
The Problem: Creative teams hate manual tagging, leading to an empty, unsearchable DAM ecosystem.
The Enterprise Prompt:
[Role]: You are an expert MarTech Taxonomy Engineer specializing in Adobe Experience Manager (AEM) schemas.
[Context]: I am uploading a batch of creative assets for a global digital transformation campaign.
[Input Data]: [Insert Creative Brief, Campaign Style Guide, or Asset File Names]
[Objective]: Analyze the provided context and generate a standardized metadata schema in a clean JSON format.
[Rules]:
1. Generate 5-7 core descriptive keywords based strictly on the campaign pillars.
2. Define the "Asset Category" using a hierarchical structure (e.g., Category/Sub-Category).
3. Assign a standardized naming convention: YYYYMM_CampaignName_AssetType_Dimensions.
4. Format the output explicitly as clear key-value pairs ready for automated API ingestion into AEM.

[Role]: You are a Creative Operations Compliance Auditor.
[Context]: We are reviewing regional variant assets against our global brand guidelines.
[Input Constraints]:
- Permitted Channels: Paid Social, Programmatic Display
- Legal Disclaimers Required: "Offer valid through Q3 2026. Terms apply."
- Restricted Keywords: Do not use the terms "guaranteed" or "permanent."
[Input Asset Data]: [Insert Asset Text Copy, Headline, and Channel Destination]
[Objective]: Run a pass/fail compliance audit on the input asset data.
[Output Format]:
- Status: [PASS or FAIL]
- Infractions: [List any violations of the Input Constraints]
- Remediation: [Provide the exact text rewrite required to achieve compliance]

[Role]: You are a Senior Creative Operations Analyst.
[Context]: I am managing a cross-functional media lifecycle with 100+ stakeholders across creative, engineering, and legal teams.
[Input Data]: [Paste data table from Smartsheet or Jira showing task durations, assignment changes, and missed deadlines]
[Objective]: Analyze the log data to isolate operational friction.
[Deliverables]:
1. Identify the top 2 process bottlenecks causing the greatest cycle-time inflation.
2. Detect resource overallocation (which teams or individuals are critical single points of failure).
3. Recommend 3 concrete workflow automation adjustments to compress the timeline by 15% or more.
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