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Episode 59 - Scott Werner

18 de novembro de 2025 · 50 min

Notas do episódio

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.

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