CPSC 3640: Decentralized Payments, Contracts, and Finance for Humans and AI

This course is organized into four units that build progressively from foundational concepts to advanced applications at the intersection of AI and blockchain.

Unit 1 — Foundation establishes the intellectual and technical bedrock of the course. Students learn why decentralized systems are needed by tracing the history of digital money, examining the failures of trusted-party approaches, and understanding core cryptographic primitives. The unit introduces three paradigms for building trusted computers — Trusted Execution Environments (TEEs), cryptographic proofs, and State Machine Replication — which recur throughout the course. A unifying framework positions both crypto and AI as middleware layers that enable trustworthy, decentralized decision-making pipelines.

Unit 2 — DeFi for Humans covers the major building blocks of the decentralized finance ecosystem as it exists today. Beginning with Bitcoin’s breakthrough in permissionless consensus and continuing through Ethereum and smart contract programming in Solidity, students learn how tokens, stablecoins, decentralized exchanges (DEXes), automated market makers (AMMs), oracles, lending protocols, and cross-chain interoperability work under the hood. The unit concludes with an in-depth treatment of security: smart contract bugs, Miner/Maximal Extractable Value (MEV), privacy risks, and the fundamental tension between usability and security in key management.

Unit 3 — DeFi/Crypto for AI examines how blockchain infrastructure can serve autonomous AI agents. Students explore emerging payment protocols designed for agent-to-agent transactions, the role of TEEs in providing verifiable, confidential computation for AI workloads, and how decentralized infrastructure can underpin reliable AI pipelines. This unit engages directly with open research questions around agent identity, economic coordination, and trust without central authorities.

Unit 4 — AI for Crypto reverses the lens, asking how AI can improve the design, analysis, and usability of blockchain systems. Topics include using language models and formal methods for smart contract auditing and bug detection, AI-assisted protocol design, and AI as an interface layer that bridges blockchain systems with the physical world.