Help Center Content & Strategy
Help Center articles had fallen behind product updates. Users were hitting dead ends on core flows because the right information existed somewhere, just not where they could find it, and often not structured for the task they were actually trying to complete.
Maintained and rebuilt articles across support.ledger.com. Designed Help Center homepages and section architecture to surface the right content faster. Tracked work in Jira across CS, product, and content teams to stay aligned on product changes before they shipped.
The underlying principle: a Help Center is a product surface, not a filing cabinet.
View Help Center ↗Used Google Analytics and platform-level reporting to find the articles users bounced from, the searches that returned nothing, and the flows where tickets spiked. Data shaped every prioritization decision.
Wireframed content layouts before writing. Evaluated and integrated AI tooling into the workflow. Worked cross-functionally with CS, product, and content to make sure accuracy and usability moved together, and that the backlog was always prioritized by user impact.
Knowledge Base Migration
Before anything could move, everything had to be counted. A full content audit surfaced hundreds of articles, each assigned to a stakeholder and put through triage: migrate, rewrite, or retire. Technical constraints hit mid-project and required cross-team coordination before migration could proceed.
Sequenced with support ops to avoid disrupting live workflows. Integrations were set up to trigger reviews and prevent content from going stale.
View migration deck ↗What the project made clear: documentation is infrastructure. It has dependencies, failure points, and technical debt, the same as any product system. Solving those things requires the same coordination you'd apply to any product problem.
Ongoing sysadmin ownership of the internal Ledger CS knowledge base followed the migration: maintaining structure, governing access, and enforcing the review process that keeps content from drifting. The migration built the system; the sysadmin work keeps it running.
AI Support Bot & Content Deflection Strategy
Business goal: reduce inbound support volume. Content goal: figure out why the bot wasn't performing and fix it. Writing for an AI system is structurally different, the question isn't whether the information is accurate, it's whether the right answer surfaces when someone types a question in natural language.
Restructured dozens of articles so answers appeared earlier and headings matched how users actually typed. Highest-volume articles prioritized first for maximum impact.
Ledger CS Chatbot for Customer Support, screenshot on the rightResult: measurable reduction in inbound support volume. Content quality is a product variable. When structured well, it shows up directly in business metrics.
Scam & Phishing Content Revamp
Crypto scams evolve faster than most orgs can document them. Inherited content was already partly out of date, a real risk given that users rely on these articles to protect their funds. The audience: non-technical, anxious, and does not read linearly.
Built a consistent structure across all scam articles: Scam Tactics, How to Detect, What to Do. Security Best Practices added to front-load critical info. Every decision balanced two things: reducing confusion and lowering anxiety. Both, at once.
Read the live article ↗
Content, Product & Knowledge Systems
Simple was one of the first all-app, no-branch banks in the US. Content strategy, help center documentation, product writing, and persona development built from real user interviews and behavioral data. Not assumptions.
Budgeting features built with product, ops, and support through sprint planning and agile workflows. This is where it became clear that content is part of the product, not separate from it.
Simple FinanceThat thinking is the foundation of the move toward PM. Simple had a product culture where content decisions had to be justified in terms of user outcomes, not just accuracy or style. That's the standard everything since has been held to.
Across every artifact in this section, the pattern is the same: content structured as product decisions, outcomes measured, and thinking documented. Not just deliverables.
This is the foundation of the move toward product management.