The rise and case of prompt engineering: How a promising AI profession became obsolete within a very short time
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Published on: April 30, 2025 / update from: April 30, 2025 - Author: Konrad Wolfenstein
The rise and fall of prompt engineering: Like a promising AI profession, became obsolete within a very short time-picture: xpert.digital
Why prompt engineers disappear faster than they came
The rise and fall of the hottest AI job from 2023
The profession of prompt engineer's promptly advertised as a promising profession has gone through a remarkably short life cycle. While large voice models such as Chatgpt revolutionize the world of work, it turns out that specialized roles for the wording of optimal entries have already become largely superfluous in 2025. According to the current reports of Wall Street Journal, the “Hottest Ai job of 2023” has practically disappeared from the labor market within a few years. The rapid development of more powerful AI models that are getting better and better in understanding user intentions has meant that prompt skills are now more in demand as a general competence and less as an independent job profile. This development is an example of the unprecedented speed with which AI technologies change the labor market.
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The short history of prompt engineering
The term “prompt engineering” was created in the course of the spread of large language models (Large Language Models, LLMS) and describes the art of formulating precise instructions in order to obtain optimal answers from AI systems. Between 2022 and 2023, interest in this activity increased rapidly and developed into a much discussed new job profile in the tech industry.
The high phase: gold digging mood 2023
At the end of 2023, prompt engineering was one of the most coveted new jobs in the technology sector. A video of the Wall Street Journal in November 2023 showed that companies offered salaries of up to $ 250,000 a year for this role. The video showed that prompt engineering was seen as a completely new kind of job that had only been possible through the emergence of large voice models such as chatt.
The core of this activity was to write text inputs or “prompt” in order to obtain the best possible answers from generative AI systems. The logic behind it was simple: the better the input, the better the output. Prompt Engineers were viewed as a translator between man and machine, who should also make complex technology accessible to people without programming knowledge.
The quick disillusionment
Despite the initial enthusiasm and the high salary promise, disillusionment quickly occurred. Like Jared Spataro, Chief Marketing Officer for KI at Microsoft, noticed: “Two years ago everyone said: 'Oh, I think promptly engineer will be the hot job.' That doesn't turn out to be true at all ”. This statement illustrates how quickly the expectations have changed to this job description.
The reality in 2025 looks different: Isabelle Bousquette from Wall Street Journal found that she does not know anyone with the job title “prompt engineer”, and the tech executives with which she spoke could also give no examples. What started as a promising career path has practically dissolved within just two years.
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Reasons for the rapid decline
The rapid descent of the prompt engineering as an independent job description can be attributed to several technological and organizational developments that have led together to have specialized prompt engineers hardly in demand today.
Technological progress in AI models
An essential factor for decline is the quick further development of the AI models itself. The newer versions of large language models have become significantly better in intuitive to understand the intentions of the users. This reduces the need for highly specialized experts who formulate the perfect input.
Modern AI systems can now also ask questions if they do not fully understand an instruction. This interactive ability makes sophisticated prompt techniques less important because the models can use the dialogue to clarify.
Deloitte's annual “Tech Trends” report for 2025 identifies three pillars that drive the AI development forward: small language models, multimodal models and agent-based AI. These developments change the way we interact with AI and make specialized prompt formulation increasingly superfluous.
Democratization of prompt knowledge
Another important reason is the broad mediation of prompt skills within companies. Instead of relying on individual specialists, today train employees in various functions in effective use of AI models. Jim Fowler, CTO of Nationwide, summarizes it concisely: "We see that this becomes an ability within a job title, not an independent job title".
This democratization of knowledge corresponds to the general tendency to broaden AI competencies instead of concentrating them in isolated expert roles. This enables more employees to use AI tools effectively in their specific work areas.
Integration into existing job profiles
What was once intended as an independent profession has developed into a component within existing roles. AI-Prompt skills are considered as a supplement to existing job profiles today, not as a separate career path. This integration reflects a more realistic approach of how AI is embedded in the world of work.
Hannah Calhoon, VP of AI at Indeed, confirmed: "We have not necessarily seen many actual attitudes for this role". This indicates that despite the initial hypes, the real demand for pure prompt engineers was limited.
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Adaptation instead of specialization: The future of AI competencies
The transformation of the labor market by AI
The case of the prompt engineering is exemplary for the quick changes that AI causes on the labor market. This development fits into a broader pattern in which AI is eliminated both jobs and creates new ones, but at a pace that was unknown so far.
Change in the requirements for tech jobs
The JoBl landscape in the technology sector is becoming increasingly complex and confusing. According to the Wall Street Journal, job names have become “more diverse, ambiguous, overlapping and sometimes more meaningless”. This applies particularly in the area of AI, where new roles arise and disappear before a general understanding of its meaning can be established.
While promptly engineering promptly loses importance as an independent discipline, the demand for other AI-related skills increases. Comments on LinkedIn indicate that AI Systems Engineers and other positions that require deeper technical knowledge are now more in demand.
Effects on software development
AI not only changes roles around the AI itself, but also established professional fields such as software development. AI-based coding tools, which can automate significant parts of the coding process, contribute to efficiency increases of over ten percent and enable faster code production.
This development could lead to slimmer development teams and higher requirements when hiring new employees, since companies are increasingly relying on generative AI coding tools. This is another example of how AI transforms existing professional fields.
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The future of prompt competence
Although promptly engineering promptly loses importance as an independent profession, the ability to effectively communicate with AI systems remains relevant. However, it takes on a different form than originally expected.
Integration into different professional fields
In the future, prompt skills are expected to be integrated into a variety of professions. A LinkedIn user commented: "Each marketing team needs someone with AI competence, systemic thinking, prompt-expertise and test-and-learning mentality. It is less about job titles and more about anchoring these skills in a team".
This perspective indicates a more nuanced development: Instead of dedicated promptly engineers, companies need employees in various departments who can effectively use AI tools. The ability to interact with AI becomes a basic competence, similar to digital knowledge today.
New specializations and more complex tasks
While simple prompt engineering is obsolete through more advanced AI models, new, more complex rollers are created. A commentator on LinkedIn mentions, for example, that his company has hired a “promptly coordinator” instead of a prompt engineer, whose task is to “catalog prompt and to guide the functional end user when creating his prompt”.
Another comment indicates that prompts are also embedded in backend pipelines: “As long as LLMs are used-in the search, in recommendations, summaries, for agent-based work or for content generation-someone has to design, test and wait for the model behavior on a large scale". This indicates that specialized prompt-expertise remains relevant in certain technical contexts.
Teaching for the AI-driven world of work
The quick rise and fall of the prompt engineering offers valuable insights into the dynamics of the AI-driven labor market and provides teaching for employees and organizations.
Speed of technological change
Perhaps the most important knowledge is the unprecedented speed with which AI-related job profiles develop. While earlier technological revolutions often needed decades to transform certain professions, this happens in the AI age within a few years or even months.
This rapid evolution requires continuous adaptation and willingness to constantly develop their skills. It also underlines the importance of transferable core competencies towards highly specialized niche skills that could be quickly outdated.
Tendency to integrate instead of specialization
Another important finding is the tendency to integrate AI skills into existing roles instead of creating completely new specializations. This corresponds to a more realistic view of how technology is embedded in organizations.
For educational institutions and training programs, this means that you should convey AI skills as a supplement to existing specialist areas instead of training isolated AI specialists. The ability to use AI tools effectively in various professional contexts becomes increasingly valuable than pure technical expertise.
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The development of the AI work world
The rapid rise and fall of the prompt engineering as an independent job description illustrates the transformative power of artificial intelligence on the labor market. In just a few years, a promising career path has changed from a highly paid special profession to an integrated ability that is relevant over different roles.
Technological advances in AI models, the increasing democratization of AI knowledge and integration into existing job profiles have meant that dedicated promptly engineers are hardly in demand today. Nevertheless, the ability to effectively communicate with AI systems remains valuable, albeit in a different form than originally expected.
This development underlines the need for workers and organizations to adapt and further train themselves continuously. In a world of work that is increasingly shaped by AI, those who can anticipate technological changes and develop their skills accordingly.
The case of prompt engineering may only be the beginning of a broader transformation of the labor market by AI. While certain specializations arise and pass, the ability to adapt and to learn continuously remains the most important competence for the future of work.
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