promptdojo_
Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

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

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