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 meetups
• Agentic coding & tooling
  • Claude Code docs
  • Claude Code + MCP
• Books, papers, and ideas
  • C. Thi Nguyen (background)
  • Games: Agency as Art (Oxford)
  • Ezra Klein Show episode (Nguyen)
  • Malcolm Gladwell, Outliers
  • Andy Hunt, Pragmatic Thinking and Learning (Refactor Your Wetware)
  • Ericsson et al. (1993) deliberate practice (DOI)
  • Macnamara & Maitra replication (2019) (DOI)
  • David Epstein, Range
  • Will Larson, Staff Engineer
  • Robert Cialdini, Influence resources
  • DHH on conceptual compression
  • Chad 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 experiments
  • Ruby method_missing
  • Ruby define_method
  • Rails rescue_from
  • Valentino's experimental Ruby project (“Chaos to the Rescue”) that uses LLMs + runtime method definition

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.

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.