When we talk about building with AI, most of the attention goes to what’s new. Models, agent frameworks, protocols, and tools seem to appear every week, making it easy to assume that adopting AI means introducing an entirely new technology stack.
But Rails developers already have many of the building blocks needed to create useful AI-assisted workflows. Generators, Rake tasks, command-line interfaces, schemas, tests, and APIs were designed to make software easier to work with by providing structure and predictable behavior. Those same qualities make them well suited for AI coding tools.
In this context, an AI-assisted workflow doesn’t mean building an agent into a Rails application. It can be as simple as a developer using an AI coding tool to complete a task in an existing codebase, whether that’s adding a feature, running tests, analyzing technical debt, or helping with a Rails upgrade. As these tools become capable of taking more actions on a developer’s behalf, they need reliable ways to interact with the codebase and the tooling around it.
This article explores how existing Ruby and Rails tooling can become part of AI-assisted development, and why introducing AI doesn’t require starting from scratch.
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