Event-Sourced Runtimes for Evolving AI Agents

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    Video summary

    Yohei Nakajima describes ActiveGraph as a runtime rather than a conventional agent harness. An immutable typed event log projects shared graph state; deterministic or model-driven behaviors respond to changes and communicate through that state.

    Yohei Nakajima explains policies, selected context views and modular packs of schemas, tools and behaviors. Proposed changes can be gated by tests and human review, while logs preserve progress and allow experiments to resume after interruptions.

    Yohei Nakajima discusses memory, coding and game experiments that track unsuccessful trials as well as accepted changes. Reported results remain his experimental account, and the closing analogy between experiential memory and a world model is a hypothesis, not an established neuroscience finding.

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    Yohei Nakajima beside the blue-and-white headline RECORD EVERY CHANGE on a black background. Framed in blue with WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 22 July 2026 and duration 17m 34s.

    Yohei Nakajima presents an experimental event-sourced runtime that records agent actions and changes while constraining self-improvement.