We often assume that working with machines should be a simple, binary affair: ask for something and get exactly what you asked for. No questions, no misunderstandings. But generative AI rewrites that logic. The reality is closer to working with a human: the more empathy and patience we bring, the better the outcomes. It’s not just about getting an answer — it’s about how we shape that answer together.
When you find yourself rephrasing a prompt because the AI “didn’t get it,” you’re discovering something important: talking to machines isn’t a blunt command — it’s a conversation. And in that space between question and response lie some very human truths about how we communicate, collaborate, and create.
Prompting Mimics Human Dialogue
Success with AI rarely comes from barking orders. Instead, it demands the same traits we rely on in everyday dialogue — empathy, patience, and nuance in how we express ourselves.
Think of speaking to a colleague. A rushed, cryptic email might confuse them, while a clear, full-sentence message — tone, context, even a sprinkle of courtesy — makes all the difference. AI doesn’t technically require perfect grammar, spelling, or politeness. But users often achieve far better results when they engage with it as if it’s part of a conversation, not just a tool.
Misunderstandings are part of the loop
Ask ChatGPT to “write an essay on leadership” and it will certainly produce an essay. It’ll be good in an objective sense — but often bad in a subjective, human one.
Real magic happens when we treat prompting like coaching a team member. A good manager doesn’t simply assign tasks. They explain, check understanding, and adjust along the way. Likewise, iterating with AI — asking clarifying questions, providing context, refining outputs — yields richer, more tailored results.
Misunderstandings aren’t glitches. They’re signals inviting us to shape the conversation. And with every exchange, we teach the model a little more about what matters to us.
A New Etiquette is Emerging
We’re inventing a new etiquette as we go. How we phrase prompts, how much context we share, even how gently we “correct” the AI when it goes astray — it’s all part of an emerging relational skillset.
Think of techniques from leadership communication, like the “management sandwich”: praise, critique, praise again. Similar patterns work surprisingly well in prompts — framing a correction between positive statements often leads to more constructive results.
These subtle choices shape not just the machine’s responses but our own relationship with technology. Are we commanding a tool? Or are we collaborating with a partner — albeit a silicon one?
Conclusión: Conversation, Not Command
Prompting isn’t a mechanical transaction. It’s communication. The future of AI hinges on those willing to engage with it as dialogue, not dictation.
Approach AI with empathy and patience — as you would a colleague, a friend, or a team — and the results won’t just be accurate. They’ll feel more human, and perhaps a little bit magical.