Exactly. The distinction between the various layers in "AI" systems is pretty vague to the newcomer. What is the "model" vs. the engine "running" it vs. weights?

I don't recall any previous tech stack that was barfed onto the scene with so little background or reference material, going from zero to endless undefined jargon... and no primer in sight.

For people who demand an understanding of their tools, it's a lot of work. I recognize the value of "AI" in performing the tasks I'd have to do manually; for example, keeping the data structures of my front- and back-ends in sync in a project. But do I want to interrupt my development and take weeks off to digest all of these tools?

And if I do, I want to run the show and fully understand it. And like you, I think that's best done locally.

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Fr0styMatt88 4 hours ago | parent | next [-]

The most unexpected thing for me was kind of philosophical in a ‘holy shit’ way.

Cloud models still feel ‘magic’, like you send a request off and get something back, like it’s something ‘special’. I used to joke that ChatGPT might be some kind of mechanical turk underneath.

Watching a model run local on your own machine hits different — you realise that yes, it IS just a computer program. Which for me actually makes me appreciate the leap we’ve made MORE, not less. From an information-theoretic point of view, LLMs really are something special.

The fact that they are just programs, that I’ve now experienced first-hand that they’re just programs, makes all those questions around consciousness and intelligence much more interesting.

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dofm 4 hours ago | parent | next [-]

Yep — it hasn't changed how I feel about what LLMs are capable of (and very much not capable of) but this visceral feeling is fascinating.

Like, just watching a computer I already owned act like ChatGPT with the wifi disconnected.

It was the first time I stopped feeling quite so helpless, somehow.

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QuercusMax 4 hours ago | parent | prev [-]

Yeah, it's been fun for me running models (mostly Qwen 3.6 27B) on my 48GB M4 MacBook Pro. When i'm using it to run models, it's basically unusable for anything else - I actually do the work on my Macbook Neo. Took me a while to figure out why the models couldn't figure out how to make tool calls - because LMStudio by default uses a 32K input window, which is smaller than OpenCode's prompt, so half of the instructions were being pruned from the middle!

	▲	dofm 3 hours ago \| parent [-]
		Yes — there is a setting for that isn't there. And as soon as you realise there's a setting for that, you have new knowledge. Qwen barely needs any of Opencode's prompt, in my experience; I think I cut it down to about three general lines I found by googling. Mainly you need only a pre-amble to make sure that the plan mode, plan switch and build mode prompt fragments make sense. Gemma 4 also needs almost nothing at all, which is fascinating, considering it is not a coding-specialist model. It just seems to be who you need it to be when you ask.

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ricardobayes 4 hours ago | parent | prev [-]

For the most part you can just download LM Studio and go from there. It provides a chat interface and an easy-to-use interface to browse, load and use LLM models. The engine: it is abstracted away by LM Studio, if you want to dig deep it's llama.cpp as the runtime. Weights are the files what you download, they are the models for practical purposes.

	▲	dofm 4 hours ago \| parent [-]
		I definitely would recommend LM Studio as a learning environment, because it surfaces a bunch of things in relatively clear-minded ways. I am very grateful for it.