Designing the systems that make content work at scale.
I’m Megan, a senior content strategist with 15 years of experience building scalable knowledge systems at the intersection of language and technical infrastructure.
Most recently at Meta, I work where editorial meets engineering: structured content, taxonomy, and AI-powered workflows that turn content operations into a measurable system, and complex information into seamless user experiences.
Recent Work
Throughout my career, I’ve found my sweet spot at the center of operational chaos. Where others see fragmented documentation and scattered feedback loops, I see a blank canvas. By combining content modeling, RAG optimization, and custom prototyping, I turn structural messes into measurable, seamless systems.
Meta AI Business Assistant on IG Boost
To support the launch of Meta’s AI Business Assistant, I authored structural documentation for the Instagram Boost integration and served as the subject matter expert for model evaluations. I built query datasets to scale intent routing and cataloged edge-case errors to refine conversational failure modes, providing the ground-truth labels needed to validate automated LLM judges.
Creator Monetization Payouts Overhaul
Distributed payouts content was a repetitive maze, straining operations and generating 279,000+ support tickets. I audited 57 articles, eliminated 22 duplicate blocks, and deployed a centralized hub using ref-ID logic. This structural overhaul automated cross-surface accuracy and stabilized the documentation layer relied on by 20 support hubs.
Content Gap Analysis Tooling & Automation
Identifying documentation gaps across five help centers historically required manual data hunting. To automate this, I vibe-coded a dashboard prototype that unifies live ticket queues, AI search misses, bug flags, and sentiment feeds. The tool runs on a custom recommendations engine to isolate high-impact content gaps and project metrics before editing begins.