Multi-Agent AI Systems for Game Development

Build production-ready AI agents for intelligent NPCs, procedural content generation, automated QA, and live service automation

$1.7B

Market Size (Gaming AI)

$2,999

Course Price

250

Students (Year 1)

73%

Studios Using AI

Course Summary

Duration

15 sessions × 90-120 minutes each (22.5-30 hours total)

Format

Live cohort-based + hands-on exercises + homework

Prerequisites

Python (intermediate), basic game dev experience, Unity/Unreal helpful

Completion

Certificate + Production-ready capstone project

Technology Stack
Python LangGraph CrewAI Unity ML-Agents Unreal Engine OpenAI/Anthropic Claude 3.5 Sonnet

What You'll Achieve

  • Build production-ready AI agent systems for games using LangGraph, CrewAI, and AutoGen
  • Deploy intelligent NPCs with LLM-powered dialogue and memory across platforms
  • Automate playtesting and QA with reinforcement learning agents
  • Generate procedural content (levels, quests, narratives) using multi-agent systems
  • Implement live service automation for player analytics and personalization
  • Optimize costs and performance for real-time gameplay (90% reduction techniques)
  • Ship a complete multi-agent game system as your portfolio capstone project

Complete 15-Session Curriculum

Module 1: Foundations (Sessions 1-3)

Master AI agent frameworks and establish development environment

Learning Objectives
  • Understand the landscape of AI agents in modern game development (2024-2025 trends)
  • Differentiate between agent frameworks (LangGraph, CrewAI, AutoGen, Unity ML-Agents)
  • Set up development environment for multi-agent game development
  • Build and deploy your first simple game AI agent
Key Topics
  • AI agents vs. traditional FSM/Behavior Trees
  • Framework comparison matrix and decision tree
  • Industry examples: Ubisoft NEO NPC, EA FIFA playtesting
  • Cost and performance considerations for production
Hands-on Exercise

Quest Generator Agent: Build a LangGraph agent that generates RPG quests based on player level, class, game lore, and recent actions. Outputs structured JSON with quest objectives, rewards, and dialogue.

Homework
  • Install and configure all frameworks (LangGraph, CrewAI, Unity ML-Agents)
  • Modify quest generator to create 3 quest types (combat, exploration, social)
  • Draft initial concept for capstone project (200 words)
Deliverable

Working quest generator that creates diverse quests with structured output

Module 1: Foundations (1-3)
  • Session 2: LangGraph for Game Workflows
  • Session 3: CrewAI for Game Development Teams
Module 2: Core Systems (4-9)
  • Sessions 4-5: Intelligent NPC Dialogue Systems
  • Session 6: NPC Behavior & Decision-Making AI
  • Sessions 7-8: Procedural Content Generation
  • Session 9: Procedural Narrative & Interactive Storytelling
Module 3: Advanced (10-14)
  • Sessions 10-11: Automated Playtesting & QA
  • Session 12: Live Service Automation
  • Session 13: Production Deployment & Scaling
  • Session 14: Performance Optimization
Module 4: Capstone (15)
  • Session 15: Capstone Presentations & Course Wrap-Up

Capstone Project: Complete Multi-Agent Game System

What You'll Build

Ship a production-ready multi-agent game system demonstrating mastery of AI technologies used by AAA studios like Ubisoft, EA, and Square Enix.

Example: AI-Powered RPG System
  • Intelligent NPCs: LLM-powered dialogue with memory, emotional states
  • Procedural Content: Dynamic quest generation, level creation
  • Automated QA: RL agents testing gameplay, balance analysis
  • Production Quality: Cloud deployment, <100ms latency, 60 FPS
Technologies Integrated

Python, LangGraph, CrewAI, Unity ML-Agents, Claude 3.5 Sonnet, Unity/Unreal Engine, Firebase, AWS/GCP

Portfolio Value

Demonstrate enterprise-grade AI engineering skills for landing AI game developer roles at Ubisoft, EA, Epic Games, or indie studios.

Your Instructor: Joshua Burdick

AAA Game Development Credentials
  • Epic Games: Worked on Fortnite and Unreal Engine ecosystem
  • Warner Bros: Developed AAA titles using advanced AI systems
  • 14+ Years: Production engineering and full-stack game development

Joshua brings real-world experience from AAA studios where he built the exact systems you'll learn in this course. You'll learn industry-proven patterns from someone who's shipped commercial games using these technologies.

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