LLMs are machine learning models trained on a huge amount of data that understand and can generate text in a human-like way. An LLM is the engine behind a chatbot — so GPT-4o is the LLM behind ChatGPT.

LLMs use complex math to predict the next word to write. Think of them like a calculator for words.

Key limitations are that they’re not great at getting our writing style just right, they (typically) don’t carry memory between conversations, they have a limited context window (like short-term memory), and their training data will always be out of date

Prompts are the instructions you give a chatbot, and there’s an art to doing them well to optimize outputs.

Carve’s prompt crafting framework is COIF: include Context, Output, Intent, Format in every prompt for best results.

10 “buckets” of tasks you can use a chatbot for in your workflow: writing and editing, research, meetings, minutes & events, project planning, travel, expenses, brainstorming as a thought partner, learning and business intelligence, translation and cultural nuances, data cleaning & analysis (see below for detailed appendix).