The “Build it yourself” trap
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A developer shares a cautionary personal story about using AI coding tools to build an optimization model without sufficient domain expertise. The result looked correct but had glaring issues that only domain experts could spot. The core lesson: AI tools excel at producing plausible-looking output, which amplifies the Dunning-Kruger effect — the less you know about a domain, the harder it is to recognize what the AI got wrong. The real question isn't whether AI can build something, but whether you understand the domain well enough to validate what it built.
Table of contents
# A brief trip back to the beginning# YOLO mode, activated# Dunning-Kruger era of AI-assisted development# What I actually learnedSort: