Women in Claude
The problem
Ziying works in a world where regulatory changes happen across multiple jurisdictions and categories at the same time. Tax, immigration, visas, and travel security updates can all shift quickly.
Manually tracking newsletters, alerts, and bulletins meant spending hours each week scanning sources, with a very real risk of missing what mattered most.
"Experience told me what mattered. AI made sure I never missed it."
What Ziying built
Ziying used Claude Cowork to build an AI agent that searches reliable public sources worldwide every day across regulatory areas she defined from her own professional experience.
The updates are structured around a practical operating frame: what changed, what it means, and what to do. The briefing is then prioritised using an urgency framework Ziying designed: act now, monitor, or awareness only. Every morning at 9am, the colour-coded briefing is delivered to her personal Gmail inbox.
Before and after
Before: hours each week scanning newsletters, alerts, and bulletins across multiple sources with no consistent prioritisation system.
After: a structured, colour-coded daily briefing organised by urgency and ready to act on, reclaiming 2 to 3 hours of manual research every week.
Why it matters
Ziying’s build is a strong example of expert-led AI. The framework is hers. The prioritisation logic is hers. Claude Cowork handles the repeated scanning and formatting so her professional judgment can stay focused on action.
For Claudettes in research-heavy, regulation-heavy, or information-heavy roles, this is a pattern worth studying: let AI gather and structure the signal, while you decide what matters.
Watch Ziying's walkthrough
Spotlight on Ziying He. Build originally published by AI Native Circle.