Who should use the Agent Orchestration workflow?
Teams or solo builders working on development tasks who want a repeatable process instead of one-off tool experiments.
Execution Map
7-step pipeline — follow each step in order
1Setup · Step 1 of 7
Open task pageCustomizable agent design and configuration
Prepare inputs and settings through Customizable agent design and configuration before running agent orchestration.
Why this matters
Customizable agent design and configuration sets up the foundation for agent orchestration; clean inputs here reduce downstream rework.
What you get
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
2Input · Step 2 of 7
Open task pageCollaborative problem solving with AI agents
Use Collaborative problem solving with AI agents to build supporting assets that improve agent orchestration quality.
Why this matters
Collaborative problem solving with AI agents strengthens agent orchestration by feeding better supporting material into the pipeline.
What you get
Supporting assets from collaborative problem solving with ai agents are prepared and connected to the main workflow.
3Input · Step 3 of 7
Open task pageMulti-agent task decomposition
Use Multi-agent task decomposition to build supporting assets that improve agent orchestration quality.
Why this matters
Multi-agent task decomposition strengthens agent orchestration by feeding better supporting material into the pipeline.
What you get
Supporting assets from multi-agent task decomposition are prepared and connected to the main workflow.
4Core · Step 4 of 7
Open task pageAgent Orchestration
Execute agent orchestration with Agent Orchestration to produce the primary automation run.
Why this matters
This is the core step where agent orchestration actually happens, so it determines baseline quality for everything after it.
What you get
A first-pass automation run is generated and ready for refinement in the next steps.
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5Refine · Step 5 of 7
Open task pageHuman-in-the-loop workflow management
Refine and validate agent orchestration output using Human-in-the-loop workflow management before final delivery.
Why this matters
Human-in-the-loop workflow management adds quality control so issues are caught before the workflow is finalized.
What you get
The automation run is improved, validated, and prepared for final delivery.
6Refine · Step 6 of 7
Open task pageAutomated data analysis and visualization
Refine and validate agent orchestration output using Automated data analysis and visualization before final delivery.
Why this matters
Automated data analysis and visualization adds quality control so issues are caught before the workflow is finalized.
What you get
The automation run is improved, validated, and prepared for final delivery.
7Deliver · Step 7 of 7
Open task pageOrchestrate AI agents
Package and ship the output through Orchestrate AI agents so agent orchestration reaches end users.
Why this matters
Orchestrate AI agents is what turns intermediate output into a usable, publishable result for real users.
What you get
A finalized automation run is ready for publishing, handoff, or integration.
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