Show HN: SWEny, YAML workflows for AI agents I'm running in prod (triage, E2E) (github.com)

A new tool called SWEny has been introduced to streamline the development of AI workflows using YAML configurations, enabling users to define tasks in plain language and generate directed acyclic graphs (DAGs) for AI agents. By utilizing the command line interface (CLI), developers can quickly create and run workflows for various applications, such as security audits and code reviews, with the ability to visualize these workflows as Mermaid diagrams. This approach not only automates the workflow creation process but also integrates with popular platforms like GitHub for continuous integration, supporting execution without connecting to external networks unless desired. The significance of SWEny lies in its potential to enhance productivity in the AI and machine learning community by making workflow management accessible and efficient. Users can leverage reusable skills designed for cross-tool compatibility and easily customize workflows through a marketplace. This innovation contributes to the rising trend of "AI workflows as code," providing a structured method to implement AI-driven tasks, track tool usage, and foster collaboration within teams. With built-in privacy features and the capability to run locally or in cloud environments, SWEny represents a significant advancement in AI workflow automation that could streamline operations across various development teams.