Inside AI Agents: What Sets Agentic Systems Apart by Cisco’s Product Leader
Product School
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Inside AI Agents: What Sets Agentic Systems Apart by Cisco’s Product Leader
536 просмотров · 1 г. назад
Product School
158 тыс. подписчиков
536 просмотров · 1 г. назад
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AI Agents is one of the hottest topics in the LLM world but the excitement is inversely proportional to the understanding of the systems itself. A simple test is to ask yourself: “What makes a system agentic?” If the response cannot meaningfully differentiate the said system with other ML systems, then this session is for you. We will also cover components of an agentic workflow and some high confidence hypotheses of why you don’t see the agentic systems everywhere around you (or maybe you do!).
Timestamps
🎙️ Welcome & Motivation for the Talk – 1:57
🧠 Understanding Agent Anatomy: 6 Key Components – 3:08
🔧 Tool Use & Memory in Agentic Systems – 5:09
🤖 Multi-Agent Collaboration & Guardrails – 8:38
📈 Framework for Evaluating Agentic System Fit – 23:42
🚦 Decision Vectors: When to Use Agentic Systems – 12:00
💡 Key Takeaways & Closing Reflections – 27:31
The content of this event is for educational purposes only and does not include any specific facts of the presenter’s current or previous company. The opinions expressed in this event are solely those of the presenter based on personal experiences and do not reflect those of the company the presenter works for.
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Meet the Speakers: Puneet Kamal, Engineering PM at Cisco Systems
Puneet Kamal is a distinguished Product Manager with a proven track record of driving innovation in machine learning (ML) and generative AI (GenAI) across some of the world's leading tech organizations. As an Engineering Product Manager at Cisco Systems, Puneet has been at the forefront of developing industry-first GenAI-powered automation frameworks, revolutionizing large-scale networking infrastructures with advanced self-healing and intelligent automation capabilities.