Works especially well for transient/hard to repro bugs. It’ll either set breakpoints or write a monitoring script, go to sleep, get woken up by the harness when the bug trips, inspect state, put together a new build based on a hypothesis built from the debugging, flash it, and loop. I’ve had sessions run completely autonomously for over a day and come with a beautiful one-line solution to a gnarly race condition.

In that regard it’s like a human: you can read code all day if you want and you might get somewhere, but being able to inspect what happened, build a new theory, test it, and iterate is way more powerful 99% of the time.

One of the things I intend on doing with it is cutting router templates for parts that I need to make a bunch of with "identical" dimensions. Get it as close as I can with the table saw and miter saw, stick the template to it, and use a flush-cut bit to clean up my slop.

It's a fun tool in its own right, I really get a kick out of designing and cutting tab-and-slot designs. They just fit together so beautifully right off the laser. I get the joy of designing the project and assembling the project without the swearing/frustration bit in the middle.

This doesn't work great for what the previous poster is asking about, where something needs to fit into a specific space (the comment about scribing a face frame is mint though), but what I typically look for when I'm building things, whether wood, metal, 3D printed, etc, is to try to find the critical faces and let everything shake out around that.

For example, in the side-mount-slide drawer box situation, you've nailed it: the spacing between the exterior face of the drawer and the interior face of the carcass is critical. What I personally would do for that situation would be something like:

- cut rear carcass rails and drawer front and backs precisely with exactly the right spacing, and probably a few temporary front carcass rails that won't be part of the finished product but can be clamped in place for lay-up

- the drawer sides and front/back get dowels that are drilled referenced to the outer edge of the drawer front/back and outside face of the drawer sides

- a slightly oversized dado in the drawer front/back/sides so that the bottom doesn't need to be made as precisely. It can still fit snug in the slot, but if it's a little oversized or undersized relative to nominal, it's not the end of the world

I think this is where it becomes a question of whether it’s an ideological rejection of LLMs or a technical/practical rejection of LLMs.

A project that is rejecting contributions where LLMs are used purely because of the “we can’t handle the amount of newbie generated inbound slop” would, in theory at least, have minimal issue where the contribution is, in fact, indistinguishable from human-only contribution. “This person has put together a solid clean patch that solves a real problem” sounds like a great kind of contributor to have.

On the other hand, a project that rejects LLM-assisted patches because of ideology or social or environmental concerns might actually hate a contributor like this even more than a random drive-by slop contributor.

I don’t have a good solution to their slop problem, but I also don’t have a good solution to their overall bandwidth problem. I like QGIS better than any other GIS software I’ve had the misfortune of using, and at the same time brace myself a little bit every time I open it up because there’s a solid chance I’m going to have encounter another weird quirk or awkward workflow that I haven’t figured out The Trick for…

> While I don't know if AI is conscious, I'm sure it has an internal world. Isn't that what a latent space literally is? LLMs operate in a high-dimensional space that can be analysed and translated to very abstract, high level concepts, behavioural tendencies, even things recognisable as emotions.

From your comment:

> My wife says please and thank you to Alexa. She gives it consideration like she would another human. When the robot asks me what my plans are for the rest of the day, I picture a Jira epic sliding from “In Progress” to “Done,” followed by a confetti emoji from a product manager at Amazon trying to earn their nubby little devil wings.

Where things get super interesting to me is the fact that it seems like (I have maybe read some academic work related to this, not sure) the kind of politeness your wife exhibits isn't useless in the context of a multi-turn session. To the other commenter's point, my understanding is that politeness/rudeness exists in the training corpus (scraped from stackoverflow, reddit, forums, etc) and that you can end up in different areas of latent space based on the overall tone of the session.

In some of the chat tools, because of the context management and "personality" stuff that happens behind the scenes, this can extend cross-session as well. ChatGPT, for example, for me, will frequently include text like "Hell Yeah!" and "Here's the shitty part..." in the responses, which is something I assume is happening because of historical context that's getting injected at the start of each session.

All of that to say... none of this, to me, has much to do with whether or not the thing is conscious, but rather that the training data makes it incredibly difficult for people to not see them as emotional beings because you can end up walking into different areas of latent space where different "emotional states" are affecting the output you're getting.

Unlike your polar bear example, an LLM can "love" you or "hate" you based on the input tokens that lead to the generation of the output tokens. Which is a pretty wild result on its own. Playing around with, say, Qwen 3.8 27B locally with my own experimental harness has been exceptionally fascinating.

I’m not sure that integrating it into a DAW is the way to go, but there’s definitely a need there.