sushi-sequence

Multi-step research pipelines are orchestrated by coordinating actions in a serial sequence, where the output of one step automatically becomes the input for the next. This ensures ordered processes and strict dependency management across all configured tasks.

Task sequence steps can be either AI-planned or manually defined based on your input requirements and desired output schemas. AI planning dynamically structures the pipeline, while manual configuration offers precise control over the ordered execution logic.

Sequence management for structured research coordinates complex tasks like competitive intelligence by linking market analysis, profiling, and discovery into a single logical sequence. It ensures each dependent action executes in the correct order to produce final results.

Multi-step sequence execution relies on the orchestrator and ai-orchestrator dependencies to manage pipeline flow. These dependencies enable the system to coordinate serial actions, handle diverse input types, and pass outputs between steps automatically.

The best way to run a competitive intelligence sequence is to issue a command like sequence: 'Build a competitive intelligence package for [Company].' The pipeline then links market analysis, competitor profiling, and contact discovery in a logical order.