Notes from the Augmeta team on causal intelligence, the craft of root-cause work, and what we’re building underneath it all.
A short note on why we're starting a publication, what we'll write here, and the one belief everything Augmeta builds quietly rests on: most companies are drowning in metrics and starving for understanding.
A war room gets eight smart people in a room and usually produces eight theories. Here are the alternatives enterprise ecommerce teams use, and where each one breaks.
The leaks that cost a large retailer the most are the ones no dashboard flags, because the rate is stable and the cause sits between three teams. Here is where to look, and how to put a dollar figure on what you find.
The question enterprise buyers ask about an AI analyst is not what it can do. It is how would we know when it is wrong. This is the test that answers it.
Most sudden conversion drops at enterprise retailers are not what the first theory in the room says. Here is the order we check causes in, with real examples of each.
Dashboards show that a number moved. Agentic KPI Ops is the practice of giving each KPI an owner that finds out why, sizes what it is worth, and follows it through to the fix.
Kai offered a root-cause triage based on the shape of its own plan, not on what the user asked. We tested four ways to read the question instead, on 626 production turns. A small typed-decision model tied Claude Haiku 4.5 at a third of the latency.
