GPT Prompt Engineering Will Haunt You
Prompt engineering, also known as shaping prompts to get exactly what you want from GPT-3 and ChatGPT will eventually bite you.
This post is here only so that I can say 6 months from now - I tried to warn you.
The core model used by GPT-3 is text-davinci-003. GPT-4 is on the near horizon and it will be so much more advanced, the prompts you build into your applications today will be fundamentally useless with text-davinci-004.
Prompt engineering is also aptly referred to as “spell casting”. You can cast spells on LLM’s (large language models) quite easily to achieve favorable results. GP3, for example, glosses over intermediate steps to reach conclusions, often resulting in misleading or entirely wrong conclusions. It is especially poor at math and computations in excess of three digits. But, when you insert a simple phrase “step by step” into the prompt, it seems to get a lot smarter. In some cases, this simple prompt assertion can increase its intelligent five times.
The prompts engineered for GP2 by countless beta testers and practitioners representing hundreds of thousands of hours in effort, pretty much completely fail when applied to GP3.
NLP spell-casting is a brittle approach.