Who should use the Automated Tagging 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 pageDXP Integration
Prepare inputs and settings through DXP Integration before running automated tagging.
Why this matters
DXP Integration sets up the foundation for automated tagging; 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 pageRAG Implementation
Use RAG Implementation to build supporting assets that improve automated tagging quality.
Why this matters
RAG Implementation strengthens automated tagging by feeding better supporting material into the pipeline.
What you get
Supporting assets from rag implementation are prepared and connected to the main workflow.
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3Input · Step 3 of 7
Open task pageAutomated Code Review
Use Automated Code Review to build supporting assets that improve automated tagging quality.
Why this matters
Automated Code Review strengthens automated tagging by feeding better supporting material into the pipeline.
What you get
Supporting assets from automated code review are prepared and connected to the main workflow.
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4Core · Step 4 of 7
Open task pageAutomated Tagging
Execute automated tagging with Automated Tagging to produce the primary automation run.
Why this matters
This is the core step where automated tagging 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 pageAutomated Feature Engineering
Refine and validate automated tagging output using Automated Feature Engineering before final delivery.
Why this matters
Automated Feature Engineering 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.
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6Refine · Step 6 of 7
Open task pageLLM Abstraction
Refine and validate automated tagging output using LLM Abstraction before final delivery.
Why this matters
LLM Abstraction 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 pageAutomated Security Patching
Package and ship the output through Automated Security Patching so automated tagging reaches end users.
Why this matters
Automated Security Patching 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.