neuron-workflow-architect

Defining Node classes and typed events allows you to create custom event-driven workflows that route processing deterministically. You establish a shared WorkflowState across nodes to maintain context, and apply middleware to handle cross-cutting concerns like logging or validation.

Yes, you can pause long-running AI workflows for human input by using interruption patterns. The skill supports optional persistence to checkpoint progress, allowing the workflow to halt for human approvals and resume execution from its saved state once approved.

Neuron AI supports state management and middleware for complex agent orchestration by utilizing a shared WorkflowState across nodes and applying middleware for cross-cutting concerns. This allows you to manage data context and inject custom logic throughout the event-driven workflow lifecycle.

The best way to structure multi-step AI processes with branching and looping is by connecting typed events and Node-based processing. This event-driven approach forms deterministic flows, enabling reusable workflow patterns like sequential execution, conditional branching, and looping.

You stream progressive results from an orchestrated AI workflow by leveraging the skill's built-in streaming support. This feature allows you to output intermediate data and partial processing results from nodes continuously as the event-driven workflow executes.