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I find LLMs remove all the fun for me. When I build my homelab, I want the satisfaction of knowing that I did it. And the learning gains that only come from doing it manually. I don't mind using an LLM to shortcut areas that are just pure pain with no reward, but I abstain from using it as much as possible. It gives you the illusion that you've accomplished something.


> It gives you the illusion that you've accomplished something.

What’s the goal? If the act of _building_ a homelab is the fun then i agree 100%. If _having_ a reliable homelab that the family can enjoy is the goal, then this doesn’t matter.

For me personally, my focus is on “shipping” something reliable with little fuss. Most of my homelab skills don’t translate to my day job anyway. My homelab has a few docker compose stacks, whereas at work we have an internal platform team that lets me easily deploy a service on K8s. The only overlap here is docker lol. Manually tinkering with ports and firewall rules, using sqlite, backups with rsync, etc…all irrelevant if you’re working with AWS from 9-5.

I guess I’m just pointing out that some people want to build it and move on.


If your sole goal is to have a homelab that self-hosts services, I completely agree. I'm speaking for those who are interested in developing their skills and knowledge, and believe that building something with AI somehow does that.

I'll agree to disagree on it not being applicable. Having fundamental knowledge on topics like networking thru homelabbing have helped me develop my understanding from the ground up. It helps in ways that are not always obvious. But if your goal is purely to be better at your job at work, it is not the most efficient path.


>I don't mind using an LLM to shortcut areas that are just pure pain with no reward...

Enlightenment here comes when you realize others are doing the exact same thing with the exact same justification, and everyone's pain/reward threshold is different. The argument you are making justifies their usage as well as yours.


That may be true. Ultimately, what I'd advise is for people to be cognizant of their goals and whether AI does or does not help to achieve them.


The thing about anything that actually gets used, is what removes the fun the quickest is when it breaks and people who actually want to use it start complaining.

In that case, it's not about the 'joy of creation', but actually getting everything up and running again, in which case LLMs are indispensable.


I don't disagree. All depends on what you're looking to get out of it.


Getting it up and running is fun but I find maintaining some services a pain. For example, Authelia has breaking configuration changes every minor release, and fixing that easily takes 1-X hours every time. I gave up for 4.38 and just tossed the patch notes into NotebookLM.


Definitely. That's a great use case. How do you use NotebookLM? First I'm hearing about it


I've been mostly using it as what I would call a "medium scope search engine". Instead of searching "$topic" or "$topic site:wikipedia.org", I can pick a few dozen links from different sources (wiki, documentation, tax code, papers, videos), toss it in NotebookLM, submit my search query in the form of a question, and look at the linked source. I see it as an evolution of doing research through library books, Internet search, and Wikipedia. I didn't know I wanted something like this until I used NotebookLM this way. It also seems to handle multiple languages reasonably well.


very cool. thanks!


I don’t give them direct access to my computer. I just use them as an alternative to scrolling reddit for answers. Then I take the actions myself.


yeah. I wrote a little about that here: https://fulghum.io/fun2




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