Is that it, my opinions would include:

Level of Optimism : AI Systems should determine level of optimism and not provide hope all the time

Trust : AI systems should be built to trust

Beneficence : Maximize positive potential: Design AI to enhance human well-being, productivity, and opportunity and not replace human.

• What is prompt engineering?

  • For me , prompt engineering is just a way to interact with the llm. Similar to how we provide code to compilers. We make things understand and produce the desired output.

• Foundations of prompt engineering & Principles of prompt engineering

  • Single: Always focus your prompt on a single, well-defined task or question. This clarity is crucial for eliciting accurate and useful responses from Copilot.

  • Specific: Ensure that your instructions are explicit and detailed. Specificity leads to more applicable and precise code suggestions.

  • Short: While being specific, keep prompts concise and to the point. This balance ensures clarity without overloading Copilot or complicating the interaction.

  • Surround: Utilize descriptive filenames and keep related files open. This provides Copilot with rich context, leading to more tailored code suggestions.

• Best practices in prompt engineering

  • Provide enough clarity

  • Provide enough context with details

    Provide examples for learning and also for training

Source : https://learn.microsoft.com/en-us/training/modules/responsible-ai-with-github-copilot/3-six-principles-of-responsible-ai