AI Amplifies What's Already There
What I took away from Tropical Rails 2025.
I went to Tropical Rails with the usual expectations: see what the Ruby community is up to, check out new tools, talk to people. I didn’t expect the entire conference to orbit around a single topic. But it did. AI and agents. Not in the “check out this new tool” sense, but in the “this changes the rules and we need to talk seriously” sense.
The takeaway
The conclusion I walked away with, and the thread running through almost every talk: LLMs and AI agents don’t have opinions about code quality, they amplify what’s already there. If good patterns go in, good code comes out. If tech debt goes in, more tech debt comes out, and faster.
If the codebase isn’t clean and prepared to scale, it won’t be able to keep up with product growth. And now that agents produce code at a pace no human can review, tech debt has stopped being just a quality problem and become a capacity problem.
This was true before too, but it never mattered this much.
Two tools that stuck with me
Two gems came up multiple times and stayed on my mind.
evil-seeds, like a database dump but smart. You can configure how data gets scrubbed, which tables to include, how many records to pull. Sounds like a good path to finally having a clean, safe copy of production to work with locally.
Blazer, for spotting weird or inconsistent data in production. The idea of having something that actively monitors data health is something we could use, whether or not we adopt this specific tool.
The real takeaway
If we’re serious about using AI to move faster, the codebase needs to be in a state that makes that possible. Agents amplify tech debt, they don’t fix it. I came back from the conference wanting to pay down technical debt, which is not something you hear people say very often.