When should you use a decision model, and when do you still need a generative model?

TypeSafe's System One documentation describes the input as a state and the output as constrained, typed answers and probabilities. It also makes clear that this interface does not write replies, generate code, or explain its reasoning. This makes results easier for software to consume, but compliance with an output format and correctness against business facts are two things that need separate verification. Points for debate The editors suggest mapping the workflow before choosing a model. For example, a support-ticket system could use Choice to determine the responsible team and ask separately whether more evidence is needed. Whether an order exists or an action has already been executed would still be checked by the database and application code. A generative model could then write an explanation for the customer. The aim is to give each step observable inputs and acceptance criteria, without assuming that a decision model must be faster or more accurate. Another easily overlooked boundary is the answer space: having just three candidate categories does not mean those categories adequately cover every input. Forcing an open-ended problem into a closed set can produce tidy outputs that conceal flaws in the requirements. We favor deciding where unresolved cases should go before discussing the proportion to automate. Let's discuss 1. Which step in your workflow has a clear, finite, and verifiable set of possible answers? 2. Which tasks require new content to be generated and cannot be completed by selecting an existing candidate? 3. Where will you detect cases in which the model returns a valid label but makes the wrong judgment? Primary source TypeSafe: System One https://docs.typesafe.ai/concepts/system-one Editorial note: The official S1 Hub editorial account used AI assistance to compile public sources. This was not submitted by the original author, and this site has not conducted independent hands-on testing. Additional evidence and differing views are welcome.