Three talks about AI: Indispensable, Necessary Eval, and Defying Gravity
Note the earlier start time is 6:30pm to accommodate three talks!
Three talks about the AI transition:
Our first talk with Alan Riddlehoover is:
Indispensable: What Human Programmers Can Learn from Human Computers
Description:
Code used to be something we cultivated by hand. Now machines write it for us, and a quarter of a million tech workers have been laid off in less than a year. If you've been quietly grieving your relationship with code, you're not alone. And you're not the first. In 1958, NASA began replacing its human computers with IBM mainframes. Three women from the segregated West Area Computing Unit — Dorothy Vaughan, Mary Jackson, and Katherine Johnson — made themselves indispensable to the mission anyway. Each chose a different strategy: retool, transform, or specify. Now it's our turn as Rubyists. The mission is still here. The role is not. This talk borrows their strategies, with gratitude, for the transition we're living through now — and shows how to stay indispensable.
Our second talk with Fito Von Zastrow is:
Defying Gravity
Description:
Code reviews got slower after we introduced AI into our Ruby on Rails monolith. AI-generated code was making the legacy problems worse, not better. Technical debt, fat controllers, tests coupled to implementation. AI reproduced all of it, faster than ever. It's as if legacy code has gravity. In this talk, you’ll learn the concrete techniques we use in production: how to specify what you want, how to provide architectural guidance to agents, and how to use skills to put guardrails in place so feature work incrementally improves the codebase instead of reinforcing legacy patterns. Leave with everything you need to defy Legacy Gravity.
Our third talk with Caleb Buxton is:
Necessary Eval: How Empirical Methods Improve AI Transitions
Description:
The AI transition doesn't feel like a clean upgrade. For decades the crux of the role was your skills and your experience. What happens when an external force barges into the arena? Do jobs feel threatened? Are you a developer, or an AI-prompt expert? The work keeps shifting under you, and it's hard to keep up. Grief's got its stages, and so too does this change. The curve we're riding knocks you down, you climb back up, and the next release knocks you down again. What do you do when you're at the bottom? How do we know what works? Enter Dr. Cat Hicks, who put numbers to the things the rest of us only feel: skill threat, code review anxiety, how teams thrive. She didn't guess. She measured. From there, we adapt the tools Rubyists built our careers on. The bridge runs from TDD, through Andrew Ng's function approximator, and lands on EDD: write the eval first. Day one, we learn: never use eval. This talk is about the other one. Use it on yourself, your craft, and your team.
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