around large language model APIs. But what happens when those APIs improve and the platforms absorb those features? In this episode of The Ruby AI Podcast, Valentino Stoll and Joe talk with builder and investor Thomas Witt, founder of Vendis.ai and operator of the pre-seed firm Expedite Ventures. Thomas shares why he believes the next generation of durable companies must deliver real value deep in the product stack rather than bolting chat onto existing software. The conversation explores why traditional CRMs are widely disliked and how an AI-native CRM might look completely different. Instead of rigid forms and required fields, Thomas describes a system where conversations themselves become the primary data source. Emails, meetings, and messages are embedded, searched semantically, and transformed into structured knowledge automatically. They also dive into the architecture required to support this shift. From Ruby on Rails and Hotwire to DynamoDB, vector search, async Ruby, and multi-model LLM workflows, Thomas shares practical lessons from building AI-heavy production systems. Along the way the discussion touches on agentic coding workflows, LLM-as-a-judge evaluation patterns, telemetry for prompt chains, and why small teams may soon replace the massive engineering orgs we’ve grown used to. If you’re curious where Ruby, Rails, and AI systems are heading next, this conversation offers a fascinating glimpse. Show Notes Guest: Thomas Witt Founder of Vendis.ai Investor at Expedite Ventures Topics we explore • Why many AI startups are just “wrappers” around LLM APIs  • What an AI-native CRM looks like when conversations become the database • Why Thomas chose Ruby on Rails with minimal JavaScript using Hotwire and Stimulus • Using Amazon DynamoDB instead of relational databases for AI workloads • Hybrid keyword + vector search with OpenSearch and Elasticsearch • Async Ruby patterns using fibers, the Async ecosystem, and the Falcon web server • Orchestrating many concurrent LLM calls within a single user interaction • Background job systems and queues such as Amazon SQS • Code quality workflows with StandardRB and RuboCop • Using models like Claude, OpenAI Codex, and Gemini together in multi-model workflows • Observability and prompt tracing with Langfuse • Why AI tooling may enable much smaller engineering teams Mentioned in the Show • Vendis.ai – Thomas’s AI-native CRM platform • Hotwire – HTML-over-the-wire approach for modern Rails apps • Falcon – Fiber-based Ruby web server • Ruby AI Builders Discord – Community of Ruby developers building AI tools • Chaos to the Rescue @ Artificial Ruby

    1 u
  2. Innovating Development: The Future of GitHub Agents and AI in Rails

    24 FEB

    Innovating Development: The Future of GitHub Agents and AI in Rails

    In this episode of the Ruby AI Podcast, hosts Joe and Valentino welcome special guest, Kinsey Durham Grace, a prominent figure in the Ruby community and member of the GitHub team. The discussion covers a range of topics including the use of AI for generating episode artwork, the application of AI agents in coding tasks, and the recent developments at GitHub like the Agent HQ. Kinsey shares insights into her day-to-day work on the coding agent core team at GitHub, including the use of custom agents to enhance coding efficiency. They also delve into the impact of AI on software development, the importance of well-rounded developer skills, and Kinsey’s perspective on the future of Ruby in the AI landscape. 00:00 Introduction and Guest Welcome 00:30 AI-Generated Images and Their Drawbacks 03:07 Kinsey's Role at GitHub 06:33 Using AI Tools in Development 11:26 Challenges in Large Monolith Apps 18:23 Modular and Maintainable Agents 24:47 AI's Role in Software Development 25:29 Challenges with Current AI Tools 26:50 Observational Memory in AI 27:42 Open Claw and Heartbeat Concepts 28:22 Collaborative AI and Future Prospects 29:22 In-House vs. Third-Party Observability Tools 29:54 New AI Products and Intent Capture 31:08 Persisting Context in Software Development 37:42 Custom Agents and Knowledge Management 46:13 The Human Element in AI Collaboration 47:20 Skills for the Future of AI in Engineering 48:54 Ruby and AI: Staying Relevant 50:50 Conclusion and Final Thoughts 🔗 Resources Mentioned in This Episode Kinsey’s talk at RailsWorld 2025: The Rise of the Agents In Rails GitHub & Agent Workflows https://github.comhttps://github.com/features/copilothttps://github.bloghttps://cli.github.comhttps://code.visualstudio.comhttps://github.com/features/codespacesModels & AI Tools Mentioned https://claude.aihttps://www.anthropic.comhttps://openai.comhttps://platform.openai.comhttps://gemini.google.comhttps://cursor.shhttps://ampcode.comObservability & Infrastructure https://www.datadoghq.comhttps://learn.microsoft.com/en-us/azure/data-explorer/kusto/query/OpenClaw https://openclaw.aihttps://github.com/OpenClawMastra AI https://mastra.aiQMD (Referenced by Valentino) https://github.com/tobi/qmdStephen Margheim – SQLite / Ruby Work https://fractaledmind.github.iohttps://github.com/digital-fabric/extraliteGitHub-Related Announcements (Former CEO Mention) https://entire.io/

    51 min
  3. From Writing Code To Orchestrating It, Agentic Development with Ben Scofield

    10 FEB

    From Writing Code To Orchestrating It, Agentic Development with Ben Scofield

    In this episode of the Ruby AI Podcast, hosts Valentino Stoll and Joe Leo are joined by Ben Schofield, an accomplished author, open source contributor, and Ruby enthusiast. The discussion starts with thoughts on the upcoming RubyConf and the unique experience of conferences hosted in Las Vegas. Ben shares his recent experiences with Bento and the impact of layoffs. The conversation delves deep into the nature of expertise, exploring questions around achieving world-class performance and domain-specific skills. The hosts explore the goals of software development, the role of AI in coding, and the importance of intentionality in using agents. They also touch on the concept of default settings in development, the nuances of staff engineering, and strategies for training future staff engineers. The discussion concludes with ideas for improving the onboarding and training of engineers in the evolving landscape of AI tools. Mentioned in this episode: RubyConf 2026 (Las Vegas)RailsConf (context/history)O’Reilly (RailsConf partner mentioned historically)Bento (Ben’s recent company)Gusto (host context)Artificial Ruby / Ruby x AI NYC meetupsAgentic coding & toolingClaude Code docsClaude Code + MCPBooks, papers, and ideasC. Thi Nguyen (background)Games: Agency as Art (Oxford)Ezra Klein Show episode (Nguyen)Malcolm Gladwell, OutliersAndy Hunt, Pragmatic Thinking and Learning (Refactor Your Wetware)Ericsson et al. (1993) deliberate practice (DOI)Macnamara & Maitra replication (2019) (DOI)David Epstein, RangeWill Larson, Staff EngineerRobert Cialdini, Influence resourcesDHH on conceptual compressionChad Fowler, The Phoenix Architecture (Leaflet)Quote referenced (“How can I know what I think till I see what I say?”)Ruby/Rails primitives referenced in Valentino's experimentsRuby method_missingRuby define_methodRails rescue_fromValentino's experimental Ruby project (“Chaos to the Rescue”) that uses LLMs + runtime method definition

    53 min
  4. New Year, New Ruby: Agents, Wishes, and a Calm Ruby 4

    27 JAN

    New Year, New Ruby: Agents, Wishes, and a Calm Ruby 4

    Ruby turns 30, Ruby 4 quietly ships, and the AI tooling arms race shows signs of maturity. Valentino and Joe unpack what stability really means for a language in its third decade, debate agent-driven development, AI “slop,” binary distribution, and whether open source incentives are breaking down—or simply evolving. Mentioned In The Show A grab-bag of tools, projects, and references Valentino & Joe brought up. Ruby & Core Ecosystem Ruby Gets A Fresh Look — Official Ruby programming language site (news, downloads, docs) now with a great new look.  Ruby Kaigi — Ruby’s flagship conference (talks, schedules, archives). Bundler — Ruby dependency manager used across the ecosystem.AI Coding Tools Claude Code — Anthropic’s CLI coding assistant workflow discussed heavily in the episode.OpenAI Codex — OpenAI’s coding agent/tooling referenced as an alternative workflow. Ruby Web Frameworks & Architecture Rails Framework — Ruby on Rails, referenced as the default baseline for many apps.Jumpstart Rails — Rails starter kits/templates mentioned as a “pick a Rails” approach.Roda Framework — Jeremy Evans’ web toolkit (lighter than Rails, bigger than Sinatra).dry-rb Suite — Ruby gems for functional-ish architecture and explicit business logic.Trailblazer — High-level architecture for operations, workflows, and domain logic.Quality, Testing, and Practice Better Specs — Community-curated RSpec guidelines mentioned as a spec style target.Datadog — Error monitoring referenced in the “well-defined bug + stack trace” workflow.Open Source Sustainability GitHub Sponsors — Sponsorship mechanism discussed as one (partial) monetization path.People Mentioned Sandi Metz — Referenced as the “code whisperer” ideal for idiomatic Ruby guidance.

    51 min
  5. Real vs. Fake AI with Evan Phoenix

    6 JAN

    Real vs. Fake AI with Evan Phoenix

    In this episode of the Ruby AI podcast, hosts Valentino Stoll and Joe Leo engage with Evan Phoenix, a seasoned Ruby programmer and CEO of Mirren. The conversation explores Evan's unique name origin, his career trajectory, and the integration of AI in development workflows. They discuss the distinction between real and fake AI in products, the impact of AI on engineering practices, and the future of AI in development tools. Evan shares insights on performance optimization, human-centric AI interactions, and the role of AI in deployment and architecture detection. In this conversation, Joe, Evan Phoenix, and Valentino Stoll discuss the evolving landscape of software development, particularly focusing on the role of AI, automation, and the Ruby programming language. They explore how AI can assist in analyzing code bases, the future of development with ambient agents, and the potential resurgence of monolithic architectures. The discussion also touches on the importance of human-centric design in software, the significance of experimentation, and the unique strengths of Ruby in the current tech environment. The conversation concludes with predictions about the future of small teams in software development and the impact of AI on coding practices.

    1u 2m
  6. Running Self-Hosted Models with Ruby and Chris Hasinski

    02-12-2025

    Running Self-Hosted Models with Ruby and Chris Hasinski

    In this episode of the Ruby AI Podcast, hosts Valentino Stoll and Joe Leo welcome AI and Ruby expert Chris Hasinski. They delve into the benefits and challenges of self-hosting AI models, including control over model updates, cost considerations, and the ability to fine-tune models. Chris shares his journey from machine learning at UC Davis to his extensive work in AI and Ruby, touching upon his contributions to open source projects and the Ruby AI community. The discussion also covers the limitations of current LLMs (Large Language Models) in generating Ruby code, the importance of high-quality data for effective AI, and the potential for Ruby to become a strong contender in AI development. Whether you're a Ruby enthusiast or interested in the intersection of AI and software development, this episode offers valuable insights and practical advice. 00:00 Introduction and Guest Welcome 00:31 Why Self-Host Models? 01:28 Challenges and Benefits of Self-Hosting 03:14 Chris's Background in Machine Learning 04:13 Applications Beyond Text 06:39 Fine-Tuning Models 12:27 Ruby in Machine Learning 16:06 Distributed Training and Model Porting 18:22 Choosing and Deploying Models 25:19 Testing and Data Engineering in Ruby 27:56 Database Naming Conventions in Different Languages 28:19 Importance of Data Quality for AI 18:03 Monitoring Locally Hosted AI Models 29:37 Challenges with LLMs and Performance Tracking 31:09 Improving Developer Experience in Ruby 31:45 Ruby's Ecosystem for Machine Learning 32:43 The Need for Investment in Ruby's AI Tools 38:25 Challenges with AI Code Generation in Ruby 43:35 Future Prospects for Ruby in AI 51:26 Conclusion and Final Thoughts

    54 min
  7. The Latent Spark: Carmine Paolino on Ruby’s AI Reboot

    18-11-2025

    The Latent Spark: Carmine Paolino on Ruby’s AI Reboot

    In this episode of the Ruby AI Podcast, hosts Joe Leo and his co-host interview Carmine Paolino, the developer behind Ruby LLM. The discussion covers the significant strides and rapid adoption of Ruby LLM since its release, rooted in Paolino's philosophy of building simple, effective, and adaptable tools. The podcast delves into the nuances of upgrading Ruby LLM, its ever-expanding functionality, and the core principles driving its design. Paolino reflects on the personal motivations and community-driven contributions that have propelled the project to over 3.6 million downloads. Key topics include the philosophy of progressive disclosure, the challenges of multi-agent systems in AI, and innovative ways to manage contexts in LLMs. The episode also touches on improving Ruby’s concurrency handling using Async and Rectors, the future of AI app development in Ruby, and practical advice for developers leveraging AI in their applications. 00:00 Introduction and Guest Welcome 00:39 Depend Bot Upgrade Concerns 01:22 Ruby LLM's Success and Philosophy 05:03 Progressive Disclosure and Model Registry 08:32 Challenges with Provider Mechanisms 16:55 Multi-Agent AI Assisted Development 27:09 Understanding Context Limitations in LLMs 28:20 Exploring Context Engineering in Ruby LLM 29:27 Benchmarking and Evaluation in Ruby LLM 30:34 The Role of Agents in Ruby LLM 39:09 The Future of AI Apps with Ruby 39:58 Async and Ruby: Enhancing Performance 45:12 Practical Applications and Challenges 49:01 Conclusion and Final Thoughts

    52 min
  8. Building Futures: AI, Careers & the Rails Ahead with Avi Flombaum

    04-11-2025

    Building Futures: AI, Careers & the Rails Ahead with Avi Flombaum

    In this episode of the Ruby AI Podcast, hosts Valentino Stoll and Joe Leo are joined by Avi Flombaum, the founder of Flatiron School. Avi talks about the origins of Flatiron, the success it achieved, and the educational methods used to teach programming, emphasizing on the importance of understanding code deeply and leveraging AI efficiently. He discusses the challenges and changes in the industry, particularly with the rise of AI, and provides insight into modern workflows and product development. The conversation also touches on the necessity of integrating product thinking into engineering and how automated workflows can improve consistency and efficiency in software creation. 00:00 Introduction and Welcoming Avi Flombaum 00:55 Avi's Journey to Founding Flatiron School 02:22 The Impact and Growth of Flatiron School 04:40 Challenges and Evolution in the Bootcamp Industry 05:39 Transitioning from Education to AI 06:39 The Role of AI in Modern Development 08:14 Effective AI Workflows for Developers 16:08 Teaching and Learning with AI 20:47 Product Management and Engineering Collaboration 27:31 Leveraging AI in Product Development 28:35 Exploring AI-Driven Product Development 29:42 Teaching Product Management Skills 30:49 Innovative Solutions in Product Design 32:25 Understanding User Needs and Problem Solving 35:33 Learning Through Code and AI Tools 42:38 The Future of Software Engineering

    52 min
Bekijk alles (18)

Trailer

Info

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.

Informatie

  • Maker
    Valentino Stoll, Joe Leo
  • Jaren actief
    2025 - 2026
  • Afleveringen
    18
  • Beoordeling
    Expliciet
  • Copyright
    © 2026 The Ruby AI Podcast
  • Website van aflevering
    The Ruby AI Podcast

Suggesties voor jou