Everything you need to know about writing world-class prompts that actually shape product behavior: the right methods, the hidden mistakes, the system prompts you can steal, and more.
Determine what specific information being presented may be inaccurate or false and indicate why you believe it to be that way. Indicate the specific section where this claim is made. Sections are numbered and there are sub-numbers within these sections. Refer to those where a sub-number is shown. Where possible, provide evidence to back up your claims and preferrably with real-world use-case scenarios. After your analysis has been completed, determine anything that should be added that the authors of the paper overlooked."
Really appreciate this thorough explanation as well as the mind shifts that need to happen when engineering prompts. I have several prompts that I'm going to take through the checklist. Also will create more rigor around our workflow in updating & approving prompts.
This is an incredibly clear and useful guide to successful prompt engineering. It is applying systems thinking and providing clear directions to an AI “product teammate” so it can have guiding principles for understanding, reasoning, using “judgment” when conflicts arise, and knowing the limits of what it can/should do. I truly appreciate the “less is more” message as well.
I highly recommend running the following prompt from various AI chatbots on this article. Here is the prompt:
"Do an in-depth analysis of the content located at:
https://www.productmanagement.ai/p/prompt-engineering
Determine what specific information being presented may be inaccurate or false and indicate why you believe it to be that way. Indicate the specific section where this claim is made. Sections are numbered and there are sub-numbers within these sections. Refer to those where a sub-number is shown. Where possible, provide evidence to back up your claims and preferrably with real-world use-case scenarios. After your analysis has been completed, determine anything that should be added that the authors of the paper overlooked."
This is a great example of how prompts are really product decisions.
The structure, constraints, and defaults matter more than clever wording.
Solid breakdown of what actually makes a system prompt reliable.
Glad you liked it, Sachin.
Really appreciate this thorough explanation as well as the mind shifts that need to happen when engineering prompts. I have several prompts that I'm going to take through the checklist. Also will create more rigor around our workflow in updating & approving prompts.
This is an incredibly clear and useful guide to successful prompt engineering. It is applying systems thinking and providing clear directions to an AI “product teammate” so it can have guiding principles for understanding, reasoning, using “judgment” when conflicts arise, and knowing the limits of what it can/should do. I truly appreciate the “less is more” message as well.