Five industries walked through — what AI-native looks like in the wild (step 9/9) · agent harnesses

Checkpoint

One last thing before we move on. pass this to mark the lesson done, or skip and keep moving. hop to the next when you're ready.

Final drill. Synthesize the case-study method into one function: pick_industry(candidates) that takes a list of industry profiles and returns the name of the BEST candidate for an AI-native rebuild.

Each candidate is a dict with:

name: string
volume_per_week: int
rules_explicit: bool
outcome_structured: bool
incumbent_avg_age_years: int

Score each candidate using these rules (higher = better wedge):

volume_per_week >= 100: +30
rules_explicit: +25
outcome_structured: +25
incumbent_avg_age_years >= 20: +20 (incumbent trap is biggest)

Return the name of the highest-scoring candidate. On a tie, return the FIRST one (Python's max with key= preserves stable order).

Five candidates run. Expected output:

best: Insurance brokerage