Investor at CoinFund
Check size: No personal check range is disclosed. CoinFund's live profile explicitly says there are no investments led by Jonathan yet, while crediting him with establishing vault and new-markets theses and contributing to Irys research; do not present him as an independently proven deal lead.
Jonathan studies how better on-chain financial and data rails enable agents, vaults and new markets. His thesis work connects composable financial infrastructure to automated commerce, and programmable storage to verifiable AI training, licensing and intellectual-property workflows. His restructuring experience on Voyager and BlockFi also gives him a failure-oriented view of custody, leverage and financial architecture.
Email or X DM are listed as preferred. Explain the non-obvious market thesis, the programmable primitive, and why it enables a new agent or financial behavior. Include architecture, cost comparisons, custody and failure modes, developer workflow, early demand and how the product earns durable control of a transaction or data layer.
CoinFund says he seeks contrarian founders taking big swings and cares about beating banks and building better financial rails for agents. His research suggests interest in cheaper, developer-friendly primitives that make data or capital programmable and support applications impossible on opaque centralized storage or fragmented legacy finance.
Inferred from his background and writing: consensus ideas without a contrarian wedge, vaults or financial products whose risks are obscured, data infrastructure that is cheap but not programmable or verifiable, and agentic products without purpose-built transaction rails. This is not a published pass list.
Identify the agent or participant, the transaction they cannot complete efficiently today, and whether a new on-chain rail improves settlement, programmability, access or risk.
Compare storage cost, permanence, mutability, on-chain readability, computation, verification and incentive alignment instead of reducing infrastructure choice to price per byte.
Stress custody, leverage, liquidity, bankruptcy remoteness and user claims using lessons from failed intermediaries before evaluating growth or yield.
A programmable datachain can bridge the gap between expensive smart-contract storage and cheap opaque blobs, enabling low-cost computation, verifiable AI and programmable rights on stored data.
Ethereum's long-term roadmap requires solving short-term fragmentation and alignment, while DeSci and AI agents are emerging as credible areas for builders beyond market-price enthusiasm.