I consider myself kind of an AI detractor but even I'll admit that the tool allowed me to do something it would have taken weeks-to-months to learn to do the hard way.
I only got it to the proof of concept stage. The patch adds aac but breaks flac support in the process. And it only works for aac in mp4 container files. But I’m sure with a bit of time we could make a patch which works everywhere and is additive only.
I say ‘we’ - I barely helped. Almost all the work was done by Claude.
Here’s Claude’s report, if anyone wants to build on this work:
https://claude.ai/code/artifact/87d38c2e-9ecb-4066-90cf-e0b2...
Not a successful anecdote, but I have a Windows Hello compatible Kengsington fingerprint reader, and for some time I wanted to write drivers for Linux. Even without using C, it would have been a huge undertaking only to fail in the end; because Claude did much of the research and concluded that the device wouldn't work on Linux (can't remember why but it made sense). Then it suggested what could work.
In this case:
LLMs know the USB Spec very well.
LLMs know how to read raw packet dumps.
LLMs know how to convert a packet dump to USB spec
LLMs know how to write code to generate USB packets from the spec.
Basically, If you have a well-documented problem, the LLM is a shortcut to learning it yourself. LLMs fail when you have a novel or poorly documented problem. They also fail when you provide the LLM with terrible context or too much context.
This is a very novel, reasonably-poorly-documented problem, and so far it has batted 1.000.
After 5-6 consecutive approaches fail, I need a reason to think the next one might work out to stay motivated.
Claude will keep burning credits trying new approaches until something sticks. That's a huge advantage in a field where most of the things you try don't go anywhere.
It also has the benefit that it doesn't usually matter too much if it gets minor details wrong. It's definitely one of the areas - like hacking - where it's a) tedious and b) insensitive to mistakes where AI absolutely shines.
The whole thing took about a day, spread out over a week or so. Without AI, I wouldn't have even started the project, because I couldn't spare the time it would have taken.
None of this would have been possible (or at least practical from a time-value perspective) for me to do without Claude driving the whole exercise.
The odds of success go up a LOT when the stock firmware is easy to extract and reverse engineer.
Or are we in a really cool time where we've solved everything so much so many times we can focus on other things?
Tertiary question: If answer two, what the fuck is that?
For programmers this is the equivalent of when accountants got spreadsheets. We can just tell the machine what to do without manually performing all the steps.
Some programmers enjoyed the code writing more than the problem solving though.
It also requires a root launcher that runs code from the user ~/.hp1008 dir, so security is weakened.
OP should probably add this to his list of accomplishments on LinkedIn...
I bought some cheap host-managed SATA drives the other day that the BIOS can't see and Windows won't recognize. I asked Claude to write a Windows app so I can use them, and it resisted at first, but then gave up and wrote it and they now work great.
It had to implement the entire stack of bare-metal drive functions over SATA and a whole new filesystem to go with it.
I am sooo tired of this AI generated slop.
There's even a zero-install method via https://printervention.app where it runs that Linux VM isolated inside a WebUSB-capable browser. That website itself was posted right here on HN not too long ago.
I get that the LLM code assistant software prefers writing stuff, but constantly re-writing the same solution seems a bit inefficient.
> Thanks for being such a game debugging partner through all the test pages. Enjoy printing, you and the family.
Maybe it's because my own LLM usage is very "Question > Answer" or "Do this > Agent does that" and I never say "Wow, that's crazy it works, thank you!" at the end or such, so I don't see that sort of things, but if I saw that regularly I'd turn me off so badly from using LLMs. I'm not exactly sure where this feeling is coming from though, it's relatively innocent but just feels so inauthentic, I'm guessing because it's simply a machine.
So I find it common (and fine, I suppose) for Claude to reply using that context. "Let me know what your wife thinks of the app" etc.
Seems an oddly specific thing to hone in on otherwise.
The real trick is to have the AI do something that makes its own money, then tokens are effectively free.
People who are complaining about token costs aren't trying.
Same thing here brother: DCP-L2510D (laser printer + scanner).
Wife is on MacOS and cannot print/scan from there, so I'm the scanman.
codeberg.org/mjmvisser/infoframe if anyone’s interested.
But of course it's hard not to both marvel and lament (at) the fact that in the mid-1990s (so yup 30 years ago) I could:
nc 192.168.1.150 9100 < tiger.ps
I know, I know, about garbled print jobs, pages of codes being printed, etc.
But still: it's hard to not at least wonder if some things haven't been lost. For a start printers with their own IP addresses were sweet (instead of a USB cable and, now, people setting up, say, a Pi just to expose a LAN IP for/to their printer). Then of course another talk could be had about the "quality" of modern day HP laser printers compared to what you'd get int the nineties.