GenAI: A New Paradigm for Problem-Solving with Undefined Inputs

Generative AI represents a transformative programming paradigm where inputs do not need explicit definitions, contrasting with traditional methods that require defined input-output contracts. By allowing a system to generate responses based on expected output descriptions rather than rigid input formats, GenAI enables solutions for complex problems, such as extracting information from unstructured text or generating SQL queries from natural language. This approach leverages large language models to handle diverse input variations and produce standardized outputs, such as JSON objects, without predefined parsing logic. While GenAI excels in scenarios involving unstructured data and flexible transformation logic, such as emails or free-form text, traditional programming remains superior for deterministic workflows, performance-sensitive applications, and situations requiring strict business rules. Ultimately, GenAI complements existing methods, offering developers a hybrid approach to tackle previously challenging problems by defining desired outcomes and allowing AI to manage input variability.