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Rishav Kumar

Product Manager • 6h

Hey, Is anyone building for LLM-native systems and AI agents? 1. LLM analytics & intelligence: Traditional tools like CleverTap or Google Analytics track events and drop-offs, but it won't work in conversational systems. When users interact with LLMs or agents, we lack visibility into resolution quality, sentiment, intent completion, and churn risk. 2. AI agent orchestration: Companies run multiple agents across sales, support, and ops. Let's say the company is a payment gateway and a customer says “I was charged twice for the same payout. I want to cancel the subscription". A double-charge complaint plus a cancellation request may trigger refund and subscription agents. An orchestrator decides which agents to invoke, in what order, with shared context and guardrails. I'd love to brainstorm it with anyone interested and build an MVP to validate it.

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