What runs where, and who may start it
The question is no longer “ChatGPT, yes or no”. The question is what runs where and who may start it. Local and in-house AI is growing alongside the cloud: a Mac mini handles inference, open weights keep closing the gap, and agents are the product of the year and the risk of the year. This series takes you from your first local model to a control room you run the whole thing from — and to the rules without which it all falls apart.
45 parts · six tracks · more coming
Read it front to back like a course, or jump around by tag. If in doubt, start with the first part of each track — they assume you have installed nothing yet.
Prefer a fixed order to a signpost? Follow the path An agent on your NAS from scratch (13 steps).
01 · 5×
Model, harness, agent — and why the question moved from “AI yes or no” to “what runs where”.
02 · 5×
Two complete setups from hardware to invoice: what runs where, what it costs and why it is put together this way.
03 · 5×
Your first model on your own machine: Mac mini, Windows with an Nvidia card, memory, and when local is enough.
04 · 6×
One gateway in front of every model, API keys in one place, and routing each job to what handles it best.
05 · 8×
A control room in your pocket: Telegram as the panel, a safe route home, and a queue you approve yourself.
06 · 8×
Files from your disk into the chat: how it really works, what RAG is, what MCP does, what stays off the cloud.
07 · 8×
Agents are the product of the year and the risk of the year. One page of rules and the case studies behind them.
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12 parts tagged “Control” · Clear filter
Five accounts, three subscriptions, every model in a different tab and the files still sitting on disk. This part is the map of the whole series: what a control room is, which four layers it consists of and in what order to build it.
Most of this series assumes a box that runs at home around the clock. If you don't have one and don't want one, you can get a large share of the benefit from the app alone. An honest comparison: what works without a server, what doesn't, and how to decide.
The second setup adds one thing: a machine that's always on. That opens up work that gets done without you — nightly batches, website monitoring, a morning summary to Telegram. And it adds one obligation the gaming PC didn't have.
You type a message on your phone, your model at home works it out, and the answer comes back into the chat. A complete guide: creating the bot, where the token belongs, how to allow only yourself, and the fifty lines of code that tie it all together.
Forwarding a port on your router is the fastest way to hand your model to the entire internet. A private network makes it available only to your devices and takes ten minutes to set up — no public IP, no certificates, no holes in the firewall.
Three devices, three different roles and one shared memory. How to divide up what gets done where, so that work in progress does not get left on the machine that happens to be shut in your backpack.
The difference between a useful agent and a dangerous one is not in the model but in a single line: where preparation ends and action begins. How to draw that line so that it holds — with a folder, a queue and one button on your phone.
Your NAS now runs an agent that reads your messages. That turns a box for photos into a machine worth locking properly. A concrete procedure for DSM: Tailscale, what to switch off, the two scheduled tasks people forget, and a test you can trust.
Ten scheduled tasks mean ten messages you'll stop reading within a week. How to fold them into a single overview that takes a minute to read, what doesn't belong in it, and how to tell it's time to cut it down.
The best ideas arrive when your hands are not free. A voice message in Telegram, a transcript, a reply by voice or text. A four-line setup, a free option and three situations where voice is the wrong tool.
The morning brief did not arrive. The agent does not react to a message. Before you start reinstalling, go through six questions in order from the most common cause to the rarest. With the commands that answer them.
In the first month you add things. By the third you have twenty tasks, read three and pay for the rest out of habit. A one-hour audit with four questions for every task, a table to fill in, and five patterns that tell you which task won't survive.
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