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  Examples of Good & Bad  Prompts and Outputs 📜Introduction In Human Computer Interaction,  Clear prompting is the link between what we intend and what AI predicts . In my last article ( How AI Understands You: Inside Human & AI Communication ), I called it the bridge between human language and AI's probability engine . This follow-up post shows how small changes in our prompts can dramatically improve accuracy . The goal isn't to write perfect prompts . It's simply to give AI enough context, clarity and direction so that the prediction pathway becomes more precise.   ❌Example 1: Bad or Inadequate Prompt + Inadequate Output Bad Prompt:  Explain coffee. Likely Output (example): Coffee is a popular beverage made from roasted beans. People drink it in many countries, and it can be prepared in various ways. Why it’s inadequate: It’s vague. It doesn’t specify audience, purpose, angle, or depth. AI must guess what you want, so it defaults to a generic, ...

  Human interaction with Generative AI tools using natural language conversation 📌Interacting with AI  - more than a Chat tool When we think of “talking to AI,” we often imagine a simple chat window.  But AI language models - the engine behind those chat windows - process far more than conversational text.  AI language models are trained systems that learn patterns from large amounts of text so they can interpret input and generate meaningful responses.   Anytime we type a prompt in a Gemini chat window, paste a paragraph, upload a document, or send files for analysis, we’re communicating with the underlying language models. Even technical inputs, such as sending data through Azure OpenAI, building code with ChatGPT, or executing instructions through an API, rely on the underlying language models. 📌 From HCI to Human-AI Conversation  Traditional Human–Computer Interaction (HCI) focused on how people used interfaces - clicking, typing, or tapping to...