Act 3, scene 13: AI agents write the language

Scene 13: AI agents write the language

AI agents write the business rules. Earlier domain languages stalled partly because the experts had to learn them and write in them. A domain expert states the intent in plain language, and an agent writes it as business rules in the domain's own vocabulary. The model's general knowledge does the translation, so the grammar can stay small: a language with a room primitive needs no bedroom keyword. It also shortens the leap. Going from plain language straight to a narrow configuration schema is a long step, and the model makes it invisibly. The grammar splits it into two shorter steps, with a readable document in between. The agent works with the grammar, worked examples, a validator and a test runner, reached through standard tooling such as the Language Server Protocol and MCP, so it checks its own work. The validator rejects anything malformed, with a location and a reason, and the agent tries again. Functional tests run against cases with known answers, and the compiler turns the result into configuration, screens or API calls, shown back to the expert. A request the language cannot express is refused rather than guessed at. The agent can still be wrong inside the language, which is why the tests carry the weight. An agent working in the language cannot add an API, a table or a code path, so the shared layers stay out of its reach. Agents may later help derive the grammar itself from the knowledge graph; for now, deciding what goes into it is architectural judgement.