Neat stuff. I just got Claude code and am training myself on Rails, I'm excited to have assistance working through some ideas I have and seeing it handle this kind of iterative testing is great.
One note: I think the author could have modified sudoers file to allow loading and unloading the module* without password prompt.
A good case study. I have found these two to be good categories of win:
> Use these tools as a massive force multiplier of your own skills.
Claude definitely makes me more productive in frameworks I know well, where I can scan and pattern-match quickly on the boilerplate parts.
> Use these tools for rapid onboarding onto new frameworks.
I’m also more productive here, this is an enabler to explore new areas, and is also a boon at big tech companies where there are just lots of tech stacks and frameworks in use.
I feel there is an interesting split forming in ability to gauge AI capabilities - it kinda requires you to be on top of a rapidly-changing firehose of techniques and frameworks. If you haven’t spent 100 hours with Claude Code / Claude 4.0 you likely don’t have an accurate picture of its capabilities.
“Enables non-coders to vibe code their way into trouble” might be the median scenario on X, but it’s not so relevant to what expert coders will experience if they put the time in.
this is a fantastic summary of how LLMs can be used in general. I have found chatgpt/gemini to be useful in following scenarios
1. ELI5 with examples on any technical paper. This summarises papers and explains to me in a way i can understand.
2. At my work, we have to make a lot of proposals, so I have a project created where I put public documents that I can share for proposals and then share the Statement of Work, and it creates a technical document in my format which is about 70% right. I can add/modify the remaining 30%
3. > Use these tools as a massive force multiplier of your own skills. - This is massive when I want to start a new code base. I spend so much time in my head architecting that tools like these help create a boiler plate and structure.
4. Many times, I have stupid ideas but not enough time to waste coding those stupid ideas. The tools help me right terrible codes for my stupid ideas!! :)
I had a suspicion AI would lower the barrier to entry for kernel hacking. Glad to see it's true. We could soon see much wider support for embedded/ARM hardware. Perhaps even completely new stripped-down OSes for smart devices.
When I read an article like this it makes me think about how the demand for work to be done was nowhere close to being fully supplied by the pre-LLM status quo.
No tests whatsoever. This isn't getting close to being merged into mainline and it will stay out-of-tree for a long time.
That's even before taking on the brutal linux kernel mailing lists for code review explaining what that C code does which could be riddled with bugs that Claude generated.
I hope Dmitry did a good job. I've got a box of 2120 tapes with old backups from > 20 years ago, and I'm in the process of resurrecting the old (486) computer with both of my tape drives (floppy T-1000 and SCSI DDS-4). It would be nice to run a modern kernel on it.
It's a good example of a developer who knows what to do with and what to expect from AI. And a healthy sprinkle of skepticism, because of which he chose to make the driver a separate module.
AI works better when it has an example. In this case, all the code needed for the driver to work was already there as the example. It just had to update the code to reflect modern kernel development practices.
The same approach can be used to modernise other legacy codebases.
I'm thinking of doing this with a 15 year old PHP repo, bringing it up to date with Modern PHP (which is actually good).
Something not yet mentioned by other commenters is the "giant caveat":
As a giant caveat, I should note that I have a small bit of
prior experience working with kernel modules, and a good
amount of experience with C in general, so I don’t want to
overstate Claude’s success in this scenario. As in, it
wasn’t literally three prompts to get Claude to poop out a
working kernel module, but rather several back-and-forth
conversations and, yes, several manual fixups of the code.
It would absolutely not be possible to perform this
modernization without a baseline knowledge of the internals
of a kernel module.
Of note is the last sentence:
It would absolutely not be possible to perform this
modernization without a baseline knowledge of the internals
of a kernel module.
This is critical context when using a code generation tool, no matter which one chosen.
Then the author states in the next section:
Interacting with Claude Code felt like an actual
collaboration with a fellow engineer. People like to
compare it to working with a “junior” engineer, and I think
that’s broadly accurate: it will do whatever you tell it to
do, it’s eager to please, it’s overconfident, it’s quick to
apologize and praise you for being “absolutely right” when
you point out a mistake it made, and so on.
I don't know what "fellow engineers" the author is accustomed to collaborating with, junior or otherwise, but the attributes enumerated above are those of a sycophant and not any engineer I have worked with.
Finally, the author asserts:
I’m sure that if I really wanted to, I could have done this
modernization effort on my own. But that would have
required me to learn kernel development as it was done 25
years ago.
This could also be described as "understanding the legacy solution and what needs to be done" when the expressed goal identified in the article title is:
... modernize a 25-year-old kernel driver
Another key activity identified as a benefit to avoid in the above quote is:
I was banned from an OpenSource project [1] recently because I suggested a bug fix. Their „code of conduct“ not only prevents PRs but also comments on issues with information that was retrieved by any AI tool or resource.
Thinking about asking Claude to reimplement it from scratch in Rust…
Here the author has a passion/side project they have been on for a while. Upgrading the tooling is a great thing. Community may not support this since the niche is too narrow. LLM comes in and helps in the upgrade. This is exactly what we want - software to be custom - for people to solve their unique edge cases.
Yes author is technical but we are lowering the barrier and it will be lowered even more. Semi technical people will be able to solve some simpler edge cases, and so one. More power to everyone.
Blast from the past! When I was a kid we had such a floppy tape device connected to a 386 or 486 computer my parents had. I think it was a Colorado Jumbo 250. I think the actual capacity was 125MB, but the drive or the backup software had some built-in compression, hence why it was marketed as a 250MB drive. Never tried to use it with the Linux ftape driver, though.
It wouldn't surprise me if the drive and the tapes are still somewhere in my parents storage. Could be a fun weekend project to try it out, though I'm not sure I have any computer with a floppy interface anymore. And I don't think there's anything particularly interesting on those tapes either.
Off-topic, but I wish Linux had a stable ABI for loadable kernel modules. Obviously the kernel would have to provide shims for internal changes because internal ABI constantly evolves, so it would be costly and the drivers would probably run slower over time. Yet, having the ability to use a driver from 15 years ago can be a huge win at times. That kind of compatibility is one of the things I love about Windows.
I've used Claude Code in the past month to do development on CoMaps [1] using the 20 USD/month plan.
I've been able to do things that I would not have the competence for otherwise, as I do not have a formal software engineering background and my main expertise is writing python data processing scripts.
E.g., yesterday I fixed a bug [2] by having Claude compare the CarPlay and iOS search implementations. It did at first suggest another code change than the one that fixed it, but that felt just like a normal part of debugging (you may need to try different things)
Most of my contributions [3] have been enabled by Claude, and it's also been critical to identify where the code for certain things are located - it's a very powerful search in the code base
And it is just amazing if you need to write a simple python script to do something, e.g., in [4]
Now this would obviously not be possible if everyone used AI tools and no one knew the existing code base, so the future for real engineers and architects is bright!
48 comments
[ 2.8 ms ] story [ 71.8 ms ] threadOne note: I think the author could have modified sudoers file to allow loading and unloading the module* without password prompt.
> Use these tools as a massive force multiplier of your own skills.
Claude definitely makes me more productive in frameworks I know well, where I can scan and pattern-match quickly on the boilerplate parts.
> Use these tools for rapid onboarding onto new frameworks.
I’m also more productive here, this is an enabler to explore new areas, and is also a boon at big tech companies where there are just lots of tech stacks and frameworks in use.
I feel there is an interesting split forming in ability to gauge AI capabilities - it kinda requires you to be on top of a rapidly-changing firehose of techniques and frameworks. If you haven’t spent 100 hours with Claude Code / Claude 4.0 you likely don’t have an accurate picture of its capabilities.
“Enables non-coders to vibe code their way into trouble” might be the median scenario on X, but it’s not so relevant to what expert coders will experience if they put the time in.
I think the training data is especially good, and ideally no logic needs to change.
That's even before taking on the brutal linux kernel mailing lists for code review explaining what that C code does which could be riddled with bugs that Claude generated.
No thanks and no deal.
A reminder though these LLM calls cost energy and we need reliable power generation to iterate through this next tech cycle.
Hopefully all that useless crypto wasted clock cycle burn is going to LLM clock cycle burn :)
The same approach can be used to modernise other legacy codebases.
I'm thinking of doing this with a 15 year old PHP repo, bringing it up to date with Modern PHP (which is actually good).
Then the author states in the next section:
I don't know what "fellow engineers" the author is accustomed to collaborating with, junior or otherwise, but the attributes enumerated above are those of a sycophant and not any engineer I have worked with.Finally, the author asserts:
This could also be described as "understanding the legacy solution and what needs to be done" when the expressed goal identified in the article title is: Another key activity identified as a benefit to avoid in the above quote is:Thinking about asking Claude to reimplement it from scratch in Rust…
[1] https://codeberg.org/superseriousbusiness/gotosocial/src/bra...
If you don't have the technical understanding of a language or framework, there is going to be a lot of ambiguity in your prompts.
This specificity gap leads the LLM to fill in those gaps for you, which may not be what you intended. And that's usually where bugs hide.
I think this is the flip side to being a "force multiplier"
Here the author has a passion/side project they have been on for a while. Upgrading the tooling is a great thing. Community may not support this since the niche is too narrow. LLM comes in and helps in the upgrade. This is exactly what we want - software to be custom - for people to solve their unique edge cases.
Yes author is technical but we are lowering the barrier and it will be lowered even more. Semi technical people will be able to solve some simpler edge cases, and so one. More power to everyone.
One of the things that has Claude as my goto option is its ability to start long-running processes, which it can read the output of to debug things.
There are a bunch of hacks you could have used here to skip the manual part, like piping dmesg to a local udp port and having Claude start a listener.
It wouldn't surprise me if the drive and the tapes are still somewhere in my parents storage. Could be a fun weekend project to try it out, though I'm not sure I have any computer with a floppy interface anymore. And I don't think there's anything particularly interesting on those tapes either.
In any case, cool project! Kudos to the author!
I've been able to do things that I would not have the competence for otherwise, as I do not have a formal software engineering background and my main expertise is writing python data processing scripts.
E.g., yesterday I fixed a bug [2] by having Claude compare the CarPlay and iOS search implementations. It did at first suggest another code change than the one that fixed it, but that felt just like a normal part of debugging (you may need to try different things)
Most of my contributions [3] have been enabled by Claude, and it's also been critical to identify where the code for certain things are located - it's a very powerful search in the code base
And it is just amazing if you need to write a simple python script to do something, e.g., in [4]
Now this would obviously not be possible if everyone used AI tools and no one knew the existing code base, so the future for real engineers and architects is bright!
[1] https://codeberg.org/comaps/comaps [2] https://codeberg.org/comaps/comaps/pulls/1792 [3] https://codeberg.org/comaps/comaps/pulls?state=all&type=all&... [4] https://codeberg.org/comaps/comaps/pulls/1782