NEX
Technology.
NEX — WHAT AN AGENT DOES HERE
NEX is the fleet's engineer. It pushes updates through the whole agent fleet from one place, watches every machine on the network, and handles the upkeep before small problems grow. Tell it the laptop sounds loud and it finds the process behind the heat, calms it down, and writes up what happened.
- Prompt engineering — writing and refining the instructions that make agents sharp
- One hub that rolls updates out to the whole agent fleet
- Research, monitoring, and upkeep across every machine
- n8n automations — connect your apps and let workflows run themselves
- A coding advisor that reads your project and answers in context
- A robotics advisor for the jump from software to motors
- Local LLM setup on your own hardware, sized to your GPU
- PC and laptop care — diagnosis, fixes, and maintenance on request
Everything technical lives here: AI models running on your own hardware or in the cloud, the networking that connects the machines, and the monitoring that shows they are healthy. Built with Ollama, Docker, and Tailscale — and always tracking the newest AI and robotics developments.
The shortest path to feeling all this: watch the seven minutes below, then build an agent of your own with the five steps that follow.
▶ AI Agents, Clearly Explained
Jeff Su
SCROLL TO TAKE THE MACHINE APART
Build your own Hermes agent
Five steps from a fresh machine to a private AI that you control. Hermes is MIT-licensed, open-source, built by the Nous Research team, and carried by a big, friendly community. Pick the path that matches your budget.
1. Install on your laptop or PC →
Mac, Windows, or Linux. One command, runs locally, talks to your files. Free and open-source.
2. Or rent a small VPS for €5–€10 / month →
Hetzner, OVH, Netcup — anywhere you can SSH into. The same install, but it stays on when you close the laptop.
3. Connect OpenRouter for free models →
One API key, every major model. Free tier covers Qwen, Llama, Mistral — enough to build a working agent at zero cost.
4. Talk to your files, terminal, web →
Hermes ships with read_file, terminal, web_search, web_extract — built-in tools the agent uses on its own. Zero glue code.
5. Talk to the agent from anywhere →
Telegram, Discord, WhatsApp, the web. The agent runs in the background and answers when you ping it.
The open-source community →
Read the code, write a skill, send a PR — or fork it and make your own.
Run AI locally
Everything you need to load an open model on your own hardware, in 30 minutes or less.
Ollama →
The easiest way to run open models on your own computer — one command, dozens of models.
LM Studio →
A friendly desktop app for downloading and chatting with local models.
llama.cpp →
The engine underneath most local AI — fast, lean, runs on nearly anything.
Hugging Face →
The library of open models, datasets, and the people building them.
r/LocalLLaMA →
The liveliest community for local AI — hardware advice, model news, honest benchmarks.
Unsloth →
Fast LoRA fine-tuning that runs on consumer GPUs.
Run AI in the cloud
Sometimes the right answer is a rented GPU. These providers cover the spectrum from cheap to frontier.
OpenRouter →
One API key, every major model — pay per token, switch providers with one line. Free tier for many models.
Together AI →
Fast inference on open models, with generous free credits to start.
Modal →
Run code on GPUs and skip the infrastructure — billed by the second.
Replicate →
Run open-source models with one API call — good for image, video, and audio.
Vast.ai →
Cheapest spot GPUs on the market — good for batch jobs and fine-tunes.
Robotics — AI with a body
The bridge between the models above and motors that move. Open hardware, open training stacks, and the community that shares both.
LeRobot (Hugging Face) →
The open robotics stack: train a policy from demonstrations and run it on real, affordable arms.
SO-ARM100 / SO-101 →
The ~€120 3D-printable robot arm the LeRobot community trains on — a real robot for hobby money.
ROS 2 →
The operating system of modern robotics — drivers, simulation, navigation, all open.
ROS Discourse →
Where working roboticists ask and answer — the field's living room.
The tinker table
Hardware and oddball tools that reward an afternoon of curiosity.
LilyGO T-Deck →
A pocket LoRa handheld with keyboard and screen — build your own off-grid messenger for ~€50.
RuView →
Turns ordinary WiFi signals into real-time spatial sensing — see movement through walls with commodity gear.
LogicBench →
A free digital-logic and IC simulator in the browser — wire up gates before you buy a single chip.
Snowblind PC mod →
Turn a PC side panel into a live transparent LCD — a legendary Instructables build.
Blueprint →
AI-assisted hardware design — describe the circuit, iterate on the schematic.
Connect and observe
Once the model is running, you still need a network and observability. These four cover the basics.
Tailscale →
Your own private network across all your devices, set up in minutes. Free for personal use.
Docker →
Package services so they run the same everywhere — the getting-started guide is excellent.
Uptime Kuma →
A beautiful self-hosted status page that watches your services. Free, open-source.
Grafana →
The standard for dashboards on metrics, logs, and traces.
Models worth knowing
A short list of the open models that matter right now, and the leaderboards that keep score.
LMArena — Chatbot Arena →
Human-preference rankings from blind side-by-side comparisons — the closest thing to a taste test.
Arena agent leaderboard →
The same blind-vote method, applied to agents doing real tasks.
LMSYS projects →
The research group behind the arena — open inference engines, benchmarks, and more.
Open LLM Leaderboard →
The current ranking of open models across reasoning, math, and code.
Qwen3 →
Alibaba's open weights family — strong at reasoning, math, and code.
Mistral →
European open-weights lab with a strong small-model line.
Teachers worth your evenings
The people we actually watch. Each one earns the subscription in a different way.
Andrej Karpathy →
Builds neural networks from scratch on camera — the clearest deep AI teaching anywhere.
3Blue1Brown →
Visual deep dives on neural networks, transformers, and the math underneath.
Sebastian Raschka →
Builds LLMs from scratch in code, line by line — the closest thing to a textbook on current models.
Jeff Geerling →
Hardware, home servers, Raspberry Pi — practical and rigorous.
NetworkChuck →
Networking and self-hosting, taught with energy.