# Smart Software > Source: > Published: 2026-09-22 03:16:23+00:00 ### From prompted intelligence to engineered intelligence Jev from [@TypeSafeAI](https://x.com/@typesafeai) finally makes the shift easier to see: intelligence is becoming part of how software works. Not as a chatbot or bolted on as some sidecar. But intelligence precision engineered into software systems from the foundation up. Much of generative AI has worked through what I call **prompted intelligence**: we give a model instructions in plain language and get text back. Then we—or our software—have to interpret that text and decide what happens next. Or what I like to call "toss spaghetti against the wall intelligence", even tho its been enormously useful. Everyone has had a lot to debate about AI, but the mere existence of LLMs requires a new philosophy of software engineering. That philosophy enables a new evolution of the craft itself, which enables the next phase of AI: **engineered intelligence**. A program can encounter some state, ask a bounded question about what that state means, receive a structured judgment, and use that judgment as part of its execution. These are semantic questions: questions about meaning. This is **semantic engineering**. This means **interpretation of meaning can become part of the machinery of software.** TypeSafe founder [Diogo Almeida](https://x.com/@CompleteSkeptic) has called this **smart software**. Its perfect. ### **Smart software is software that uses intelligence as part of how it operates.** That is different from software that was written with AI. It is different from an application with a chatbot attached to it. And it is different from using a model as an assistant that waits for a person to ask a question. The distinction is where intelligence sits in the architecture. In the familiar prompt-and-response model, a human gathers context, asks for a judgment, interprets the response, decides whether to trust it, and determines what happens next. Smart software begins when some of that interpretation moves inside the system itself. The application encounters a situation, requests a bounded judgment, evaluates the result within its rules, takes an authorized action, observes what happened, and continues. That produces a different loop: **State → judgment → bounded decision → authorized action → observation → new state** Once intelligence enters that loop, the engineering problem changes. It is no longer enough to ask whether a prompt produces a good answer. We have to ask what context the judgment receives. What outcomes it is allowed to produce. How uncertainty is represented. When the system may act. When a person must review the decision. What evidence is retained. What happens when the judgment is wrong. That is the transition from **prompted intelligence** to **engineered intelligence**. Prompted intelligence asks a model to help us think. Engineered intelligence makes bounded judgment a designed component of a software system. And smart software is what becomes possible when we do that well.