1 min lesson
The AI-for-its-own-sake trap
Say what this means in practice: "And use deterministic logic everywhere it's cheaper and more reliable."
Step 1 of 2
Interview move
Demo with discipline. Walk the slice end to end, then say what you deliberately cut and why, the approach you rejected (for example, parallel enrichment because cost outran the match-rate gain) and how it generalizes to a new program by swapping the trigger. Cursor finalists demo what they built and defend the decisions - the defense is half the grade.
The AI-for-its-own-sake trap
Bolting an LLM onto a step that a formula or a lookup handles better reads as weak judgment, not AI-native impact. Reach for AI to classify fuzzy inputs, personalize at scale or let an agent take an action - and use deterministic logic everywhere it's cheaper and more reliable.