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Instructor-led training / ai-agentic-langg

Enterprise Agentic Engineering: Advanced Orchestration with LangGraph & LlamaIndex

Master deterministic state machines, multi-agent cyclic graphs, and advanced enterprise retrieval using LangGraph and LlamaIndex.
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Instructor-led

ai-agentic-langg

Duration
2 Days
Format
Live Online
Access
Multiple Timezones

Overview

About this course.

This 2-day hands-on workshop equips engineers to design, build, and deploy production-grade, stateful multi-agent systems. Participants master deterministic state machines and cyclic graphs using LangGraph, implement advanced hierarchical data indexing and retrieval pipelines with LlamaIndex, build resilient real-world retry loops, and integrate human-in-the-loop validation checkpoints for high-reliability enterprise execution.

Objectives

What you'll learn

  • Design cyclic, stateful multi-agent architectures using LangGraph state machines.
  • Build advanced structured data indexing, parsing, and retrieval-augmented generation pipelines using LlamaIndex.
  • Bridge LlamaIndex advanced retrieval tools seamlessly into LangGraph agent nodes.
  • Implement production-ready persistence, time-travel debugging, and human-in-the-loop checkpoints.

Audience

Who it's for

  • Senior Software Engineers
  • AI Architects
  • Enterprise Systems Developers

Prerequisites

Before you start

  • Advanced proficiency in Python
  • Familiarity with foundational RAG concepts and vector databases
  • Experience working with Pydantic and data validation schemas

Outline

Course outline.

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1. Deterministic State Machines with LangGraph

  • State Machine Foundations: Overcoming the limits of linear DAG chains with cyclic, stateful agent graphs.
  • LangGraph Core Primitives: Configuring StateGraph, custom nodes, edges, conditional routing, and state reducers.
  • Resilience Engineering: Designing deterministic retry loops, global exception handling, and fallback routes.
  • Hands-on Lab: Engineering a cyclic, self-correcting agent loop with memory state persistence.

2. Enterprise Data Indexing & Tool Extraction with LlamaIndex

  • Advanced Ingestion Pipelines: Utilizing LlamaParse for complex documents, hierarchical indexing, and metadata tagging.
  • RAG as a Service: Packaging advanced vector index workflows and query engines into clean, deterministic execution functions.
  • Strict Schema Output: Enforcing rigid, structured Pydantic syntheses from disparate multi-source enterprise queries.
  • Hands-on Lab: Building an enterprise-grade multi-document querying engine optimized for agent consumption.

3. Multi-Agent Topology & Hybrid Orchestration

  • Cross-Framework Integration: Connecting LlamaIndex query engines as specialized tools within LangGraph nodes.
  • Multi-Agent Design Patterns: Developing supervisor-worker, hierarchical teams, and peer-to-peer communication graphs.
  • Visualizing System State: Leveraging LangGraph Studio for real-time trace testing, state inspection, and validation.
  • Hands-on Lab: Constructing a multi-agent supervisor network that routes complex operational prompts to specialized sub-graphs.

4. Enterprise Production Readiness & Capstone

  • Human-in-the-Loop Mechanics: Setting state breakpoints, auditing actions, and injecting human modifications during live execution runs.
  • Enterprise Ops & Tracing: Managing token limits, rate-limiting strategies, and advanced tracing via LangSmith.
  • 3-Hour Capstone Project: Architect a production-ready Enterprise Graph Orchestrator that uses LlamaIndex for heavy document parsing, LangGraph for cyclic agent routing, and an active Human-in-the-Loop verification gate.

For teams

Training a whole team?

Request private training for Enterprise Agentic Engineering: Advanced Orchestration with LangGraph & LlamaIndex and we'll follow up with a quote for your group.

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