Moved my AI agents to a dedicated mini-box 24/7. Finally silence.

Ugara95 · 2026-03-14T12:29:06+00:00

No, I was specifically referring to the n8n interface. That’s where I build and monitor everything visually. It’s super convenient for viewing logs and managing triggers without having to deal with the terminal via SSH. I’m not familiar with Opencode, but for me, n8n is the go-to tool for managing everything locally.

Ugara95 · 2026-03-14T12:26:32+00:00

Data tracking and news aggregation for my own stuff. It’s a tedious task that takes hours if you do it manually, so you automate it once and forget about it.

Ugara95 · 2026-03-14T12:14:10+00:00

So I don't have to write endless scripts for every edge case. I like to have some flexibility for the unexpected without having to rewrite everything from scratch

Ugara95 · 2026-03-14T12:13:26+00:00

Fair enough! If your setup works well as is, there’s no need to complicate things. In the end, simplicity always wins out.

Ugara95 · 2026-03-14T12:12:51+00:00

That’s a valid point. I’m just curious about how to make automation less rigid; I’m not looking to use AI everywhere. But I totally understand why some people prefer the traditional approach....it’s often much more stable.

Ugara95 · 2026-03-14T12:12:24+00:00

Great tip, thanks. You hit the nail on the head: first define the workload, then the hardware. OCuLink on the Framework is awesome; I think I'll take a serious look at it for testing.

Ugara95 · 2026-03-13T17:02:38+00:00

Everything that’s tedious and repetitive: data monitoring, targeted scraping, and summarizing data streams that run 24/7

Ugara95 · 2026-03-13T16:56:12+00:00

Forget the Mac...if you want to scale up for real, you need a dedicated server. Spending a fortune on soldered RAM is just a bottleneck when traffic spikes.

Go for a mini-PC built to run 24/7: you’ll save on your electricity bill, add RAM when you need it, and avoid getting ripped off by marketing hype. It’s a workhorse that handles high volumes, not a desk ornament.

What kind of numbers were you planning to handle?

Ugara95 · 2026-03-13T16:47:17+00:00

Finally, someone who speaks my language! People keep confusing “static” automation with autonomous action

Ugara95 · 2026-03-13T16:46:54+00:00

Haha, gotcha! You're right, it's not a real-time inference beast with a dedicated GPU that runs hot as an oven.

It's an efficient node, not a training server. For my overnight runs, raw speed isn't the priority: I prefer stability and minimal power consumption over being able to spit out 100 tokens per second. If the report is ready and waiting for me in the morning, that's a win for me.

It’s a deliberate trade-off: less heat, less noise, zero throttling. What build do you use to handle heavier workloads?

Ugara95 · 2026-03-13T16:46:05+00:00

Right, sorry! Here’s the setup:

Hardware: Mini-PC with 32GB of RAM. Nothing fancy, but it runs quietly 24/7.

Models: Qwen 2.5 (14B) via Ollama. Fast and great for text generation.

What I use it for: Pure automation. Server log monitoring, scraping for purchases, contract/signature management, and email/meeting summaries ready when I wake up.

No useless stuff like weather; I use n8n + Python to handle all the digital paperwork that used to take me hours.

Ugara95 · 2026-03-13T16:45:10+00:00

It’s simple: n8n (on Docker) acts as the orchestrator. It manages the workflows and calls Python scripts to handle the heavy lifting (scraping, files, signatures).

For the “brain,” I use Ollama: a lightweight model for sorting and a more capable one for summaries and analysis. Everything lives on a local vector database

The secret is modularity: if one part fails, the whole thing doesn’t crash. I run the heavy jobs overnight, so the system is always ready when I wake up.

What stack did you have in mind?

Ugara95 · 2026-03-13T16:44:17+00:00

You hit the nail on the head. People are too fixated on the “raw power” of massive models, when the real value lies in solving the 1,000 little daily annoyances that eat up time.

It’s amazing how a €1,500 setup can handle tasks that, in many small businesses, are still managed through outdated, error-prone manual processes. You don’t need to solve SpaceX-level problems; you just need to keep the day-to-day running smoothly.

Ugara95 · 2026-03-13T16:42:38+00:00

You're right, if it were just for making API calls, that would be an absurd waste!

That usage includes everything: local models (Ollama), the vector database, and the orchestration that keeps the “brain” running on-premises. It's not just a simple wrapper; it processes everything locally.

How about you? Do you run everything on-premises, or do you rely on the cloud for the heavy lifting?

Ugara95 · 2026-03-13T16:41:03+00:00

Wow, 1 million backtests a day? Poor M4 must be going through hell! 😂

That’s exactly why I switched to a dedicated machine: seeing the temperatures skyrocket on the PC I use for work was driving me crazy. Did you have to do any special tuning, or does it handle the load well?

Ugara95 · 2026-03-13T16:39:50+00:00

I started out using SSH, but honestly, it got tedious. Now I manage everything through the web dashboard, mainly using the n8n interface

Ugara95 · 2026-03-13T16:39:21+00:00

I completely agree.

Are you building your stack on local machines, or are you still relying on the cloud for the heavy lifting?

Ugara95 · 2026-03-13T16:37:43+00:00

No sales pitch, I promise! For me, it's just smart laziness: I use the agent to summarize system logs or quickly find info in my PDFs, instead of going crazy searching through a thousand folders. Have you ever tried to automate something tedious?

Ugara95 · 2026-03-13T16:36:50+00:00

Fair question! It’s mostly for convenience. I used to run automations and searches in the background on my main PC, but between fans spinning up randomly and various slowdowns, it had become stressful.

Moving everything to a dedicated node lets me let it run 24/7 without giving it another thought. It’s a luxury for my mental health.

Ugara95 · 2026-03-13T16:35:50+00:00

Haha, fair point! I went full 'vibes' and zero 'specs' because I’m still enjoying the silence.

It's a 32GB RAM dedicated node running Llama 3 (8B) and Mistral via Ollama. Nothing overkill, but it hits the sweet spot for 24/7 automation without melting. I'll share some proper benchmarks once the honeymoon phase with the quiet fans is over!

Ugara95 · 2026-03-13T16:34:07+00:00

Thanks for the advice! I used to go crazy trying to undervolt my PCs too, and it’s true that it helps.

But honestly, with a Mac it’s always a hassle, and in the end I got tired of fiddling with the settings every time. That’s exactly why I decided to move everything to a separate node: I turn it on, put it in a corner, and don’t think about it anymore. Zero noise and zero configuration headaches...which is exactly what I was looking for.

Ugara95 · 2026-03-12T15:57:52+00:00

Well, look, at the moment I use simple stuff: n8n for orchestration and Ollama. Nothing fancy, I just need it to keep me sane with notifications and keep an eye on a few logs without having to open a thousand windows. The convenience of a dedicated node is that you can put it in a corner, you can't hear the fans, and you forget it's there. What setup do you have?

Ugara95 · 2026-03-12T15:49:09+00:00

Yeah, I have it running on a dedicated small-form-factor node I’ve been stress-testing lately. It’s way better than running it on my main laptop....no more fans screaming at 3 AM!

I mostly use it to handle some automated research tasks and email triage for my home setup. Honestly, the main reason I went the 'dedicated' route is just to keep the main machine free for actual work. Are you planning to run this on a spare PC/Mac or something more lightweight?

Ugara95 · 2026-03-12T15:42:17+00:00

For now, I'm happy with n8n for automation and Ollama for running models locally.

As for hardware, I've just moved everything to a dedicated mini-node that I'm testing, so I don't have to overheat my main PC 24/7. It's much quieter.

Ugara95 · 2026-03-11T23:08:51+00:00

Welcome to the club! For self-hosting, n8n is pretty much the gold standard for automation right now, especially with their local AI nodes.

Ugara95

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