Join us for an in-depth session exploring the evolution from Large Language Models (LLMs) to autonomous Agentic AI. We will deconstruct the core architectures powering the next generation of AI applications, comparing top industry frameworks like LangGraph, AutoGen, and CrewAI. From mastering essential design patterns- such as the ReAct framework, multi-agent planning, and
structured memory- to implementing Human-in-the-Loop (HITL) guardrails, you will discover how to design scalable, responsible, and truly adaptive AI systems.


Key Takeaways:

  • The Paradigm Shift: Why the industry is moving from simple models to autonomous agents.

  • Framework Showdown: Real-world applications of LangGraph, AutoGen, and CrewAI.

  • Architecting Workflows: Deep dive into ReAct patterns, long-term memory integration, and HITL.

  • Production-Ready Strategy: Designing scalable, responsible systems built for the enterprise.

Webinar Registration

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Agenda for the session

  • From Prompts to Autonomous Agents
  • Designing Autonomous Workflows & Patterns
  • Scaling Responsibly with HITL Guardrails
  • Live Q&A

About Speakers

Mr. Manikant Kandukuri

Consulting Lead Data Scientist

Manikant is a passionate data scientist with 7+ years of experience. His wide experience includes his stints as a data scientist with companies like Deloitte. Qolsys, and Tiger Global. In addition to this, he has also spent considerable time mentoring learners to help them understand the intricacies of data science. Currently, he works on LLMs-based Generative AI projects using langchain, llamaindex, and other frameworks.

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