Yohei

for ActiveGraph, i'm using Cofounder by @intelligenceco as my... cofounder I'm working on the repo, doing research. Cofounder built the website, manages newsletter/blog, and when I do a new blog or have something new to share, I just ping it saying "here's a link/content, can you draft an email and share it with our mailing list?"

ran my first benchmark this weekend (longmemeval) mostly to test activegraph, learned a lot! - this is a stepping stone to show the event based agent system works. the AI convinced me not to start with graph extraction of facts/entities - learned running benchmarks takes a long time - understand more what a good benchmark vs bad benchmark is (I think this is pretty thorough) - fully reproducible open source repo and tests - seems like ActiveGraph is well suited for this, performed solid, which is a good start

quick summary of someone's github, cool! here's me

so many experiments I want to run… 😵‍💫

had to do something while my agents were keeping busy

last night i got an agent to fork itself, propose a modification to itself on the fork, run through tests (sandbox, etc), and only accept the change into itself after the tests passed

oh even better, since you can test the runtime without an LLM, you can post this into Claude: “look up http://activegraph.ai, install and run a small experiment I would like leveraging this, and explain what happened to me with a visual site”

it’s the weekend! if you want to try playing w ActiveGraph, just point your AI to http://docs.activegraph.ai and ask it build something :)

these guys built a research agent with activegraph (using their @monid_ai tool) and found that every claim was traced to a source - which is not prompted, but natively baked in to the approach (they also told me they got this working in ~30 min, yay)

babyagi has ~200 citations, but 0 papers... i just published my first paper on arXiv 😆 "The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems" https://t.co/c7mbRggdCh the case for agents that coordinate through persistent replayable state — no conversation loops, no workflows, no A2A — with auditability, forking, and causal lineage built in. check it out and let me know what you think!

in case anyone is confused like i was, the acquisition did go through, and the order was made to wind that back manus needs to raise and buy back, or it will likely go into some divesture process which means the VCs who were in manus do not have to return the capital they got from the acquisition (plz correct if i’m wrong here)

Healthspan just launched BioAge+, a biological age score that breaks down which systems are driving it and why kind of like a context graph for your health

we've been building agents around the llm, starting with conversations, adding tools, giving rules, logging everything, and storing a form of it as retrievable state Active Graphs flips this. what if we treated the logs as the agent, which include rules provided (and changed), tools given/used, and conversations. behaviors (including llm calls) sit on top of this, react to changes, and then create changes back into the state. this is more like how we work. we don't have workflows, just a whole bunch of rule based behaviors that sometimes chain. we are also not defined by our reasoning capability, but by our beliefs and experiences that shaped them.

if this works, will be great for self-improving agents because of the ability to fork and diff agent runs

this was not on my bingo card

what if we mapped older distributed systems patterns (like actor models or reactive, state-driven blackboards) to LLM agents?

I didn’t really understand what people meant by stateful agents so I started exploring my current take is that we’re not there yet, which led to an interesting experiment…

flymyai is a simple cloud agent with tons of APIs/models baked in under one api key once you have that working, you can drop that into something like lovable