The Contrarian's Guide to AI

In a conversation on the High Agency Podcast, AI consultant Jason Liu shares insights into building reliable and scalable AI products, emphasizing the importance of measurable metrics and iterative testing. Liu, known for his expertise in RAG and LLM projects, discusses the value of diversifying AI applications and the significance of domain experts in AI product teams. He advocates for a focus on effective communication and clear evaluation criteria, suggesting that AI engineers should prioritize outcomes over the hype surrounding AI advancements. Liu introduces his Python library, Instructor, which aids in structuring LLM outputs and highlights its growing adoption. He also addresses the potential overhype of AI and the need for businesses to align AI use with tangible benefits rather than flashy technology. The discussion touches on the challenges of integrating traditional machine learning principles into modern AI workflows, the role of structured prompting, and the need for domain expertise in crafting effective AI solutions.