{"id":"sam-green","title":"Sam Green","content":"**Sam Green** is the founder of Cambrian Network, a company focused on building financial data infrastructure for agent-driven and onchain financial systems. His work has centered on the development of agentic finance, AI-enabled trading systems, and the use of [blockchain](https://iq.wiki/wiki/blockchain) data for automated financial decision-making. [\\[1\\]](#cite-id-ox7tD34fC97JjA4v) \n\n## Education\n\nGreen graduated from the University of Central Arkansas in 2009 with a Master’s in Applied Mathematics. He then attended UC Santa Barbara, where he earned his Ph.D. in Computer Science in 2019. [\\[2\\]](#cite-id-0WrVBAAKvHzKO14U) \n\n## Career\n\nGreen began his career as a firmware engineer at ARMA Design from 2009 to 2010, where he developed embedded systems software in C and Assembly, worked with customers on implementation challenges, and contributed to project proposals and technical quotations. In 2010, he joined Sandia National Laboratories as a cryptographic engineer, conducting assessments of cryptographic systems and serving as an instructor for the laboratory’s cryptography training program. He was later promoted to Senior Member of Technical Staff, leading research and development initiatives to evaluate and advance cryptographic security systems while managing technical teams and project delivery.\n\nFrom 2015 to 2018, Green pursued doctoral research at the University of California, Santa Barbara, under the supervision of cryptographer Çetin Kaya Koç. His research focused on methods for improving the efficiency of deep reinforcement learning, and he contributed to the development of the university’s first reinforcement learning course. Following his doctoral work, he returned to Sandia National Laboratories as a Senior Member of Technical Staff in artificial intelligence research and development from 2018 to 2020. During this period, he worked on hardware-aware approaches for improving the power efficiency of neural networks and developed early techniques for distilling reinforcement learning agents.\n\nIn February 2020, Green joined [The Graph](https://iq.wiki/wiki/the-graph) as Core Development Team Lead. Through his work with Semiotic Labs, a core development team within [The Graph](https://iq.wiki/wiki/the-graph), he contributed to the development of network infrastructure, including systems for on-chain payments and data verification. While at [The Graph](https://iq.wiki/wiki/the-graph), he also served as an Entrepreneurial Research Fellow with Activate from 2021 to 2023, supporting the commercialization and development of deep-technology research.\n\nIn November 2024, Green founded Cambrian Network and became its chief executive officer. The company develops infrastructure for [blockchain](https://iq.wiki/wiki/blockchain) data services and systems to support autonomous financial applications. [\\[3\\]](#cite-id-X5yw9pOz063Ew5JB) \n\n## Interviews\n\n### Agentic Finance\n\nIn a May 2026 episode of *The Rollup* podcast, Green discussed the rise of agentic finance and its potential to become a major industry by 2026, driven by autonomous [AI agents](https://iq.wiki/wiki/ai-agents) increasingly used in [DeFi](https://iq.wiki/wiki/defi) for yield optimization, trading, and portfolio management. He described how these systems combine rule-based automation with AI-driven analysis of on-chain and off-chain data, including market signals and sentiment, to make more adaptive financial decisions. Green also outlined Cambrian Network’s role in building financial data infrastructure, focusing on aggregating and structuring on-chain information to support both retail and institutional users. He further explained the company’s development roadmap, which includes phases centered on verifiability, [mainnet](https://iq.wiki/wiki/mainnet) deployment, and longer-term convergence between [crypto](https://iq.wiki/wiki/cryptocurrency) and traditional financial systems through AI-enabled automation. The discussion emphasized the importance of reliable data infrastructure and tooling as the foundation for scalable agent-based financial systems, alongside the broader shift toward more integrated and automated financial markets. [\\[4\\]](#cite-id-3qK3rFglEpzPScRs) \n\n[YOUTUBE@VID](https://youtube.com/watch?v=6IjinlRAg54)\n\n### Reshaping Crypto\n\nIn an April 2026 episode of *The Crypto Beat*, Green joined [Austin Griffith](https://iq.wiki/wiki/austin-griffith) of the [Ethereum Foundation](https://iq.wiki/wiki/ethereum-foundation-ef) to discuss how artificial intelligence is reshaping [crypto](https://iq.wiki/wiki/cryptocurrency) development, trading, and risk management. The conversation focused on the increasing use of AI tools such as GPT, Claude, and Opus in building, auditing, and deploying [smart contracts](https://iq.wiki/wiki/smart-contract), with the panel noting that these systems are beginning to automate work that previously required entire engineering teams. They also discussed the emergence of “agentic finance,” in which [AI-driven agents](https://iq.wiki/wiki/ai-agents) handle trading and portfolio management tasks, evolving from rule-based systems to more adaptive machine learning approaches.\n\nThe discussion further explored how AI is lowering barriers to entry in [crypto](https://iq.wiki/wiki/cryptocurrency) development by reducing costs and enabling individuals or small teams to build complex applications more quickly, potentially accelerating the creation of high-growth companies. They highlighted the parallel rise in both offensive and defensive capabilities, with AI enhancing security threats while also improving defensive tooling and auditing processes. The panel also touched on emerging standards for agent interoperability and payments, as well as the long-term possibility of autonomous AI systems managing [smart contract](https://iq.wiki/wiki/smart-contract) ecosystems end-to-end. Despite acknowledging risks related to security and complexity, they expressed a broadly optimistic view of AI serving as a new interface layer for [crypto](https://iq.wiki/wiki/cryptocurrency), making development more accessible, efficient, and scalable. [\\[5\\]](#cite-id-xRuOjNgTQ25V69DI) \n\n[YOUTUBE@VID](https://youtube.com/watch?v=E6FkjoM2qrE)\n\n## Presentations\n\n### Agentic Revolution\n\nAt Devconnect 2025 in December, Green highlighted that while [crypto](https://iq.wiki/wiki/cryptocurrency) user interfaces were currently problematic, the emergence of [autonomous agents](https://iq.wiki/wiki/ai-agents) would transform the user experience. He explained that agents, defined as programs capable of sensing, thinking, and acting on behalf of users, would address limitations of existing AI models and significantly improve performance through continual doubling of AI capabilities, akin to Moore’s law. Drawing on historical revolutions—from the industrial revolution to the information age—Green emphasized that the upcoming agentic revolution would surpass previous transformative eras in its impact on productivity. He focused in particular on its implications for finance, especially [crypto](https://iq.wiki/wiki/cryptocurrency) and [blockchain](https://iq.wiki/wiki/blockchain) systems, where programmable money would enable agents to autonomously manage assets, execute trades, allocate liquidity, and optimize lending protocols. Green showcased the rapid growth of agentic finance, with assets under management soaring from near-zero to over $500 million within a year, and outlined project categories including prediction, trading, information analysis, liquidity provisioning, and lending agents. He stressed the importance of financial intelligence for agents to discover opportunities efficiently and predicted that [stablecoins](https://iq.wiki/wiki/stablecoin) and [DeFi](https://iq.wiki/wiki/defi) would be the initial gateways to mass adoption, ultimately leading to a future in which [autonomous agents](https://iq.wiki/wiki/ai-agents) would make financial decisions seamlessly and securely, revolutionizing the entire financial ecosystem. [\\[6\\]](#cite-id-p3WXHHVVn1pPYSkp) \n\n[YOUTUBE@VID](https://youtube.com/watch?v=Uccf3wmKTO4)\n\n### DeFi Agents\n\nAt [ETHDenver](https://iq.wiki/wiki/ethdenver) in February 2025, Green discussed reinforcement learning (RL) and its potential to revolutionize [decentralized finance (DeFi)](https://iq.wiki/wiki/defi) by enabling agents to learn and adapt through trial and error. Drawing on his academic background in cryptography and RL, he explained how RL models animal learning and can operate in both simulation and real-world environments to optimize decision-making. Green highlighted RL's capability to teach agents behaviors surpassing human proficiency, exemplified by robots riding bicycles or AI self-correcting during training. He emphasized RL’s suitability for long-term strategic problems such as trading, portfolio management, market making, arbitrage, and [yield farming](https://iq.wiki/wiki/yield-farming), particularly its adaptability to shifting markets and complex sequential decision-making. Despite early-stage adoption and challenges such as delayed rewards, explainability issues, and regulatory risks, Green noted that major financial institutions and emerging [DeFi](https://iq.wiki/wiki/defi) projects are experimenting with RL to improve efficiency, risk management, and profitability. Overall, he believed that builders interested in finance have significant opportunities to innovate with RL, especially given the early nature of its applications in [DeFi](https://iq.wiki/wiki/defi). [\\[7\\]](#cite-id-FeQA62dPk4ZYTskd) \n\n[YOUTUBE@VID](https://youtube.com/watch?v=IlvQk5QSS-8)","summary":"Founder of Cambrian Network and AI finance innovator, Sam Green specializes in agent-driven, AI-enabled, and onchain finance solutions. 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