When we initially started crafting solutions using GPT-4, I thought our expertise in data science, machine learning, and NLP would be crucial.
I was wrong.
Actually, building LLM applications with GPT-4 demands an entirely new skill set and even a job title that doesn't yet exist. We delve into this in Episode 8 of our AI Strategy Series, titled "The Surprising Skills You Need to Build LLM Applications."
The main hurdle? The developer interface. While LLMs are pseudo-intelligent and can execute complex, high-impact tasks, they can also produce inconsistent results and even generate false information.
This diverges significantly from the stable, "dumb" interfaces developers have engaged with for decades. The requisite skills involve an experimental mindset, akin to that of a data scientist, coupled with a systems-level engineering perspective—what we term an AI Systems Engineer.
AI Systems Engineer: Download this Free Job Description
The AI Systems Engineer will be your initial LLM application development team member. Their responsibilities include crafting prompts and interfaces, as well as possessing the apt blend of soft skills for designing experiments and educating the broader development team.
Feel free to adapt this job description for your organization. It'll signal to potential candidates that you’re on top of your game and offer a compelling opportunity.