Sometimes the talk is of art, sometimes of science, sometimes of engineering. That makes sense. New practices are almost always first made understandable through familiar terms. This makes them seem more tangible, more relatable, and sometimes even more significant.
Nevertheless, a certain doubt remains as to whether these labels are truly accurate.
Perhaps prompting is neither art nor science nor engineering in the strict sense. Perhaps its significance lies elsewhere: in the fact that it creates a new form of access. A technique of approach. A vehicle into very different realms of knowledge and action.
Familiar terms are only partially applicable
Art, science, and engineering each have a domain in which their core competencies are relatively clear. Art creates its own spaces for expression. Science organizes knowledge with a commitment to method. Engineering develops robust solutions under specific conditions. In all three cases, distinct standards, routines, and forms of responsibility emerge.
With prompting, this is less clear.
Of course, it can be creative, systematic, and highly structured. Of course, one can be better or worse at it. And naturally, real advantages can be gained through experience, precision, and shrewdness. Nevertheless, there is much to suggest that prompting is not in itself a self-contained discipline, but rather operates between disciplines.
It often does not create its own space. It opens up access to existing spaces.
That is precisely where its true strength may lie
Those who are skilled at using prompts often achieve results surprisingly quickly. Ideas become more concrete, texts usable, images visible, analyses plausible, and code functional. This changes something fundamental: people can use language to approach topics more quickly that previously had higher barriers to entry.
That is no small thing. On the contrary.
Perhaps this is precisely where the true productivity of AI lies: in the fact that AI adds a new layer over virtually all knowledge and work processes. Not equally deep everywhere, not equally impactful everywhere, but in such a way that access to knowledge, expression, and preliminary capacity for action becomes broader and faster.
Prompting would then primarily be the practice of addressing this new layer.
Access is not the same as expertise
This is precisely why conceptual caution is warranted.
After all, just because AI and good prompts can generate results more quickly doesn’t mean that the expertise needed to reliably interpret those results automatically grows along with them. Someone who arrives at a legally sounding formulation, a medically sounding classification, or a technical sketch doesn’t necessarily already possess the judgment to reliably recognize quality, risks, and limitations.
Perhaps that is the crucial distinction: Prompts scale access. Competence grows more slowly.
This would not be a devaluation of prompts, but rather a clarification of their value. For access is an enormous resource. Access lowers barriers, accelerates first steps, and expands scope for action. But access does not automatically replace experience, responsibility, and deep contextual knowledge.
The Productive Confusion of Our Time
This may also be one of the defining tensions of the current phase of AI. Never before has it been so easy for so many people to enter specialized fields, produce initial results, and present themselves with a sense of confidence. This is fascinating and productive.
At the same time, this very fact gives rise to a new ambiguity.
For when access works so well, it can easily create the impression that it is the skill itself. As if the right input were already a sufficient substitute for experience. As if preliminary ability to act were already the same as established expertise.
Whether this is really the case is open to doubt.
What Continues to Define Expertise
Expertise isn’t merely about being able to produce something. It is most evident when results must be contextualized, contradictions identified, unintended consequences considered, and uncertainties managed. In other words, where judgment matters just as much as production.
Precisely because AI broadens access, this distinction could become even more apparent in the future.
For if more people arrive at initial results more quickly, the question of who can actually assess their quality becomes more important. Perhaps this is why AI does not diminish the value of expertise, but rather clarifies what it actually consists of: not mere production, but responsible judgment.
Why Caution Is Wise in Categorization
Terms like prompt engineering undoubtedly have practical value. They help to name and take a new practice seriously. But they may also lend it a coherence that does not yet exist. Prompts seem less like a distinct field of expertise than a cross-cutting foundational technology that touches on many fields of expertise but does not simply replace them.
Perhaps it changes the precursors of expertise more than expertise itself. Perhaps it shifts the threshold for participation more than the nature of skill. Perhaps that is precisely why it is so consequential.
A Cautious Hypothesis
If we don’t jump to conclusions too quickly, perhaps this idea stands out above all: Prompten primarily scales access to expertise, not expertise itself.
This is not a definitive conclusion. Rather, it is an observation made with reservations. But perhaps a helpful one. For it allows us to take the current enthusiasm seriously without rushing to make sweeping generalizations.
AI opens up new paths in the worlds of knowledge and work. Prompten is a central practice in this regard. Precisely for this reason, it is worth not losing sight of the difference between access and skill. For it is likely precisely there that it will be decided what in this technological upheaval is merely fast—and what truly endures.
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