In 2023, the global prompt-engineering market was valued at $222.1 million and projected to expand at a compound annual growth rate (CAGR) of 32.8% from 2024–30. In early 2025, Sam Altman, CEO of OpenAI, said that “the prompting tricks that many people used in 2023 are no longer relevant, and some of them will never be needed again.” Were we too quick to predict prompt-engineering a great future?

According to Altman, the answer is yes. In Adam Grant’s Re-thinking podcast, he said that figuring out what questions to ask will soon be more important than figuring out the answer. Although it wasn’t clear what Altman meant by ‘figuring out what questions to ask’, it was clear that he wasn’t talking about prompting.

While the dictionary defines prompt-engineering as the process of designing inputs for generative AI models to deliver useful, accurate, and relevant responses, the process of figuring out what questions to ask is way harder to define.

In a recent TED Talk, Perplexity CEO Aravind Srinivas described our innate curiosity and relentless questioning as a “human quality that makes us so human.” But he didn’t give a definition of asking, let alone a guide for figuring out what questions to ask.

AI executives like Altman and Srinivas seem to agree that the most valuable skill in the age of AI is neither prompt-engineering, IQ, EQ, or adaptability. It’s the ‘human quality’ of figuring out what to ask. To understand and unlock this human quality, however, we do not get much help from the AI executives.

In my LinkedIn Learning course on how to unlock your question mindset to think clearly and navigate uncertainty, I make a fundamental distinction between speaking clearly and thinking clearly. While speaking clearly is about expressing and explaining something that you already know well, thinking clearly is about exploring and experimenting with something that you don’t know – yet.

Just as you can’t speak clearly unless you know what you want to say, prompting requires you to know what kind of answers you’re looking for. You must design your prompt in a way that makes it possible for AI to deliver useful, accurate, and relevant responses. And in order for you to do that, you not only need to know what it means for an answer to be useful, accurate, and relevant, you also need to adjust your input to the machine. In short, to be good at prompting, you must be good at adapting what you already know to what the machine can already do.

With asking, it’s the other way around. Just as you can’t think clearly unless you’re open to new insights and ideas, you can’t figure out what to ask if you think you already know the answer. To ask, you must be willing to be wrong – about what a useful, accurate, and relevant answer is, but also about everything else. And in order for you to do that, you not only have to acknowledge that you don’t know the answer, you also have to accept the possibility that there are no clear answers. In short, to be good at asking, you must be good at living with possibilities that are unknown to both you and the machine.

Srinivas seemed to reach a somewhat similar conclusion in his TED Talk when he said, “We are all curious and when we are curious, we want answers. We really do. But what we really want are those answers that lead us to the next set of questions.”

But where does that leave you? For Srinivas and other AI executives, it leads to a discussion of the future of technology: “With all of the world’s answers available to us,” Srinivas said, “the tools we use to ask our questions, and the stuff that we build using those answers, those to me are the future of our technology.”

But are the tools that Srinivas and others are building really designed for you to ask questions? Or are they designed for you to adapt what you already know to what the machines can already do? By not distinguishing between prompting and asking questions, AI executives are not making it easier for you to understand and unlock your ‘human quality’ of asking questions. Rather, they make it harder for you and everyone else to remember what asking questions is really about – that is:

The ASK acronym is not derived from ‘the future of our technology’. It is derived from the past and present of our humanity. More specifically, it is derived from philosophy’s 2,400 years of experience in asking the existential, ethical, and epistemological questions that no one – least of all a machine – can answer for you. These are the questions that help you figure out who you are, what is the right thing to do, and how you deal with what you (don’t) know. They typically present themselves as:

Existential doubt or crises, e.g. “Who am I if I cannot have the career, I thought I would have?” “Can I do bad things and still be a good person?” “Will I still be the same if I change how I live my life?”

Asking these kinds of questions of a tool built with the future of technology in mind may help you “build stuff”, but it won’t help you live with the fact that sometimes there are no clear answers. And when that is the case, it doesn’t matter how good you are at prompting. All that matters is whether or not you are willing to ASK.

So, maybe that’s what Altman meant when he said that figuring out what questions to ask will soon be more important than figuring out the answer? Maybe that’s what it takes to win in the AI age: To stop prompting and start ASK-ing?