“Prompt engineering” is no longer a job, but a skill

The big picture: The rise and fall of “prompt engineering” as a career path is a telling example of how quickly the AI job landscape can change. The era of easy-access, low-barrier AI roles may be over, replaced by positions that demand deeper expertise and a readiness to evolve alongside the technology itself.

Just two years ago, prompt engineering was the talk of the tech world – a seemingly essential new job born from the rapid rise of artificial intelligence. Companies were eager to hire specialists who could craft the right questions for large language models, ensuring optimal AI performance. The role was accessible, required little technical background, and was seen as a promising entry point into a booming industry.

Today, however, prompt engineering as a standalone role has all but disappeared. What was once a highly touted skill set is now simply expected of anyone working with AI. In an ironic twist, some companies are even using AI to generate prompts for their own AI systems, further diminishing the need for human prompt engineers.

The brief rise and rapid fall of prompt engineering highlights a broader truth about the AI job market: new roles can vanish as quickly as they appear. “AI is already eating its own,” says Malcolm Frank, CEO of TalentGenius, in an interview with Fast Company.

“Prompt engineering has become something that’s embedded in almost every role, and people know how to do it. Also, now AI can help you write the perfect prompts that you need. It’s turned from a job into a task very, very quickly.”

The initial appeal of prompt engineering was its low barrier to entry. Unlike many tech roles, it didn’t require years of specialized education or coding experience, making it especially attractive to job seekers hoping to break into AI. In 2023, LinkedIn profiles were filled with self-described prompt engineers, and the North American market for prompt engineering was valued at $75.5 million, growing at a rate of 32.8 percent annually.

Yet the hype outpaced reality. According to Allison Shrivastava, an economist at the Indeed Hiring Lab, prompt engineering was rarely listed as an official job title. Instead, it has typically been folded into roles like machine learning engineer or automation architect. “I’m not seeing it as a standalone job title,” she added.

As the hype fades, the AI job market is shifting toward roles that require deeper technical expertise. The distinction is clear: while prompt engineers focused on crafting queries for LLMs, machine learning engineers are the ones building and improving those models.

Lerner notes that demand for mock interviews for machine learning engineers has surged, increasing more than threefold in just two months. “The future is working on the LLM itself and continuing to make it better and better, rather than needing somebody to interpret it,” she says.

This shift is also evident in hiring trends. Shrivastava points out that while demand for general developers is declining, demand for engineering roles overall is rising. For those without a coding background, options are narrowing.

Founding a company or moving into management consulting, where expertise in AI implementation is increasingly valued, may be the best routes forward. As of February, consulting positions made up 12.4% of AI job titles on Indeed, signaling a boom in advisory roles as organizations seek to integrate AI into their operations.

Tim Tully, a partner at Menlo Ventures, has seen firsthand how AI is changing the nature of work, not necessarily by creating new jobs, but by reshaping existing ones. “I wouldn’t say that [there are] new jobs, necessarily; it’s more so that it’s changing how people work,” Tully says. “You’re using AI all the time now, whether you like it or not, and it’s accelerating what you do.”

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