Exactly. A demo only has to work once. A system has to clear inference costs on every single run, at scale, for months. We feel that math directly. We run these agents in our own ventures first. So the cost ceiling hits our P&L before it hits a client’s. That order of operations is what keeps the thing alive past the demo.
the fastest no's in pitch meetings are products that get commoditized the second the next model ships. worth naming that the defensibility bar moved up a lot in the last 6 months.
Spot on. The bar climbed because the base models swallowed most of what used to pass for a feature. What holds now is the layer you own around the model: proprietary data, workflow depth, distribution. We build that layer in our own ventures before we offer it to clients. This is why a new model release tends to make those systems stronger, not obsolete.
Love this — most AI startups skip the economics test and ship a demo that dies on inference costs. Validate the unit economics before the model.
Exactly. A demo only has to work once. A system has to clear inference costs on every single run, at scale, for months. We feel that math directly. We run these agents in our own ventures first. So the cost ceiling hits our P&L before it hits a client’s. That order of operations is what keeps the thing alive past the demo.
the fastest no's in pitch meetings are products that get commoditized the second the next model ships. worth naming that the defensibility bar moved up a lot in the last 6 months.
Spot on. The bar climbed because the base models swallowed most of what used to pass for a feature. What holds now is the layer you own around the model: proprietary data, workflow depth, distribution. We build that layer in our own ventures before we offer it to clients. This is why a new model release tends to make those systems stronger, not obsolete.