Designing the systems that make content work at scale.
I'm Megan, a senior content strategist with 15 years of experience turning fragmented information ecosystems into systems that scale: across help centers, AI products, and the infrastructure that connects them.
Most recently at Meta, I work where editorial meets engineering: structuring content for RAG retrieval, building internal tooling, and measuring whether the words we publish actually change user behavior. The throughline across my career has been the same: find the structural problem underneath the content problem, then fix both.
Recent Work
My work sits at the intersection of content strategy, information architecture, and AI systems. I take on projects where the documentation is broken, the data layer is a mess, or the AI is hallucinating — and I leave them with a structure that holds.
Content Gap Analysis Tooling & Automation
A prototype dashboard that unifies live ticket queues, AI search misses, bug flags, and sentiment feeds into one automated, prioritized view of documentation gaps across five Help Centers.
View case study →AI Skill Library
A searchable, filterable catalog of proven AI prompts — replacing scattered Slack threads and notes with one shared, rated reference the whole content strategy team could reuse.
View case study →Meta AI Business Assistant on IG Boost
Authored the structured, machine-readable knowledge layer Meta’s AI Business Assistant needed to stop hallucinating — plus the query datasets and failure-mode catalog used to validate automated LLM judges.
View case study →Creator Monetization Payouts Overhaul
Replaced a fragmented, three-platform payouts documentation maze with one synchronized source of truth — auditing 57 articles, cutting 22 duplicates, and stabilizing 20 support hubs.
View case study →Ads Manager Permissions & Onboarding
Restructured a high-drop-off permissions flow by fixing its information architecture, not its copy — moving prerequisites to the top and validating the new layout through A/B testing.
View case study →