Why does AI model selection matter in commercialization systems?
Different model choices affect cost, speed, quality, reliability, workflow and scalability.
A project view across the questions, things built and field notes that belong to the same work.
Different model choices affect cost, speed, quality, reliability, workflow and scalability.
This is one of the problems I am currently working on through MAS.ai.
MAS.Ai is a commercial intelligence project for law firms built around a simple question: can observable changes in the market help a law firm understand possib
I noticed something uncomfortable while working with AI on a long product build.
I have been building parts of a commercial intelligence system together with another team and another AI. What has surprised me is that the value does not prima
We wanted to verify that cross-tenant learning could not accidentally become approved global learning. The running system turned out to have no functioning appl
We thought the next step in the learning architecture was to prove tenant isolation. Looking at the running system showed something more basic: there was no ope
A declined meeting could mean wrong timing, wrong relationship, incumbent supplier, poor outreach, low priority or no need.
AI usage increased without a proportional increase in useful progress. We changed the workflow from many small review loops toward larger coherent work packages
A single opportunity can produce several outcome records. If every event becomes a calibration observation, one real situation can create artificial evidence.
More events did not necessarily make an account more interesting. Several independent observations pointing toward the same underlying change appeared more usef