Private AI content workflow
Content Writing Agent
An in-development AI-assisted writing workflow intended to help stakeholders draft clearer enrollment and brand-aligned content while preserving human review and policy constraints.
Role
AI Workflow Builder / Technical Lead
University of Arizona
Tags
Applied AI WorkflowContent GovernanceHuman Review
Problem
Content writers needed help producing branded, audience-specific copy because generic AI output sounded too obviously AI-generated and did not reliably follow university or department guidance.
Users
Content writers, content team leadership, and division teams that need enrollment- and brand-aligned copy.
Ownership
- Owned project inception, product design, AI workflow design, implementation, coordination, prototype, and production version.
- Worked from the content team manager's pain point into an internal workflow that could support broader division use.
- Designed the interface and workflow around how writers actually create and improve copy.
Hard Parts
- Designing a UI that made sense for channel-specific briefs, voice, style, audience, and writing goals.
- Supporting saved examples of strong outputs so the system could improve with more frequent use.
- Adding research mode over approved university-specific sources while cross-referencing university and department writing guidelines.
Leadership
- Turned a stakeholder complaint about AI writing quality into a product workflow.
- Coordinated from concept through design and implementation.
- Kept human review and policy constraints central instead of treating the tool as unsupervised generation.
Shipped
- Prototype and production workflow.
- Channel-specific briefs for voice, style, and audience.
- Saved examples of good outputs for future improvement.
- Research mode using approved university-specific sources.
- Guideline cross-reference against university and department writing standards.
Impact
- Improved content quality and made the drafting workflow easier for writers.
- Reduced complaints about AI-sounding copy.
- Created a safer AI writing process tied to brand and audience context.
Highlights
- Framed the work around stakeholder content quality, enrollment messaging, brand alignment, and safer AI-assisted drafting.
- Focused on human review and policy constraints rather than unsupervised publishing.
- Connected the workflow to broader content editing, guidance, and review needs for non-technical teams.
- Treated AI drafting as a stakeholder enablement problem, not just a generation feature.
Tools
LLM workflowsPrompt/workflow designStructured outputsHuman reviewBrand guidanceEnrollment content workflowsStakeholder enablement