AI & LLMs.

Explore an AI project as a collection of connected parts. Data, labels, model configuration, evaluation examples, and the decisions behind a release all deserve attention. These guides help you record those relationships and compare language models against the actual work you want them to perform.

Start with the AI asset inventory if you need a map of the workflow. Choose the LLM selection checklist if you already have a task and are comparing deployment options. Both guides emphasize clear evidence, documented limitations, and manageable operating requirements. The evaluation tag continues into prompt testing, where small instruction changes can be examined with the same care as a larger model choice.