ChatGPT Sparks Lasting Demand for Prompt Engineers – A Year Later!
Prompt engineering has proven to be a lucrative and enduring skillset, as evidenced by its staying power in the year since ChatGPT was introduced to the public. Despite ongoing speculation about AI rendering certain jobs obsolete, this particular skillset has emerged as a valuable asset.
Google searches for the term — which refers to the art of using artificial intelligence tools to create better images and written answers — have increased by an order of magnitude since a year ago. LinkedIn noted in its November Future of Work report that the proportion of “prompt engineering” and “prompt crafting” in member profiles has increased significantly.
“The joke I heard this year is that the most popular programming language in 2023 will be English,” said Justin Farris, director of product management at software development platform GitLab. He made his remarks in an interview for the latest episode of the Bloomberg Originals series AI IRL, which is now streaming.
The rise of high-speed engineering jobs highlights another way AI could reshape the job market—not just by eliminating roles, but by promoting workers who are adept at using and massaging AI services into jobs. Like all artificial intelligence, however, the technology is rapidly evolving in ways that may one day displace these workers as well. For example, last month OpenAI released the latest version of its image generator, Dall-E, and suggested that it had been improved enough to reduce the need to “learn fast design.”
Farris expressed optimism for rapid planning in the near future. “In 12 months, I think more and more people will be using it,” he said. “We’re so early. Everyone in tech is talking about it, but it hasn’t crossed the chasm where everyone else is using it.
Newly created engineering roles can pay as much as $335,000 a year, Bloomberg reported in March, and involve people who spend their days coaxing artificial intelligence systems to produce better results or helping companies train their employees to take advantage of the technology.
“The reason those people are compensated so much is because they also have expertise in their field,” Farris said. He likened the know-how to someone who knows advanced applications like Microsoft Corp.’s Excel, but also has a deep understanding of the subject matter behind the numbers and formulas they enter into a spreadsheet.
Farris offered several pieces of advice for people interested in becoming a fast engineer or making better use of AI in their work. Among them was learning to iterate with tools like ChatGPT — and being patient.
“Discuss one of these systems and give it more information,” he said. “Wait to get the result you want on the tenth query, not the first. Because when you do that, you’re giving the model a lot of context and domain to get better results. You might not get it on the first query.”
