i work in trust & safety / security product management, and earlier in my career i was at a yc startup (s16). i saw firsthand how scrappy teams have to be with limited resources and once you're sucked in its a time suck for the brightest minds who are focused on other parts of the business. and since most startups don’t have dedicated security or trust & safety orgs (yet) and still deal with the same issues, especially in marketplaces where arbitrage is part of the product. and fwiw, product abuse is a signal—if users are exploiting your system, it usually means you’ve built something valuable enough to be worth exploiting. so i tried to piece something together that teams can have otb for threat intel, detections, playbooks, dashboards, but they’re disconnected, and now we’re trying to layer ai on top of that. i put together a “defensive knowledge base” that connects threat → signal → control → response → outcome and makes that context navigable for both humans and ai. to put it into practice i modeled two example startup environments inspired by collectibles marketplace: one focused on marketplace integrity (pricing, seller trust) and one on transaction risk (account takeover, payouts). each includes intel cards, controls, runbooks, and a connected index. not trying to replace existing tools or other open source solutions (for sure buy them if you an afford them), more of a lightweight context layer to add to library.