We’ve all had that moment. You ask an AI for something seemingly simple, and what comes back is… not quite right. You wanted a concise summary, but you got a novel. You asked for a story in the style of a noir detective, but it reads like a cheerful travel blog. The instinct is to blame the machine, to think it’s being obtuse. But more often than not, the gap in understanding starts with a gap in our word choice.
Prompting an AI isn’t like talking to a person. It’s a fundamentally different kind of conversation. When we speak to another human, our words are wrapped in layers of shared context, body language, tone, and cultural shorthand. We can say “make it pop” or “give it more of a vibe” and, through a messy process of interpretation, we might get close to what we want. A computer has none of that. It has only the words you give it, taken at their most literal, statistical face value.
This is where the humble, often-ignored dictionary definition becomes your secret weapon. When you prompt an AI, you are not making a suggestion; you are writing a specification. You are a programmer, and your natural language is the code. Just as a coder must know the exact syntax of a function, a good prompter must respect the precise meaning of a word.
Consider the difference between asking for something “concise” versus something “succinct.” To a human, they’re synonyms. But their dictionary hearts beat differently. Concise means expressing much in few words, with a focus on completeness stripped of excess. Succinct implies not just brevity, but a kind of compactness and precision, often in a formal or pithy way. Telling an AI to make a text “concise” might guide it to trim adjectives. Asking for it to be “succinct” might steer it toward sharper, more declarative sentences. The nuance is the outcome.
This precision scales from single words to entire concepts. Do you want a character to be “stubborn,” “obstinate,” or “steadfast”? The dictionary reveals the crucial shades: stubborn is informal and often irrational, obstinate implies a more offensive rigidity, while steadfast leans toward admirable loyalty. The AI will weave a different narrative fabric from each thread. Asking for a “dark” room is vague; is it unlit, poorly lit, painted a dark color, or possessing a grim atmosphere? The word “murky” specifies a thick, cloudy darkness, while “dim” suggests a faint, low light. Each sends the AI’s imagination down a distinct path.The temptation is to use more words, to talk around the idea in hopes the AI will catch our drift. But this often backfires, adding noise and contradictory signals. Mastery lies in using the right word, not just more words. It’s the difference between shouting “make the picture warmer!” and specifying “use a color palette dominated by amber and terracotta tones with soft, golden-hour lighting.” The latter speaks the AI’s language—the language of defined attributes.
This process, ironically, makes us better communicators with people, too. It forces us to interrogate our own thoughts. What, exactly, do I mean by “dynamic” or “professional” or “cozy”? Defining our terms dissolves fuzzy thinking. We move from a hazy feeling of what we want to a clear conceptual blueprint.
So, the next time you sit down to converse with an AI, pause for a moment. Think of yourself as a wordsmith forging a key. The more carefully you craft that key—the more you align your words with their precise, dictionary-honed meanings—the more smoothly it will turn in the lock, opening the door to exactly what you imagined. The machine is waiting to understand. It’s our job to speak with clarity it can compute.
