In our rapidly changing world, the use of Generative AI is increasing daily. As an advocate for open-source technology and making learning accessible to all, I am eager to share the methods and principles I employ daily to create effective prompts. These strategies are designed to simplify and streamline your workflow process..
Before jumping into conclusions let’s get into the definition of Prompt Engineering and Thinking Principles that could be leveraged with any Large Language Models like gpt4/bard/opensource large language models.
Prompt Engineering
Prompt Engineering involves crafting precise questions or commands for AI models like GPT-4, BARD, or open-source alternatives to elicit specific, helpful responses. It enhances your interaction with AI for tasks such as email composition, content creation, or information retrieval.
GPT-4 Output
Bard / Gemini Output
From the above we can see both of the principles when adopted to create a low code platform gives a step by step understanding and process. It also give a person on what to work on and how to expand their mind. Feel free to write in the comments what prompts have you used to get better output.
For further collaborative projects feel free to connect to me in linkedin
Work Cited :
- [[ Prompt Engineering ]]
- [[ Prompting Guide ]]
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