Fast code that misses the user's reality is still the wrong code

AI is making implementation faster. That removes friction that used to give teams time to question assumptions before they became software. The risk is not bad code. It is polished, technically correct code built on the wrong model of how people actually use things.

This session reframes user empathy as a technical skill for engineers. Not the soft stuff. The reasoning shows up in API design, error states, data freshness, retries, validation, and the prompts engineers give AI before asking it to build. Product defines the destination. Engineering decides how the system behaves when the real world gets messy.

When AI can write the happy path quickly, engineering judgment matters more, not less.