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
Información
- Programa
- FrecuenciaDos veces al mes
- Publicado10 de febrero de 2026, 2:00 p.m. UTC
- Duración53 min
- Temporada1
- Episodio15
- ClasificaciónApto
