elizaOS

Technical Track Introduction

Master the art of building sophisticated AI agents with ElizaOS

Welcome to the Technical Learning Track for ElizaOS - your comprehensive guide to building production-ready AI agent systems.

What You'll Build

By completing this track, you'll be able to create:

  • Autonomous AI Agents that can reason, plan, and execute complex tasks
  • Custom Plugins extending ElizaOS with new capabilities
  • Multi-Agent Systems where agents collaborate and coordinate
  • Production Deployments handling thousands of concurrent users
  • Advanced Integrations with external APIs, blockchains, and services

Who This Track Is For

Perfect For

  • Full-Stack Developers wanting to add AI capabilities to applications
  • Backend Engineers building scalable AI infrastructure
  • DevOps Engineers deploying and monitoring agent systems
  • AI Researchers experimenting with agent architectures
  • Technical Founders building AI-powered products

Prerequisites

Required Knowledge:

  • TypeScript/JavaScript: Comfortable with ES6+, async/await, modules
  • Node.js: Understanding of event loop, npm/bun, package management
  • Git: Version control, branching, pull requests
  • APIs: REST, WebSockets, authentication patterns

Helpful but Not Required:

  • Docker and containerization
  • Database design (PostgreSQL)
  • AI/ML fundamentals
  • Cloud deployment (AWS/GCP/Azure)

Technical Architecture Overview

Core Technical Concepts

1. Agent Runtime

The AgentRuntime is the heart of ElizaOS - an orchestration system that:

// Core runtime responsibilities
class AgentRuntime {
  // Manages agent lifecycle
  async initialize(): Promise<void>
  
  // Processes incoming messages
  async processMessage(message: Memory): Promise<Response>
  
  // Manages state and memory
  async composeState(message: Memory): Promise<State>
  
  // Coordinates actions
  async evaluateActions(state: State): Promise<Action[]>
  
  // Handles service registration
  registerService(service: Service): void
}

Key Concepts:

  • Event-driven architecture for scalability
  • Plugin-based extensibility for modularity
  • State composition for context awareness
  • Action evaluation for decision making

2. Memory System

ElizaOS implements a sophisticated memory architecture:

interface MemorySystem {
  // Short-term memory (conversation context)
  conversationMemory: Memory[]
  
  // Long-term memory (persistent storage)
  longTermMemory: MemoryStore
  
  // Semantic memory (knowledge base)
  knowledgeBase: KnowledgeStore
  
  // Working memory (current state)
  workingMemory: State
}

Memory Types:

  • Conversational: Recent messages and context
  • Episodic: Specific events and interactions
  • Semantic: Facts and knowledge
  • Procedural: How to perform tasks

3. Plugin Architecture

Plugins extend ElizaOS capabilities:

interface Plugin {
  name: string
  description: string
  
  // Optional components
  actions?: Action[]
  evaluators?: Evaluator[]
  providers?: Provider[]
  services?: Service[]
  
  // Lifecycle hooks
  onInitialize?: (runtime: IAgentRuntime) => Promise<void>
  onMessage?: (message: Memory) => Promise<void>
}

Plugin Categories:

  • Model Providers: AI model integrations (OpenAI, Claude, Ollama)
  • Platform Clients: Social platforms (Discord, Twitter, Telegram)
  • Service Integrations: External APIs and services
  • Custom Logic: Domain-specific functionality

4. Action System

Actions are the "muscles" of your agent:

interface Action {
  name: string
  description: string
  
  // Validation logic
  validate: (runtime: IAgentRuntime, message: Memory) => Promise<boolean>
  
  // Execution logic
  handler: (runtime: IAgentRuntime, message: Memory) => Promise<Response>
  
  // Optional examples for better AI understanding
  examples?: Example[]
}

Action Types:

  • Response Actions: Generate replies
  • Tool Actions: Use external tools
  • State Actions: Modify agent state
  • Integration Actions: Interact with services

Track Curriculum

Phase 1: Foundation (Week 1)

Day 1-2: Architecture Deep Dive

  • Understanding the runtime lifecycle
  • Plugin system architecture
  • Memory and state management
  • Event-driven patterns

Day 3-4: Development Environment

  • Setting up TypeScript development
  • Debugging ElizaOS agents
  • Testing strategies
  • Performance profiling

Day 5-7: First Custom Plugin

  • Plugin structure and lifecycle
  • Creating custom actions
  • Adding evaluators and providers
  • Testing and deployment

Phase 2: Advanced Development (Week 2)

Day 8-9: Memory Systems

  • Implementing custom memory stores
  • Vector databases for semantic search
  • Knowledge graph integration
  • Memory optimization techniques

Day 10-11: Multi-Agent Systems

  • Agent communication protocols
  • Shared state management
  • Coordination patterns
  • Consensus mechanisms

Day 12-14: Production Systems

  • Scaling strategies
  • Error handling and recovery
  • Monitoring and observability
  • Security best practices

Phase 3: Specialization (Week 3)

Choose your specialization path:

Path A: Platform Integration

  • Building custom clients
  • WebSocket management
  • API rate limiting
  • Platform-specific features

Path B: AI/ML Enhancement

  • Custom model providers
  • Fine-tuning strategies
  • Prompt engineering
  • RAG implementation

Path C: Infrastructure

  • Kubernetes deployment
  • Auto-scaling agents
  • Distributed systems
  • High availability

Development Best Practices

Code Organization

// Recommended project structure
my-elizaos-project/
├── src/
│   ├── plugins/           // Custom plugins
│   │   ├── my-plugin/
│   │   │   ├── index.ts
│   │   │   ├── actions/
│   │   │   ├── providers/
│   │   │   └── tests/
│   ├── agents/           // Agent configurations
│   ├── lib/              // Shared utilities
│   └── types/            // TypeScript definitions
├── tests/                // Test suites
├── scripts/              // Build and deploy scripts
└── docs/                 // Documentation

TypeScript Patterns

// Use strict typing for safety
import { IAgentRuntime, Memory, State } from '@elizaos/core';

// Define clear interfaces
interface MyCustomAction extends Action {
  customProperty: string;
  
  // Use generics for flexibility
  process<T extends Memory>(input: T): Promise<ProcessedResult>;
}

// Leverage type guards
function isValidMemory(obj: unknown): obj is Memory {
  return obj !== null && 
         typeof obj === 'object' && 
         'content' in obj;
}

Testing Strategy

// Unit tests for individual components
describe('CustomAction', () => {
  it('should validate correct messages', async () => {
    const result = await action.validate(runtime, message);
    expect(result).toBe(true);
  });
});

// Integration tests for plugins
describe('MyPlugin', () => {
  it('should register with runtime', async () => {
    const runtime = new AgentRuntime(config);
    await runtime.registerPlugin(myPlugin);
    expect(runtime.plugins).toContain(myPlugin);
  });
});

// E2E tests for complete flows
describe('Agent Conversation', () => {
  it('should handle multi-turn dialogue', async () => {
    const agent = await createAgent(config);
    const response = await agent.chat('Hello');
    expect(response).toMatchSnapshot();
  });
});

Performance Optimization

Key Metrics

  • Response Time: < 500ms for simple queries
  • Throughput: 100+ concurrent conversations
  • Memory Usage: < 500MB per agent instance
  • Token Efficiency: Optimize context windows

Optimization Techniques

// 1. Efficient state composition
async function composeState(message: Memory): Promise<State> {
  // Parallel data fetching
  const [memories, knowledge, context] = await Promise.all([
    this.searchMemories(message),
    this.searchKnowledge(message),
    this.getRecentContext()
  ]);
  
  // Selective inclusion based on relevance
  return {
    relevantMemories: memories.slice(0, 5),
    knowledge: knowledge.slice(0, 3),
    recentMessages: context.slice(0, 10)
  };
}

// 2. Caching strategies
const cache = new LRUCache<string, EmbeddingVector>({
  max: 1000,
  ttl: 1000 * 60 * 60 // 1 hour
});

// 3. Connection pooling
const dbPool = new Pool({
  max: 20,
  idleTimeoutMillis: 30000,
  connectionTimeoutMillis: 2000,
});

Security Considerations

Authentication & Authorization

// Implement API key validation
middleware.authenticate = async (req, res, next) => {
  const apiKey = req.headers['x-api-key'];
  
  if (!apiKey || !await validateApiKey(apiKey)) {
    return res.status(401).json({ error: 'Unauthorized' });
  }
  
  next();
};

// Role-based access control
const checkPermission = (action: string) => {
  return async (runtime: IAgentRuntime, message: Memory) => {
    const user = await runtime.getUser(message.userId);
    return user.permissions.includes(action);
  };
};

Data Protection

  • Encryption at rest for sensitive data
  • Input sanitization to prevent injection
  • Rate limiting to prevent abuse
  • Audit logging for compliance

Contributing to ElizaOS

Getting Involved

  1. Start Small: Fix documentation, add tests
  2. Build Plugins: Share your creations
  3. Report Issues: Help improve the framework
  4. Join Discussions: Share your expertise

Contribution Workflow

# Fork and clone
git clone https://github.com/yourusername/eliza.git
cd eliza

# Create feature branch
git checkout -b feature/my-awesome-feature

# Make changes and test
bun test
bun run lint

# Submit PR with clear description

Resources & Support

Documentation

  • API Reference: Detailed method documentation
  • Architecture Guides: System design patterns
  • Example Code: Working implementations
  • Video Tutorials: Visual learning resources

Community

  • Discord: #technical-discussion channel
  • GitHub Discussions: Architecture decisions
  • Weekly Office Hours: Live Q&A sessions
  • Code Reviews: Learn from experts

Your Learning Journey

Week 1 Goals

  • Set up development environment
  • Understand core architecture
  • Build your first plugin
  • Deploy a basic agent

Week 2 Goals

  • Implement custom memory system
  • Create multi-agent communication
  • Add comprehensive tests
  • Optimize performance

Week 3 Goals

  • Choose specialization path
  • Build production system
  • Contribute to open source
  • Share your learnings

Ready to Begin?

Start your journey with the Architecture Overview to understand how ElizaOS works under the hood. Then move to Development Setup to prepare your environment.

Remember: The best way to learn is by building. Start with simple plugins and gradually increase complexity as you understand the system better.


Estimated completion time: 40-60 hours of focused learning
Difficulty: Advanced
Outcome: Production-ready AI agent development skills

Welcome to the future of AI development. Let's build something amazing together!