Search Queries and AI Prompting
05-Jul-2023
In 1997 Google Search made it clear that as the number of information artifacts increased, the more discrete humans would have to become to find anything on the Interwebs. In 1997, we struggled to learn how to search. Some of us got good at it. Some, not so much, and many still struggle today. is still a thing. In contrast to modern search, artificial general intelligence is based on ALL the information artifacts plus ... ALL the ways all the information artifacts could ever possibly be used, remixed, joined, and analyzed. This is a massive difference and certainly a giant leap forward in information technology.
To say that prompt engineering is about discrete and articulate queries is almost laughable. Have we ever faced a more critical moment in history where we must choose words more wisely?
Over the years, have modern search systems become more forgiving or poorly crafted queries? Nope. AI queries will likely follow the same arc.
If anything, modern search systems have become more sensitive, producing less helpful outputs year over year. And this is why those who need to find stuff are turning to conversational UIs and UXs that can sustain context, perhaps nudging the productivity curve in their favor.
While search and AI productivity share similar challenges, prompt engineering subtly tosses a new monkey into the wrench. The slightest change in a prompt can significantly change outcomes to make them almost unrecognizable. Unfortunately, this - and this alone - suggests we need to shape prompts like we craft legal documents.
With great power comes the responsibility to advance future information systems that leverage this technology. We must tame prompts through well-understood change management processes.