Why AI Prompts Should Be Specifications, Not Vague Assignments

Software engineer Anton argues that a prompt handed to an AI executor must function as a self-contained specification, not an open-ended assignment that leaves facts to be discovered later. The core distinction is that an assignment describes desired output while leaving the executor to gather missing details, whereas a specification embeds every required fact upfront. Under a single-message execution model, any unanswered question inside the prompt means the prompt is simply not ready to be sent. Anton recommends a dedicated facts section covering exact file paths, full type signatures, existing shared primitives, literal value names, and a single ready-to-run acceptance command. This approach shifts the cost of fact-finding entirely to the author before writing, eliminating repeated lookups and ambiguous references during execution.