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Episode 59 - Scott Werner

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Manage episode 520084898 series 3310917
内容由Drew Bragg提供。所有播客内容(包括剧集、图形和播客描述)均由 Drew Bragg 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.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.

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Honeybadger is an application health monitoring tool built by developers for developers.
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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

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章节

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集单集

Artwork
icon分享
 
Manage episode 520084898 series 3310917
内容由Drew Bragg提供。所有播客内容(包括剧集、图形和播客描述)均由 Drew Bragg 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.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

章节

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)

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