Every major shift in technology has carried with it a rush of teachers, trainers, and consultants eager to turn new tools into marketable lessons. When the typewriter became common, entire schools were established to train secretaries. When spreadsheets spread through offices, workshops promised to teach the secrets of Excel. In our time, the rise of artificial intelligence has created a flood of tutorials, online courses, books, and seminars. The pattern is familiar: each new tool is accompanied by a new “skill set” to be mastered.
With AI, this dynamic is especially visible. The term “prompt engineering” appeared almost immediately after language models became widely available. Suddenly, the ability to phrase requests in just the right way was treated as a technical art. Articles and courses promised to teach the tricks of wording, structure, and order. The implication was that those who learned this new skill would hold an advantage over others. A similar movement is beginning around the idea of “specs,” structured documents that guide AI systems in a more consistent way.
The existence of these economies is not surprising. People are always drawn to anything that promises a clear path through uncertainty. The sense of learning a skill, receiving a certificate, or mastering a new technique provides both comfort and legitimacy. But the deeper question is whether AI really demands this constant cycle of new skills, or whether it points us toward something more foundational.
The Business Model of Skills
The business model of skills thrives on novelty. Each time a new tool appears, a new set of courses and certifications follows. The value is not always in the skill itself but in the sense of participation. Attending a workshop, completing a module, or adding a certificate to a résumé signals to oneself and to others that one is keeping up with the times.
This pattern has repeated across history. The arrival of the typewriter generated courses in “touch typing” that were marketed as the key to office success. When computers became commonplace, short courses in “computer literacy” promised to open the gates of opportunity. Later, spreadsheets created an entire industry of Excel manuals and seminars. Even soft skills like communication, leadership, or mindfulness have been wrapped into workshop culture, where techniques are packaged into steps and sold as mastery.
There is nothing inherently wrong with this. People often gain confidence and competence by participating in such programs. At the same time, the cycle is clear: new tool, new skill, new market. AI has simply become the latest and most profitable stage of this model. The question is whether this cycle still makes sense when the very tool being taught is capable of performing the skill on our behalf.
The Fragility of Skills in the Age of AI
The fragility of the skills economy becomes obvious when we recognize what AI can already do. Take prompts as an example. For a short period, “prompt engineering” was treated as a rare talent. Yet within months, AI itself was able to generate better prompts than most humans. If one asks a model to write an effective prompt for a task, it can often produce a refined version that outperforms casual attempts.
The same applies to “specs.” They may be a useful way to organize requirements, but nothing prevents AI from drafting them. A team can hold a brainstorming session, record their raw notes, and then ask an AI to generate a structured specification document. What was once a marketable skill is absorbed into the tool itself. The cycle of learning is shortened, sometimes to the point of disappearing entirely.
This reveals the irony. The very economy that grows around teaching people how to use AI is undercut by AI’s ability to handle the skill itself. The more the tool improves, the less sense it makes to devote time and money to mastering its tactical aspects. This does not mean skills disappear entirely, but it shifts attention to something else. If AI can generate prompts and specs, then the real task lies elsewhere.
Beyond Tactics: The Human Foundation
The difference between tactics and foundations is crucial. Tactics are surface skills, often limited to particular tools or formats. They are useful but replaceable. Foundations are the deeper capacities that shape who we are and how we live. They involve judgment, imagination, discernment, authorship, and integrity.
AI has revealed that tactics are easier to automate than many expected. What once looked like rare expertise turns out to be reproducible. This forces a return to foundations. Instead of asking, “How do I master the next skill?” we are invited to ask, “What is the core of my own thinking, and how do I strengthen it?” This shift is not comfortable, because foundations cannot be acquired through a weekend course. They require ongoing reflection and practice.
The real gift of AI, then, may not be the mastery of new technical tricks, but the exposure of what truly matters. When the surface is taken care of by machines, we are left with the deeper work that cannot be outsourced. AI can provide structure, but it cannot tell us what we value. It can generate drafts, but it cannot provide the life experience that makes writing meaningful.
Growth versus Efficiency
The dominant narrative in organizations often revolves around efficiency. How can we achieve more with fewer people? How can processes be streamlined and outputs multiplied? From this perspective, AI is welcomed as a tool of acceleration. Specs and prompts fit neatly into this vision, because they promise control and repeatability.
Yet there is another dimension that matters just as much, if not more: growth. Growth is not about more output, but about deepening understanding, expanding perspective, and enriching life. It is about becoming more fully human. AI can play a role here as well, not by increasing speed but by creating space for reflection.
The irony is that what organizations prize as efficiency may not be what humans need most. For individuals, the deeper blessing of AI is the chance to reorient attention toward growth. When repetitive or tactical tasks are absorbed by machines, time is freed for exploration, creativity, and the cultivation of wisdom.
The Trap of Superficial Progress
Certificates and licenses create the impression of progress. They serve as visible markers of advancement, yet often they measure compliance rather than transformation. Completing a course or earning a badge may demonstrate that one has followed instructions, but it does not necessarily indicate a change in understanding or character.
AI has made this hollowness more visible. If the certificate is for a skill that AI already performs, then the badge becomes symbolic rather than practical. It signals participation in a trend rather than mastery of something enduring. The danger is that we mistake the appearance of progress for the substance of growth.
True progress is harder to measure. It shows in the way someone thinks, writes, and acts. It is visible in judgment, clarity, and integrity. These qualities cannot be reduced to a set of steps, nor can they be granted by a license. They must be lived and cultivated over time. AI, by removing the illusion of certain tactical skills, brings us back to this truth.
The Blessing of Companionship
One of the most profound ways AI can serve is as a companion in inquiry. Not a replacement for thought, but a partner in reflection. Through conversation, AI can surface perspectives, test ideas, and provide mirrors that help us see our own assumptions. This is not about efficiency or automation, but about companionship in the pursuit of meaning.
The contrast with the skills economy is sharp. Workshops produce tactical competence. Dialogue with AI can produce insight. Certificates validate technique. Companionship fosters growth. The first belongs to the surface of productivity. The second belongs to the depths of intellectual and spiritual life.
When AI is approached as a partner in dialogue, it becomes more than a tool. It becomes a presence that can provoke, question, and support. It does not remove the responsibility of authorship, but it can make the journey richer. This is the dimension that many overlook when the conversation is reduced to skills and tactics.
Re-imagining Learning and Work
If AI exposes the fragility of tactical skills, then education and work must be reimagined. Education should not be centered on the endless acquisition of skills that tools can already perform. It should be about cultivating the foundations of judgment, empathy, creativity, and clarity. Work should not be defined only by output, but by the pursuit of meaning and contribution.
This does not mean skills vanish, but they take their proper place. They are useful in service of deeper aims, not ends in themselves. AI can generate the tactical elements, but it cannot replace the work of deciding what matters. This opens the door for a reorientation of both education and professional life.
The challenge is cultural as much as technical. We must shift from valuing only what can be measured to recognizing the worth of what is lived. Certificates may continue to circulate, but the true task will be to nurture capacities that cannot be outsourced. AI has made this choice clearer by revealing how quickly skills can be automated.
The True Task
The skills economy will not disappear. There will always be new workshops, new certificates, and new agencies offering the latest tactical advantage. This is part of how economies function, and it will continue as long as people seek reassurance and legitimacy.
But for individuals, the question is different. Do we chase tactics, or do we seek foundations? Do we measure progress by badges, or by growth in understanding and character? AI brings this question into focus. It takes care of the surface, leaving us with the core.
The true blessing of AI lies here. Not in the endless cycle of mastering and monetizing new skills, but in the rediscovery of what cannot be automated: the growth of thought, the clarity of writing, the pursuit of meaning, and the companionship of dialogue. These are not skills to be mastered, but foundations to be lived. AI has exposed the difference, and in doing so, it has offered us the chance to return to what matters most.
Image by Johnnie Shannon
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