create-skills-workflow

You create multi-step AI workflows by using a micro-file architecture with progressive step loading, state persistence, and interactive decision points. This methodology ensures sophisticated AI processes remain clear and maintainable throughout execution.

Progressive step loading is an AI development technique that minimizes context by loading one workflow step at a time. It enables multi-step AI skills to execute complex phases without overwhelming the model's context window.

You build a sequential AI workflow by defining structured phases with state persistence and interactive decision points. This allows an AI assistant to analyze code, generate a refactoring plan, execute changes, and run tests as a single coherent process.

Yes, you can implement conditional logic and user-driven choices using interactive decision points within a structured workflow design. This facilitates user input and dynamic branching while maintaining state persistence across different execution phases.

Building complex AI skills with this workflow methodology requires no external dependencies. It uses a self-contained micro-file architecture and references to guide the creation and execution of professional multi-step workflows.

The best way to manage state across multiple AI workflow phases is through structured state persistence within a micro-file architecture. This ensures data is maintained accurately across different steps and interactive decision points.