It's a really strange intersection of my literary background and analytical thinking. As a poet, the role also feeds into my obsessive nature with approaching language. I love the "mad scientist" part of the job where I'm able to come up with a dumb idea for a prompt and see it actually work. In addition to the pure prompt-engineering part of my job, I also advise on how the models behave, why they might behave the way they do, which model to use, whether we can make a specific tool, and what approach we should take to do that. Example-following, or "here are some good product descriptions, write one like this about this.".Instruction, or "write a product description about this.". It's my job, then, to write prompts that can get that query to generate the best output through: In simple terms, a user types something like, "write a product description about a pair of sneakers," which I receive on the back end. I do this by designing the text around a user's request. In practice, I spend my days writing text-based prompts - which I can't reveal due to my NDA - that I feed into the back end of the AI tools so they can do things such as generate a blog post that is high-quality, grammatically correct, and factually accurate. Since then, the scope of my job has grown I now help improve existing tools and create new ones with the goal of getting the AI to spit out the best responses for users. Taking his advice, I managed to come up with a solution for better tone adherence, which led to a full-time job offer at the company. But then the founder explained that prompting is kind of like writing a spell: If you say the spell slightly wrong, something slightly wrong can happen - and vice versa. At first, I barely knew what I was doing. Soon after, I got offered a one-month contract to work on executing different types of tones. Account icon An icon in the shape of a person's head and shoulders.
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