Conversations vs Prompt Engineering

Long and complex prompts are not always great for getting the best response from chatGPT, Bing or Bard, or Claude.

Focusing on a series of prompts like a conversation can help you get much better and more accurate results from ChatGPT and other LLMs. This is because a series of prompts allows you to provide the LLM with more context and context, which can help it to better understand what you are asking for and generate more relevant and accurate responses.

Here are some tips for using a series of prompts like a conversation with ChatGPT:

• Start with a broad prompt that introduces the topic of the conversation. Try to ask chatgpt what it already knows or thinks about the broad topic and why its important etc.
• Follow up with more specific prompts that ask the LLM to elaborate on different aspects of the topic.
• Use open-ended questions to encourage the LLM to generate creative and informative responses.
• Use feedback to guide the conversation in the desired direction.
• Be patient and understanding. LLMs are still under development and may not always generate perfect responses.

The question-answer structure: This is a simple and common structure that involves asking and answering questions. You can use this structure to elicit information, opinions, or feedback from the LLM or the user. For example, you can ask “What is your favorite book?” or “How do you feel about this topic?” You can also use follow-up questions to provide more details or clarification. For example, you can ask “Why do you like it?” or “Can you explain more?”

• The problem-solution structure: This is a useful and effective structure that involves identifying and solving problems. You can use this structure to help the LLM or the user with a specific task or challenge. For example, you can ask “What is the problem?” or “What are you trying to do?” You can also use suggestions or recommendations to provide solutions or alternatives. For example, you can say “You can try this method” or “You can use this tool”
• The narrative structure: This is a creative and engaging structure that involves telling or creating stories. You can use this structure to entertain, educate, or inspire the LLM or the user. For example, you can ask “Can you tell me a story about this topic?” or “Can you write a poem about this theme?” You can also use feedback or reactions to provide appreciation or criticism. For example, you can say “That’s a great story” or “That’s not very realistic”
• Use natural and engaging language: AI chatbots can learn from your input and feedback, and try to match or respond to your tone, emotion, and humor. Therefore, you should use natural and fluent language, and try to make the conversation engaging and interesting for both you and the chatbot. For example, instead of saying “Hello”, you could say “Hi there, how are you today?” or “Greetings,”

When users engage in polite assertive conversations, ChatGPT's ability to absorb and apply feedback becomes particularly valuable. It can quickly grasp user expectations and adjust its responses accordingly, striving for user satisfaction.

Provide clear and specific instructions. Explain to the LLM what you want it to do or say in each step of the conversation. Avoid using ambiguous or vague language.

To structure a better conversation or series of prompts to get better responses from an LLM, you should:

1. Start with a clear goal in mind. What do you want to achieve with the conversation? Do you want to generate creative text formats, translate languages, write different kinds of creative content, or answer your questions in an informative way? Once you know your goal, you can tailor your prompts accordingly.
2. Use natural and engaging language. Avoid using stilted or formal language. Instead, use language that is similar to how you would talk to a friend or colleague. This will help the LLM to generate more natural and engaging responses.
3. Provide clear and specific instructions. Explain to the LLM what you want it to do or say in each step of the conversation. Avoid using ambiguous or vague language.
4. Ask open-ended questions. Open-ended questions allow the LLM to generate more creative and informative responses than closed-ended questions. For example, instead of asking “Do you like this poem?”, ask “What do you think of this poem?” or “How do you feel about this poem?”
5. Handle errors and exceptions gracefully. If the LLM makes a mistake or misunderstands your instructions, don’t get frustrated. Simply provide clear and concise feedback, and try again.

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Here are some additional tips for writing effective prompts:

• Use priming examples. Priming examples can help the LLM to understand the context of your prompt and generate a more relevant response.