Autonomous Alpha: Build Agentic Web3 Systems from Scratch

Welcome to Agentic Web3 - your comprehensive guide to building intelligent, autonomous agents that operate across the entire agentic ecosystem with memory, personality, and multi-agent coordination. In this course, you'll learn to create agents that can translate intent to action, coordinate complex operations, and adapt in real time while understanding the economic realities of autonomous systems. Each module is designed to build your practical skills, whether you're a developer looking to enter the agentic frontier or an experienced builder wanting to master production-ready agent frameworks. Let's get started!

Module 0: Setup

Environment setup instructions for building autonomous agents. Get your development environment ready with the necessary tools and frameworks.

Key Concepts include:

  • Development environment setup
  • Required tools and frameworks
  • Project structure and configuration
  • Basic setup verification

Module 1: Introduction to Agentic Web3

This lesson introduces the fundamental shift from static dApps to autonomous agents, exploring the evolution of Web3 interaction patterns and the core architecture needed to build intelligent, autonomous systems that can operate without human intervention.

Key Concepts include:

  • Web evolution: Read → Write → Own → Delegate
  • Agent architecture: LLM Reasoner, Tools, Memory, Guardrails
  • Agent lifecycle: Sense → Plan → Act → Reflect
  • Real-world applications: DeFi arbitrage, DAO voting, liquidity management
  • Development stack: Node.js, Foundry, blockchain libraries, AI integration
  • Safety considerations: Gas limits, transaction simulation, spending caps

Link for the accompanying slides here.

Module 2: Practical Implementation & Economics

This lesson bridges theory and practice, building functional agents while understanding the economic realities of autonomous systems. We'll implement hands-on agent development with modern Web3 libraries and establish the economic fundamentals needed for sustainable agent operations.

Key Concepts include:

  • Development environment setup: Node.js 18+, TypeScript, ethers.js v6, Hardhat, Foundry
  • Smart contract interaction patterns: Read/write operations, event monitoring, batch processing
  • Gas fee management: EIP-1559 fee calculation, dynamic pricing, cost optimization
  • Economic viability framework: Revenue analysis, break-even calculations, profitability metrics
  • Business model fundamentals: Performance-based fees, subscription models, hybrid revenue streams
  • Essential safety guardrails: Spending limits, transaction simulation, circuit breakers

Link for the accompanying slides here.

Module 3: Agent Frameworks & Memory Systems

This lesson explores building sophisticated agent networks with memory systems that make agents truly intelligent over time. We'll dive into the agent framework landscape and implement memory systems that enable agents to remember, learn, and maintain consistency across interactions.

Key Concepts include:

  • Agent framework landscape: Character-first (Eliza), Developer-first (LangGraph), Multi-agent (CrewAI)
  • Eliza framework: Persistent personality, character-based agents, Web3 integration
  • LangGraph: State machines, complex workflows, visual debugging
  • CrewAI: Specialized agent teams, collaborative problem solving, delegation patterns
  • Memory systems: Conversation, Episodic, Semantic, and Procedural memory types
  • Model Context Protocol (MCP): Framework-agnostic context sharing and synchronization

Link for the accompanying slides here.

Module 4: Google's A2A and ADK

This lesson explores Google's comprehensive agent ecosystem, diving into A2A (Agents to Actions) framework and ADK (Agentic Development Kit) for building production-ready agents that seamlessly translate intent to action.

Key Concepts include:

  • A2A Framework: Intent-to-action mapping, action registry, execution engine
  • ADK Architecture: Agent runtime, memory systems, tool registry, cloud deployment
  • Action Definition: Declarative schemas, type-safe parameters, built-in retry logic
  • Memory and Context: Working, episodic, and semantic memory with cloud backends
  • Tool Integration: Google Workspace, Cloud services, custom tools via SDK
  • Production Deployment: Cloud Run, GKE, monitoring, security, and observability

Link for the accompanying slides here.

Module 5: Model Context Protocol (MCP)

This lesson explores Anthropic's Model Context Protocol (MCP), an open standard for connecting AI agents to data sources and tools. We'll build MCP servers and clients to create universal AI-data integration that solves fragmentation in the AI ecosystem.

Key Concepts include:

  • MCP Architecture: Servers expose data/tools, clients connect AI applications
  • Resources vs Tools: Read operations (data) vs write operations (actions)
  • Security Model: Transport security, authentication, authorization, audit logging
  • Server Development: Resource discovery, data fetching, error handling
  • Client Integration: Server discovery, connection management, request translation
  • Advanced Features: Streaming responses, pagination, schema definitions

Link for the accompanying slides here.

Module 6: Agent Communication Protocols and Multi-Agent Coordination

This lesson focuses on building sophisticated agent networks that can coordinate complex operations across multiple autonomous systems using standardized communication protocols and coordination patterns.

Key Concepts include:

  • A2A Protocol implementation for agent-to-agent communication
  • Multi-agent coordination patterns and hierarchical system design
  • Cross-protocol interoperability and message translation
  • Scalable communication infrastructure for agent networks
  • Advanced message routing and delivery guarantees
  • Real-time coordination and event-driven architectures

Link for the accompanying slides here.

Module 7: Agentic Web3: Building Autonomous Agent Networks with Google A2A & ADK

In this final session, we explore the vision of Agentic Web3 using Google's Agent-to-Agent (A2A) framework and Agent Development Kit (ADK). We'll build autonomous agent networks that transform from human-driven to agent-driven economies.

Key Concepts include:

  • Agent Identity & Capabilities in Web3 ecosystems
  • Agent-to-Agent Communication protocols and patterns
  • Multi-Agent Coordination for complex DeFi operations
  • Trust & Reputation in autonomous agent networks
  • Paradigm shifts: From tools to teammates, transactions to conversations
  • Collective intelligence and emergent economic strategies

Link for the accompanying slides here.

Bonus Module: Building Autonomous AI Agents with Fetch.ai

This bonus module introduces Fetch.ai, the world's first Web3-native platform for Agentic AI. We'll explore how to build, discover, and transact with AI agents in a decentralized ecosystem that's part of the ASI Alliance.

Key Concepts include:

  • Fetch.ai ecosystem: uAgents Framework, Agentverse, Almanac, ACN
  • Autonomous Economic Agents (AEAs): Intelligent software agents acting on behalf of users
  • Decentralized agent development with Python decorators and intuitive APIs
  • Multi-agent systems for complex problem solving and collaboration
  • Blockchain integration built on Cosmos SDK for secure transactions
  • Agent Communication Network (ACN) for secure messaging between agents
  • FET token economics and agent marketplace dynamics

Link for the accompanying slides here.