AI risks are significant, and as of yet there’s no widespread, binding regulation in the UK, US or Australia yet — that’s a problem. But governments are trying to balance regulation with innovation — they don’t want regs to stifle innovation and progress.

To mitigate risk of using AI tools at work, know your policy for AI, know what tools are already available to you, be wary of free trials, and don’t put personally identifiable info (PII) in these tools unless you have express permission to.

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conversations, they have a limited context window (like short-term memory), and their training data will always be out of date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).