Mastering Intelligent Agents: A Deep Dive into Agentic AI
23 August 2025 | 09:30AM - 05:30PM
About the workshop
New to the world of Agentic AI and want to quickly get proficient in the key aspects of learning, building, deploying and monitoring Agentic AI Systems? This is the workshop for you! In this workshop you will get a comprehensive coverage of the breadth as well as deep dive into the depth of the vast world of Agentic AI Systems. Over the course of six modules, you will spend the entire day focusing on the following key areas:
- Learn essential concepts of Generative AI, Agentic AI and Agentic RAG Systems
- Deep dive into industry standard design patterns for architecting Agentic AI Systems - Tool-Use, Reflection, Planning, Multi-Agent
- Leverage Industry-Standard frameworks including LangChain, LangGraph and CrewAI to build simple and advanced Agentic AI & Agentic RAG Systems
- Learn basics of how to deploy Agentic AI Systems as APIs as well as debug and monitor them
While we want to keep the discussions as framework and tool-agnostic as possible, since 90% of the workshop will be hands-on focused; we will be using LangChain and LangGraph (currently the leading framework used in the industry) for most of the hands-on demos for building Agents and also a bit of CrewAI. While the focus of the workshop is more on building Agentic AI Systems we will also showcase how you can build a basic web service or API on top of an Agent using FastAPI and deploy and monitor it using frameworks like LangFuse or Arize AI Phoenix.
Important Note: You may need to register for some platforms like Tavily, WeatherAPI etc for the workshop (no billing needed), we will send the instructions ahead of time. That will be essential for running the hands-on code demos live along with the instructor in the session.
Additional Points
- Prerequisites: Solid understanding of Python, NLP and Generative AI will be useful
- Content Provided: Slides, complete code notebooks, datasets
- Infrastructure: Most of the hands-on demos we will do on Google Colab for the deployment and monitoring section we will provide the cloud infrastructure (either Colab or Runpod.io).
*Note: These are tentative details and are subject to change.
Instructor
Modules
This module will cover the essentials of Generative AI as a nice recap or refresher for everyone to be on the same foundational level and then we will dive into the essential concepts and components of Agentic AI Systems
- Whirlwind tour of Generative AI
- Recap of Prompting LLMs & RAG Systems
- Introduction to Agentic AI Systems
- Key components of Agentic AI Systems - LLM, Tools, Memory, Prompts, Routers, Workflows
- Current tool landscape in Agentic AI
- Tool Calling or Function Calling - The workhorse of Agentic AI Systems
- Hands-on: Prompting and RAG with LangChain
- Hands-on: Tool Calling for Agentic AI with LangChain
This module will build on the tool-calling aspects from the previous module and will teach you how to build basic tool-use Agents using LangChain, LangGraph & CrewAI and the ReAct pattern.
- Introduction to LangGraph and key components
- Hands-on: Build a ReAct Tool-Use Agent with LangGraph
- Hands-on: Build a ReAct Tool-Use Agent with CrewAI
- Hands-on: Build a Text2SQL Data Assistant Agent using LangGraph
This module will focus on how to manage short-term and long-term memory for Agentic AI Systems, how to store, manage and retrieve conversational history and agent workflow history for such systems. We will also look at in-memory and external memory management schemes and leverage these to build conversational Agentic AI Systems with LangGraph, LangMem
- Introduction to short-term and long-term memory
- Threads, memory snapshots, long-term memory stores
- Managing memory limits and context window limitations
- Internal and External Memory Stores
- Hands-on: Build a Conversational Agentic AI Financial Assistant
- Bonus: Using LangMem and Mem0 for advanced memory management
This module will focus on how to leverage industry-standard Agentic AI Design patterns and build and architect more advanced Agentic AI Systems leveraging tool-use, planning, reflection and multi-agent systems
- Key Design Patterns for Architecting Agentic AI Systems - Tool-Use, Planning, Reflection, Multi-Agent System
- Hands-On: Build your own Deep Research Agentic AI System leveraging Planning, Tool-Use, Multi-Agents
- Hands-On: Build Multi-Agent Systems for analysis & research - Supervisor / Hierarchical Architectures
This module will focus on how to leverage your enterprise or private data using RAG along with the power of AI Agents to build Agentic RAG Systems using industry-standard Agentic RAG architectures
- Key Design Patterns for Architecting Agentic RAG Systems - Router RAG, Adaptive RAG, Corrective RAG and more
- Hands-On: Build a Router RAG System for Customer Support Resolution
This module will briefly cover the key steps involved in building and deploying a simple Agentic AI System using LangGraph, FastAPI on the cloud and monitoring and tracking the Agent execution using popular monitoring frameworks like LangFuse or Arize AI Phoenix
- Key workflow for Building → Deploying → Monitoring an end-to-end Agentic AI System
- Hands-On: Build a simple LangGraph AI Agent (recap)
- Hands-On: Wrap AI Agent in a Web Service API using FastAPI
- Hands-On: Deploy Agentic API in the Cloud
- Hands-On: Test & Monitor AI Agent execution and traces
- Future Scope: Next Steps and Best Practices
