This podcast interviews Chip Huyen, author of "AI Engineering," about the evolving field of AI engineering and its differences from traditional machine learning engineering. The discussion covers defining AI engineering, common techniques for building AI applications (prompt engineering, RAG, fine-tuning), challenges in evaluating AI systems, and common mistakes teams make. Huyen emphasizes a structured approach, starting with simple solutions and iteratively increasing complexity, prioritizing problem understanding over solely focusing on new technologies. A key takeaway is the importance of data preparation and human evaluation in building effective AI systems, even with readily available APIs. The interview concludes with Huyen's perspective on the future of software engineering in the age of AI, highlighting the continued need for human problem-solving skills.
