When we started building Radarix.ai , the visible product was always a map: layers of public-source signals stitched together so a person can see what's happening in air, at sea, and across borders in one glance. The interesting engineering, though, didn't end up living in the map. It lived in the boring layer underneath — the part nobody tweets about: state . This post is a build-log on what we've learned trying to scale a live, multi-source monitoring product without drowning in our own automation. The shape of the problem Most of us already know we should be watching more signal streams than we are: launches in our space, competitor activity, new directory listings, mentions of our project, market shifts, source data we depend on. The reason we don't is operational, not technical: doing it manually doesn't scale, and doing it semi-automatically usually devolves into a graveyard of scripts that nobody dares to touch six months later.…