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关于人工智能的争论映射了启蒙运动从未解决的一个问题。卢梭说工具腐蚀了我们。孔多塞说他们完善了我们。尼采说,两人都没有抓住重点。技术是对品格的考验,唯一诚实的答案就是你在遭遇中变成什么样子。
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Mark Hendrickson
I'm building Neotoma, a deterministic state layer for long-running agents. The core problem: agents are increasingly stateful, handling tasks, contacts, transactions, and commitments over time, but their memory is built for retrieval, not truth. It drifts between sessions, overwrites without history, and cannot be traced or replayed. Neotoma treats memory as state evolution: every observation is versioned, every entity snapshot is reproducible, every decision can be replayed. Schema-bound, local-first, cross-platform via MCP, and entirely user-controlled.
The principle underneath is the same one that's driven all of my work: people should control their own data, memory, money, and digital infrastructure, not cede it to platforms that optimize for engagement over truth.
I work as a solo founder in Barcelona, operating with AI agents as a team rather than as tools. Every workflow, email, finance, content, and product, runs through a shared repo and source of truth. The agents follow the same playbook I do. That only works because the state layer is explicit and inspectable, which is exactly the contract Neotoma is designed to provide.
Before this chapter, I spent nearly two decades building products across consumer web, crypto, and startups: writing and shipping at TechCrunch, co-founding Plancast (acquired by Active Network), co-founding KITE Solutions, advising and building with early-stage startups, leading user experience at Hiro for the Stacks blockchain, and running Leather at Trust Machines. You can see the full arc on my timeline.