Show HN: PromptLayer – Track, debug, and maintain GPT prompts in prod

LLMs are a funky thing to work with, and we need a whole suite of new tools to make them prod-ready.

> Prompt engineering is a concept in artificial intelligence, particularly natural language processing (NLP). In prompt engineering, the description of the task is embedded in the input, e.g., as a question instead of it being implicitly given. Prompt engineering typically works by converting one or more tasks to a prompt-based dataset and training a language model with what has been called "prompt-based learning" or just "prompt learning".[1][2] Prompt engineering may work from a large "frozen" pretrained language model and where only the representation of the prompt is learned, with what has been called "prefix-tuning" or "prompt tuning".[3][4]

From https://en.wikipedia.org/wiki/Prompt_engineering

A prompt engineer is a person who designs and creates user interface prompts, such as chatbot prompts or command line prompts, to communicate and interact with users effectively. They are responsible for defining the language, tone, and structure of the prompts in order to guide users and elicit the desired response.