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Rishav Kumar

Product Manager • 2m

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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AKHIL MISHRA

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vyshn av

Hey I am on Medial • 1m

As someone learning and building AI/ML systems, understanding LLM security risks is essential.

Anonymous

Hey I am on Medial • 1y

Microsoft has launched a new piece of open source infrastructure which allows users to direct multiple AI agents to work together to complete user tasks. Magentic-One (a play on Microsoft and Agentic) employs a multi-agent architecture where a lead

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Shuvodip Ray
•

YouTube • 1y

AI relies on robust data management across 7 key components to build effective AI models: 1. sources, 2. ingestion, 3. storage, 4. transformation, 5. analytics, 6. governance and security, and 7. orchestration.

Keval Rajpal

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Recently learn how LLM works, maths behind attention layers and transformer, continously trying to keep up with rapid development in AI space, getting so overwhelmed 🥲 Now google came with "Mixture-of-Agents (MoA): A Breakthrough in LLM Performance

Rahul Agarwal

Founder | Agentic AI... • 1m

Most people studying AI agents never deploy one real system people actually use. Because they stop at prompts. Prompting is practice. Building is different. Production systems require architecture, workflows, evaluation, and real operational think

Rahul Agarwal

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Baqer Ali

AI agent developer |... • 10m

Yep 2025 is the era of ai agents. We have MCPS that is the Model context protocol in which your AI agent that is a LLM model will have a access to server and that server will have tools like duckduckgo serach YFinance etc this was from antopic ai and

Ashinee Kesanam

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Google introduced yet another spectacular toolkit, the Agent Development Kit (ADK)—a free, open-source Python toolkit designed to simplify the creation of advanced AI agents. ADK empowers developers to build, test, and deploy multi-agent systems with