a memory library for AI Agents :)
open source and hosted!
nice, what's your approach? Graphs?
Readit Newsthis is going straight into my funny folder
Is it just me, or does it seem to be temporarily down?
It won't load for me right now
This blog post isn't human speech, it's typical AI slop. (heh, sorry.)
Way too verbose to get the point across, excessive usage of un/ordered bullets, em dashes, "what i reported / what coinbase got wrong", it all reeks of slop.
Once you notice these micro-patterns, you can't unsee them.
Would you like me to create a cheat sheet for you with these tell tale signs so you have it for future reference?
Hello, would you add something to this list? I think it's pretty good
> Over‑polished prose – flawless grammar, overly formal tone, and excessive wordiness.
> Repetitive buzzwords – phrases like “delve into,” “navigate,” “vibrant,” “comprehensive,” etc.
> Lack of perspective shifts – AI usually sticks to a single narrative voice; humans naturally mix first, second, and third person.
> Excessive em‑dashes – AI tends to over‑use them, breaking flow.
> Anodyne, neutral stance – AI avoids strong opinions, trying to please every reader.
> Human writing often contains minor errors, idiosyncratic punctuation, and a more nuanced, opinionated voice.
> It's not just x, it's y
You do realize that chatgpt has a very recognizable and irritating style, right?
Hello, I am interested in this topic. What would you say were the tale tale signs of AI generated text for you? Apart from:
- excessive em-dashes
- useless words, verbosity
There would't be a problem if there was transparency and clear boundaries. The future is simply enjoying what you want, but we have to get there past these first steps.
Kimi K2 Thinking, MiniMax M2 Interleaved Thinking: open models are reaching, or have reached, frontier territory. We now have GPT and Claude Sonnet capable at home, as they are open-weight. Around this time last year, we had the DeepSeek moment, Now is the time for another moment.
Benchmarks show that open models are equal to SOTA closed ones but own experience and real world use shows the opposite. And I really wish they were closer, I run GPT-OSS 120b as a daily driver
casual workstation flex to kick off the blog
Also, getting into the guts of how agents work and messing around with the knobs and levers is super interesting and where the real differentiating skills are
Built on ADK, CUE, and Dagger
https://github.com/hofstadter-io/hof/tree/_next/lib/agent
(my swiss army knife for dev work, getting a rename soon(tm))