Registration page for a new pet When using Large Language Models to convert specifications into code, the boundaries of your input heavily shape the boundaries of the model's output. If you feed an LLM an API specification, its baseline assumption is that you want an API. This short case study explores what happened when converting a standard OpenAPI 3.0 specification into a runnable Flask project using Claude.ai—and how adding a single sentence to the prompt dramatically altered the architectural and visual output. The Experiment & The Starting Prompt The goal was simple: take the standard OpenAPI 3.0 Petstore example specification and prompt Claude.ai to turn it into a complete, runnable Flask application pre-packaged for Visual Studio Code. Here was the initial prompt structure: Plaintext In the next prompt I am going to enter an OpenAPI specification. Your role is to convert this into a Flask-based program and then save the files as a zipped-up file ready for importing i...
Experiments with various forms of LLMs to improve productivity