Domain-Driven Agents

The author explains that large language models excel in greenfield projects but struggle with legacy codebases riddled with inconsistent terminology and missing domain language, causing incorrect guesses. By separating strategic decisions—understanding and planning changes—from tactical implementation, they use AI agents and reusable markdown-based skills to automate refactoring and issue resolution, reducing the manual effort of tech-debt cleanup.