Artwork

Contenido proporcionado por Drew Bragg. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Drew Bragg o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
Player FM : aplicación de podcast
¡Desconecta con la aplicación Player FM !

Episode 59 - Scott Werner

49:16
 
Compartir
 

Manage episode 520084898 series 3310917
Contenido proporcionado por Drew Bragg. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Drew Bragg o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

What if AI could make your work more creative instead of more crowded? We sit down with Scott Werner to unpack a practical path for Ruby developers who want the leverage of AI without sacrificing taste, clarity, or joy. From agentic coding with Claude Code to context-rich tools like Tidewave, we walk through how better inputs—logs, DOM access, database state—turn generic suggestions into usable plans that reduce cognitive load and speed up real problem solving.
Scott shares the origin story of Artificial Ruby, a New York meetup that started as a casual happy hour and became a monthly mini conference. That community energy matters: many devs began their careers remotely and missed the spark of live conversations. By focusing on play and curiosity, the group channels the early Ruby vibe—ship small experiments, trade sharp feedback, and rediscover the fun of making software together. That ethos powers Scott’s projects: Monkey’s Paw, a prompt-based web framework that leans into expressive generation, and Latent Library, a hallucinatory book explorer that asks what new interfaces AI enables.
We also tackle the “slop generator” problem and how to curb it. Different models have different tendencies, so route tasks where they fit: broad ideation to one, surgical changes to another. Constrain edits, ask for reasoning before code, and hand the model real context so it can propose focused steps. The same philosophy informs testing with computer-use models: if an agent can’t find your logout or complete checkout by looking at the UI, maybe your users struggle too. Rather than replacing developers, these tools elevate the craft—pushing commodity work downward while widening the canvas for design, problem framing, and tasteful implementation.
Want more? Check out ArtificialRuby.ai for upcoming events and videos, explore LatentLibrary.xyz, and find Scott’s essays and tutorials at WorksOnMyMachine.ai. If this conversation helps you rethink your workflow, follow, share with a teammate, and leave a review so more builders can join the experiment.

Send us some love.

Honeybadger
Honeybadger is an application health monitoring tool built by developers for developers.
Judoscale
Autoscaling that actually works. Take control of your cloud hosting.
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
Support the show

  continue reading

Capíttulos

1. Meet Scott And Set The Stage (00:00:00)

2. What Sublayer Builds With AI And Ruby (00:01:38)

3. Training, Newsletter, And Video Series (00:03:35)

4. Artificial Ruby: Community Origins (00:03:58)

5. In‑Person Meetups And Pandemic Careers (00:06:08)

6. What Ruby Needs For AI Adoption (00:10:12)

7. Using AI As Context Partner Not Coder (00:15:46)

8. Model Personalities And Monkey’s Paw (00:20:45)

9. Play, Why’s Spirit, And Latent Library (00:23:42)

10. Rails Scaffolds, AI, And Real Work (00:28:59)

11. Blockers Shift: Context And Throughput (00:32:01)

12. Humans Provide Ideas; AI Needs Prompts (00:36:16)

13. Craft Vs Commodity And New Layers (00:42:13)

14. Computer Use Models And Testing Agents (00:47:43)

66 episodios

Artwork
iconCompartir
 
Manage episode 520084898 series 3310917
Contenido proporcionado por Drew Bragg. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Drew Bragg o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

What if AI could make your work more creative instead of more crowded? We sit down with Scott Werner to unpack a practical path for Ruby developers who want the leverage of AI without sacrificing taste, clarity, or joy. From agentic coding with Claude Code to context-rich tools like Tidewave, we walk through how better inputs—logs, DOM access, database state—turn generic suggestions into usable plans that reduce cognitive load and speed up real problem solving.
Scott shares the origin story of Artificial Ruby, a New York meetup that started as a casual happy hour and became a monthly mini conference. That community energy matters: many devs began their careers remotely and missed the spark of live conversations. By focusing on play and curiosity, the group channels the early Ruby vibe—ship small experiments, trade sharp feedback, and rediscover the fun of making software together. That ethos powers Scott’s projects: Monkey’s Paw, a prompt-based web framework that leans into expressive generation, and Latent Library, a hallucinatory book explorer that asks what new interfaces AI enables.
We also tackle the “slop generator” problem and how to curb it. Different models have different tendencies, so route tasks where they fit: broad ideation to one, surgical changes to another. Constrain edits, ask for reasoning before code, and hand the model real context so it can propose focused steps. The same philosophy informs testing with computer-use models: if an agent can’t find your logout or complete checkout by looking at the UI, maybe your users struggle too. Rather than replacing developers, these tools elevate the craft—pushing commodity work downward while widening the canvas for design, problem framing, and tasteful implementation.
Want more? Check out ArtificialRuby.ai for upcoming events and videos, explore LatentLibrary.xyz, and find Scott’s essays and tutorials at WorksOnMyMachine.ai. If this conversation helps you rethink your workflow, follow, share with a teammate, and leave a review so more builders can join the experiment.

Send us some love.

Honeybadger
Honeybadger is an application health monitoring tool built by developers for developers.
Judoscale
Autoscaling that actually works. Take control of your cloud hosting.
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
Support the show

  continue reading

Capíttulos

1. Meet Scott And Set The Stage (00:00:00)

2. What Sublayer Builds With AI And Ruby (00:01:38)

3. Training, Newsletter, And Video Series (00:03:35)

4. Artificial Ruby: Community Origins (00:03:58)

5. In‑Person Meetups And Pandemic Careers (00:06:08)

6. What Ruby Needs For AI Adoption (00:10:12)

7. Using AI As Context Partner Not Coder (00:15:46)

8. Model Personalities And Monkey’s Paw (00:20:45)

9. Play, Why’s Spirit, And Latent Library (00:23:42)

10. Rails Scaffolds, AI, And Real Work (00:28:59)

11. Blockers Shift: Context And Throughput (00:32:01)

12. Humans Provide Ideas; AI Needs Prompts (00:36:16)

13. Craft Vs Commodity And New Layers (00:42:13)

14. Computer Use Models And Testing Agents (00:47:43)

66 episodios

Todos los episodios

×
 
Loading …

Bienvenido a Player FM!

Player FM está escaneando la web en busca de podcasts de alta calidad para que los disfrutes en este momento. Es la mejor aplicación de podcast y funciona en Android, iPhone y la web. Regístrate para sincronizar suscripciones a través de dispositivos.

 

Guia de referencia rapida

Escucha este programa mientras exploras
Reproducir