What is ChatGPT Prompt engineering?
ChatGPT prompt engineering refers to the process of designing and crafting effective prompts to interact with the ChatGPT language model. The prompt is the initial text or question provided to the model to elicit a desired response. Prompt engineering involves formulating prompts in a way that helps guide the model’s behavior and ensures the generation of accurate and relevant responses.
Here are some strategies and considerations for effective and efficient ChatGPT prompt engineering:
- 1. Clear and specific instructions: Provide the model with explicit instructions to guide its response. Clearly specify the desired format, structure, or type of information you expect from the model.
- 2. Context setting: Start the prompt with relevant context information to establish a specific domain, topic, or scenario. This helps orient the model and ensures its responses are aligned with the given context.
- 3. System message: Consider using a system message to set the behavior of the model. A system message is a special instruction placed before the user message, influencing the model’s role or persona in the conversation. For example, you can instruct the model to play the role of a historical figure or adopt a specific tone.
- 4. Explicit user instructions: Clearly state what you want the model to do or provide. For example, if you want the model to summarize a passage, explicitly mention it in the prompt.
- 5. Multiple-turn conversations: If you want to have a multi-turn conversation with the model, you can maintain a consistent persona by using a system message at the beginning of each turn. Additionally, you can use user instructions to explicitly refer to prior messages or refer back to the conversation history.
- 6. Temperature and max tokens: Adjust the temperature parameter to control the randomness of the model’s responses. Higher values like 0.8 make the output more random, while lower values like 0.2 make it more focused. Set an appropriate maximum number of tokens (e.g., 50 tokens) to limit the response length and avoid getting cut-off responses.
- 7. Experiment and iterate: Prompt engineering is an iterative process. Experiment with different prompts, instructions, and parameters to refine the model’s behavior and achieve the desired outputs. Adjust the prompts based on the model’s responses to improve its accuracy and relevance.
Example: in the image above this blog, I used this ChatGPT prompt:
It’s important to note that while ChatGPT prompt engineering can help guide the model’s behavior and thus increase your productivity and creativity, it does not guarantee perfect responses. Monitoring and reviewing the model’s outputs, along with human oversight, are crucial to ensure the quality & accuracy.
However, ChatGPT prompt engineering is without a doubt a key AI-skill you have to possess if you want to be succesful in FinTech and RegTech in the future.
That is why we have designed different on-demand workshops on:
- ChatGPT prompt engineering for managers.
- ChatGPT prompt engineering for HR-professionals.
- ChatGPT prompt engineering for marketeers.
- ChatGPT prompt engineering in customer experience.
- ChatGPT prompt engineering for entrepreneurs.
- ChatGPT promot engineering for corporate FinTechs, for FinTech Startups * for FinTech Scaleups.
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If you want learn the right ChatGPT prompt engineering skills and fast, contact us today for a free online intake session. Please email your mobile number and the link to your LinkedIn profile using this form. Then we immediately will contact you to schedule that call or face-to-face meeting.
Kind regards,
Tony de Bree
p.s. Let’s connect on LinkedIn and follow me on Instagram and on Twitter @tonydebree & @fintechtrends.
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