Why AI Personalization Is Getting Worse Despite Better Models
In this monologue, the speaker argues that AI personalization quality is declining even as language models improve, because product teams are abandoning proper user modeling in favor of generic Retrieval-Augmented Generation (RAG) and large language model (LLM) wrappers. He explains that without building individualized context, AI systems remain shallow and make statistical guesses about human needs, leading to subpar experiences. The speaker emphasizes that humans are subjective, and what works for one user may not work for another, so the nuanced understanding of users must be retained in-house. He concludes with a clear recommendation: use LLMs solely for language processing while keeping reasoning, judgment, and user modeling within the product team, avoiding outsourcing the core human‑centric aspects of product design.
