Model Online / On-Site
Duration
Modules 4 modules

Course Objective

To enable engineers to design fault-tolerant multi-agent systems capable of cyclic reasoning using LangGraph and stateful graph architectures where linear chains (DAGs) fall short.

Throughout the course, participants implement state persistence (checkpointing), time-travel debugging, human-in-the-loop interrupts, and production observability with LangSmith through hands-on coding.

Target Audience and Prerequisites

  • Target Audience: Senior software engineers, AI/LLM application developers, and technical architects designing complex autonomous systems.
  • Prerequisites: Strong Python proficiency (typing, asyncio, Pydantic) and prior experience with LLM APIs and tool calling.

Key Takeaways and Focus Areas

  • Balancing deterministic control and autonomous decision-making using StateGraph, Nodes, Conditional Edges, and Reducers.
  • Building resumable executions, interrupt gates, and human-in-the-loop approval workflows backed by PostgreSQL/Redis checkpointer stores.
  • Deploying Supervisor, Hierarchical, and Subgraph multi-agent patterns to production with LangGraph Platform and LangSmith.

Curriculum

Stateful Graph Architecture, State Schemas, and Cyclic Flows
  • StateGraph primitives, TypedDict/Pydantic state schemas, and custom reducer functions
  • Conditional edges, ReAct loops, and dynamic parallel node execution (Send API)
Checkpointing, Long-Term Memory, and Human-in-the-Loop
  • Thread-level persistence, cross-thread MemoryStore, and PostgreSQL checkpointer architecture
  • Breakpoints/interrupts, external state editing, and time-travel debugging
Advanced Multi-Agent Design Patterns
  • Modeling Supervisor, router, handoff, and nested subgraph topologies
  • Architecting plan-and-execute, reflection, and self-correcting RAG/code generation agents
Streaming, LangSmith Observability, and Production Deployment
  • Real-time streaming architectures across token, state update, and custom event modes
  • Tracing, evaluation with LangSmith, and scaling deployments on LangGraph Platform

Other Courses in This Category

  • Open-Source Model and Agent Ecosystem: Self-Hosted Enterprise AI Stack

    Learn how to serve open-source models like Llama, Mistral, and Qwen on vLLM, integrate them with open-source agent frameworks, and build a self-hosted enterprise AI stack.

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    4 modules
    View
  • Enterprise AI Development with Microsoft Azure AI Foundry

    Model selection, enterprise RAG and agent development, content safety filters, automated evaluation, OpenTelemetry tracing and secure deployment on Microsoft Azure AI Foundry.

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    5 modules
    View
  • Building Multi-Agent Systems with Microsoft Agent Framework

    Enterprise single- and multi-agent orchestration, MCP tool integration, memory and stateful process workflows using Microsoft Agent Framework (unifying Semantic Kernel and AutoGen).

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    5 modules
    View
  • GitHub Copilot and Autonomous Coding Agents for Engineering Teams

    Accelerating the software development lifecycle with GitHub Copilot Agent Mode, Copilot Coding Agent, custom instructions, IDE MCP servers and automated PR review.

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    5 modules
    View
  • Enterprise Agent Infrastructure with Amazon Bedrock AgentCore

    Deploying agents built with any framework (Strands, LangGraph, CrewAI) securely and at scale using Amazon Bedrock AgentCore: Runtime, Memory, Identity, Gateway and Observability.

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    5 modules
    View
  • Developing Production AI Agents with AWS Strands Agents SDK

    Building model-driven agents with the open-source AWS Strands Agents SDK: @tool decorators, native MCP integration, multi-provider model support, multi-agent patterns and OpenTelemetry tracing.

    Enterprise AI Platforms & Agent Cloud Ecosystem Corporate
    Live Course
    5 modules
    View

Get in touch