The model picker — when Sonnet is wrong and Haiku is right — step 3 of 8

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound record with one of 8 categories. 20,000 records/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound incident note with one of 8 incident labels. 20,000 notes/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound campaign asset with one of 8 ship labels. 20,000 assets/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound brand asset with one of 8 kit labels. 20,000 assets/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound support ticket with one of 8 categories. 20,000 tickets/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound claim line with one of 8 clearance labels. 20,000 lines/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound research cut with one of 8 confidence labels. 20,000 cuts/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound tracker row with one of 8 risk labels. 20,000 rows/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound application with one of 8 screening buckets. 20,000 applications/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound handoff step with one of 8 exception labels. 20,000 steps/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)

# four real tasks. each one is a real product feature you might ship.
# think volume x difficulty before picking.
tasks = [
    "A: Tag every inbound discovery doc with one of 8 privilege categories. 20,000 docs/day.",
    "B: Generate a 4-week marketing strategy for a Series A SaaS launch. Runs maybe once.",
    "C: Extract {amount, vendor, date} from 5,000 expense receipts per day.",
    "D: Architect a multi-tenant database migration plan for a 50-table schema.",
]
for t in tasks:
    print(t)