having an event stream like activegraph is the base of how we move to next level and that will probably be composition, which can let you ac…

having an event stream like activegraph is the base of how we move to next level and that will probably be composition, which can let you achieve better results with smaller models. - get the core event stream - wrap things in a nice monad - now you compose the models: > main runner's stream > add on a validator agent that checks specific user interaction and changes/obfuscates data > parallelized tasks that run multiple agents at same time > classifiers, mappers, tinkerers, translators and some can be SOTA models, some can be super fast models, some can be local mini models. and this way you can build highly complex and observable pipelines, "swarms" or "brains" for whatever you need. much more solid, reproducible and observable than your generic imperative orchestration. 🆕 ActiveGraph: The Log is the Agent my talk from AI Engineer is live!!! 😆 https://www.youtube.com/watch?v=khVX_BUnEwU it's about @activegraphai, an event-sourced graph runtime for building durable long-running agents: - what it is - code examples - experiments - benefits & surp…

Related

• The Log is the Agent 它的核心观点是：不要把日志当成 agent 的副产品，而要把 append-only event log 当成 agent 本身。 在 ActiveGraph 里，目标、规则、工具调用、LLM 响应、产物和关系都写入同一条事件日志；当前状…
• I’ll be in room 2005 (graph track) at 11:10am to talk about ActiveGraph: event-sourced graph runtime for building auditable agents! Been hav…
• and here's what a coding agent on activegraph looks like basically you always get a trace and a graph automatically
• ActiveGraph makes the agent trace the runtime: Yohei Nakajima's open-source Python runtime treats an append-only event log as the source of …
• two fun surprises from using activegraph: - the coding agent i was using would query the trace db to debug instead of looking at the logs li…

Source: Yohei Nakajima (X) | 2026-07-24