Despite the buzz surrounding it, the prominence of prompt engineering may be fleeting.
Prompt engineering has taken the generative AI world by storm. The job, which entails optimizing textual input to effectively communicate with large language models, has been hailed by World Economic Forum as the number one “job of the future” while Open AI CEO Sam Altman characterized it as an “amazingly high-leveraged skill.” Social media brims with a new wave of influencers showcasing “magic prompts” and pledging amazing outcomes.
However, despite the buzz surrounding it, the prominence of prompt engineering may be fleeting for several reasons. First, future generations of AI systems will get more intuitive and adept at understanding natural language, reducing the need for meticulously engineered prompts. Second, new AI language models like GPT4 already show great promise in crafting prompts — AI itself is on the verge of rendering prompt engineering obsolete. Lastly, the efficacy of prompts is contingent upon the specific algorithm, limiting their utility across diverse AI models and versions.
So, what is a more enduring and adaptable skill that will keep enabling us to harness the potential of generative AI? It is problem formulation — the ability to identify, analyze, and delineate problems.
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