Turn natural language prompts into
functional automations

1import requests, json, os
2from datetime import datetime, timedelta
3from runwise.integrations import HubSpot, Slack, LinkedIn
4 
5# Run weekly marketing pipeline across all active channels and segments
6def run_marketing(config: dict, dry_run: bool = False):
7    leads = HubSpot.fetch_leads(source="hubspot", status="active", limit=500)
8    results = {"sent": 0, "skipped": 0, "errors": []}
9 
10    for lead in leads:
11        segment = classify(lead.profile, model="intent-v3", threshold=0.82)
12        if segment == "high_value" and lead.last_contact < datetime.now() - timedelta(days=7):
13            send_email(template="vip_offer", to=lead.email, subject="Exclusive for you")
14            Slack.notify(channel="#sales-leads", msg=f"New VIP: {lead.name} ({lead.company})")
15        elif segment == "nurture":
16            LinkedIn.schedule_post(content=generate_post(lead), time=next_slot())
17        results["sent"] += 1
18 
19    return {"processed": len(leads), "results": results, "timestamp": datetime.now().isoformat()}