In this interview for MIT SMR Voices, Albert Phelps, Co-founder of Tomoro.ai, discusses how leveraging human communication skills in prompt engineering maximizes AI potential, enhances collaboration, and drives enterprise innovation.
LLMs can boost worker productivity, but outputs may reflect less human creativity and originality.
From ideation to user testing, large language models are allowing companies to explore more ideas and iterate faster.
By implementing structured frameworks such as AI agents, integrating structured prompts, and incorporating human interaction patterns and guardrails, businesses can navigate LLMs' creative potential while ensuring reliability.
How do we know whether algorithmic systems are working as intended? A set of simple frameworks can help even nontechnical organizations check the functioning of their AI tools.
