“The fact that it sometimes tells us useful information is merely a coincidence. To teach it to speak, we supply it with a vast amount of human writing, because what better way to learn to speak than from seeing billions of examples of real people doing exactly that. As it happens, the text that we fed it also contained some useful information. LLMs don’t “know” anything. They are just very good at pattern recognition and reproduction. It just so happens that the phrase “The Great Fire of London” is often followed by the number 1666. What do we mean when we talk about pattern recognition? In the context of languages, pattern recognition can take on many forms: Understanding how vocabulary and sentence structure patterns make up different writing styles, voices, and personas Understanding how language can be used to convey sentiment and identifying semantically and thematically similar language Understanding how language is mapped between different domains These are the real strengths of modern AI chatbot tools, so how can we use these ideas to help us write better prompts? Let’s start with a couple of tips you may already be familiar with to make sure we’re all on the same page. Roleplay. LLMs are general-purpose by design. So anything we can do to help narrow down their response options will only serve to provide us with better responses. After all, context is everything. Asking your AI chatbot to adopt a role or persona helps it to understand the goal of the interaction, narrowing down the scope of what’s relevant. Without roleplay, it often tries to cover too much information or to take the response in different, potentially irrelevant directions. “You’re a financial advisor speaking to a beginner investor. Explain what a stock option is and when someone might use one.””