With FileMaker 26, how do you set up your database so an AI model can understand it? Two features make this easier: GetTableDDL, which describes your schema in a language AI already speaks, and field annotations, which explain what each field actually means. This reframes how to invest in aging but essential FileMaker solutions. The system you already depend on does not need to be rebuilt to work with AI. It needs to be made legible.
A Fork In The Road
Many teams adopting AI move quickly and pay for it later, connecting assistants to data that the model does not truly understand. Inspecting the schema may produce answers that sound confident and are quietly wrong. A schema an AI can understand produces answers you can act on more confidently. What follows is how GetTableDDL and field annotations work together, including the behavior that will surprise you the first time you hit it (the “Fork in the Road” below), and the FileMaker naming quirks that quietly waste tokens if you are not paying attention.
