The original title is: "Practical lessons for building AI products users trust: consistency, validation, and starting small"

Short summary

This article argues that building an AI model is easy, but building an AI product people trust is hard. Key lessons include prioritizing consistency over model selection, avoiding constant model switching, keeping humans in the loop, and starting with small problems that save users time. The advice is generic but emphasizes user-centric AI product development.

• •Model selection matters less than data quality, validation, and consistency
• •Users forgive mistakes but not inconsistency — treat it as an engineering goal
• •Start with one problem solved well rather than trying to use AI everywhere

Generated with AI, which can make mistakes.