TypeSafe AI says reliable decisions need code, not decision models

TypeSafe AI (@typesafeai) says a model cannot make reliable decisions on messy data alone, so reliability requires code.

In an X post on November 5, 2026, the company says reliable decisions come from composing reliable judgments in code, and that its product Jev makes those judgments. It says calling Jev a decision model places it at the wrong layer of abstraction and hurts reliability.

In a second post the same day, TypeSafe argues that data distributions are always less predictable than semantic logic, string caveats, embedding vectors, or complex machine learning. It recommends stating what you need to know and checking whether a plain reading of your data is enough to decide reliably.