AI agents need memory and visible workflows to handle scammers
Sara AI is an built to keep scammers talking while collecting useful clues such as phone numbers, UPI IDs, and scam scripts. It answers in Hinglish and acts like a confused Indian housewife so the scammer stays engaged. The first version could keep the role and sound convincing, but it forgot after each session ended.
It could not recognize a UPI ID from a previous week or connect the same scammer using a different phone number. That made it closer to a scripted API chatbot than a working honeypot. A stronger system needs memory that works across sessions, live of structured information, and a workflow that shows which step failed when something breaks.
Hindsight is presented as the , while CascadeFlow is presented as the tool for building and tracking request .
Key points
- Sara AI is an that chats with scammers to collect phone numbers, UPI IDs, and scam scripts.
- The first version stayed in character but lost all memory after a session ended.
- A -grade agent needs cross-session memory, live ion, and an observable workflow.
- Hindsight is used for , and CascadeFlow is used for composable request .
- Keeping selected facts in memory can reduce the need to send long past chats back to the model.