By Paul Chimodo
Remember the tech headlines of 2023? Amid the rise of large language models like GPT-4 and Claude, the world was told that “prompt engineering” could be one of the hottest jobs of the decade. A career where crafting the right AI instructions might earn you six-figure salaries without needing deep programming skills.
Three years on, that vision looks more like a mirage.
Today, the dedicated role of “prompt engineer” has all but faded. The dream of earning massive money simply by typing clever queries into an AI is largely gone, replaced by a more realistic view of where AI jobs actually are.
Experts like Aminat Shotade, an enterprise software engineer and AI specialist, describe prompt engineering as a “bridge job” — a temporary skill that filled the gap between early AI limitations and where the technology is heading. Right now, getting good results from AI still requires creativity and understanding, so specialists were in demand. But most of those roles were short-term contracts or project gigs rather than long-term career positions.
Many companies have treated prompt engineers like consultants brought in to solve an immediate problem before moving on. This reflects a broader trend in technology employment: when systems can perform a job efficiently, businesses tend to automate rather than maintain permanent human roles.
One key development that accelerated this shift was the rise of Automated Prompt Optimisation (APO) around 2024. Instead of relying on humans to fine-tune AI prompts, newer tools began automating the process by running thousands of prompt variations faster than any person could manage. As AI systems continue to improve their ability to learn and self-optimize, the need for humans as middlemen is shrinking.
Freelance platforms in 2026 still list prompt engineering tasks, but many are now micro-gigs such as rating AI responses, generating prompt variations or testing outputs. While these jobs provide short-term income, experts warn that they may not offer long-term career stability.
This is why some specialists advise against building a career solely around prompt writing. The main risk is not that the work does not exist, but that treating it as a primary professional identity could become limiting as technology evolves.
Instead, the most successful tech professionals are focusing on broader skill combinations. Many are moving into roles such as AI systems engineering, workflow architecture and domain-specific technology applications. These roles involve designing systems where AI is one component rather than the entire solution.
Industry observers also describe a shift sometimes called the “revenge of the subject matter expert.” In the early AI boom, there was an assumption that technology workers needed to teach AI about industry knowledge. Today, it is often more efficient to train professionals in fields such as medicine, law or marketing to use AI tools than to train prompt writers in those disciplines.
The lesson for young tech enthusiasts is clear. Prompt engineering is valuable as a foundational skill, similar to knowing how to use spreadsheet software or basic coding tools. However, building a sustainable career in the AI era requires deeper expertise that can grow over time, such as programming, data science, systems design or specialized domain knowledge.
As Shotade puts it: “Don’t be a hammer looking for nails; be a carpenter who knows when to use the hammer.”
Leave feedback about this