community @NousResearch · ex @KPMG
by day seven you will have an agent that knows how you work, has skills of its own, answers from your phone, runs one job on a schedule and keeps its own files tidy. one outcome a day, about twenty
a few days ago I asked what was hardest to figure out right after your first launch of Hermes Agent. 100+ replies later, the same questions kept surfacing, so we gathered all of them, added the 20 we
in Flightplan #1 I stood up an always-on agent on a box I had to keep alive myself, a cheap VPS or the Mac Mini on my desk, and the fiddly part was the box. the hardening, the tmux session, the
you want an AI agent you can message from your phone, one that kept running after you close the laptop and come back on its own after a reboot? Hermes Agent does this: it runs as a gateway you talk to
most fine-tuning tutorials show you a clean run: install a library, point it at a dataset, watch the loss drop, ship. mine didn't go like that. the first time I measured my model, it had apparently
M3 launched yesterday. the benchmark table looks great and not a single number on it has been independently checked, because there has not been time. so instead of retyping MiniMax's slide, I gave it
I have written two guides on running local LLMs on consumer hardware. part 1 covered the concepts and a working setup from zero. part 2 was the full flag reference and the tuning method. both of them
this is part 2 of my local LLM setup guide. part 1 covered the concepts and a working setup from zero. this one is the reference: every flag, what it actually controls, when to change the default, and
most people think you need a cloud subscription or a $2,000 GPU to run AI locally. you don't. I've been running 20 billion parameter models on an RTX 4060 Ti, an 8 GB card, and getting genuinely
a MiniMax engineer published an internal post-mortem that I think every LLM practitioner should read. the case: ask the model who leads TNT (the C-pop group), and it correctly answers "Ma Jiaqi." ask
this morning I tore out half my AI agent and rebuilt it almost completely. deleted 17 skills, archived 3 months of researches and pointed the entire system at a single mission: learn everything about
there are 450+ repos tagged "agent-memory" on github and 460+ tagged "context-management." me and my agentic best friends went through them. what I expected to find: 40 tools doing roughly the same
