> gaussfacts::gaussfact("dice")     # match string
God does not play dice, unless Gauss promises to let him win once in a while. 
God does not play dice with the universe, but Gauss does. 
> 

Changes in version 0.0.4 (2026-09-01)

• Support character argument to support lookup via regular expression
• Correct one old typo in README.md

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

Stable releases, with security support

I run Linux in lots of places, from remote servers/VMs, to my house router, to my desktop/laptop. Some of those I don t want to be updating regularly with new software releases, I need something I can be sure is going to keep working, but will get necessary security + critical updates. A rolling distro that provides security via the latest upstream release doesn t provide that guarantee. Equally there need to be regular stable releases, or things become too stale. (The one time I considered moving away from Debian was during the 3 year Sarge / 3.1 release cycle. I think if things hadn t improved I d have jumped ship to Ubuntu at the time.)

A good selection of packages

One of the reasons I moved from RedHat to Debian was the wide range of packages available as part of the standard OS. Pulling it all into the distro helps with quality control, compared to random 3rd party packages. A centralised bug system and repository is a win too. Perhaps packages at all is something I should list, but I take it as a given if you re running a distro. I need to know what I have installed on my machine, what version that software is, what files it owns, and what it depends on.

Free Software

This is important to me. I ll make pragmatic compromises about software I run on my systems if it makes sense, but I want to start from a place that does not require anything non-free. I ve run a company on Debian, and I ve worked on numerous products that ran it under the hood. The DFSG give me confidence I can do that.

Smooth upgrades

Debian s ability to upgrade a system smoothly is one of the reasons I first moved to it. The first upgrade I did was remotely on a machine sitting on a 2Mb/s leased line. I was nervous doing the reboot at the end, but it came back fine. At the time the equivalent procedure with RedHat involved rebooting into the OS installer to do the upgrade.

I know things have moved on since then, and really it should all be scripted, and machines should be cattle not pets, but for personal use I run a small enough number of machines that having the upgrade path between releases is a must have.

Community

The original pull of the Debian community was the knowledge I could get involved, and upload packages that were missing that I was using. That s how I first got involved, uploading things Black Cat used, which made life easier for us in the long run. I don t have time to maintain all the software I use myself, and I don t want to be beholden to a commercial entity to do so for me, so a distribution that allows me to help out where I can as part of the community seems to me to be the right way to do things.

Architecture support

Perhaps less important, especially when I started using Debian, but these days I have amd64, arm64, armhf, and riscv machines. Everything except for the risvc box is doing something useful, and would need replaced if I couldn t keep running it, and I expect RISC-V to transition into that state in the next few years as the hardware improves.

Binary packages

I ran a FreeBSD desktop for some time. It might have been the way I was holding it, but binary package installs were generally not something reliable, especially after the initial install, and I ended up building things from ports from source quite often. That worked incredibly well (I used to think people who raved about Gentoo really should just go do it properly and use FreeBSD), but I don t want to spend time compiling things, especially on some of my machines (my router should not need a compiler, for example).

Why LLMs are so deceptive The output of an LLM often looks very compelling, professional and correct. Humans have evolved to trust or distrust new information based on easy to detect secondary factors like what authority the speaker holds, or how confidently and eloquently the message is conveyed. Humans are however very bad at fact-checking and cross-referencing new information, as it requires a lot of effort, and humans like saving energy and being as lazy as possible.

Information asymmetry The less you know about something, the easier it is to fool you on that topic. Nobel prizes in economics have been given in for research on how information asymmetry distorts markets and leads to suboptimal outcomes. In the field of software engineering we have now witnessed a flood of aspiring software developers using AI to create software that looks like it might work, but that is actually full of flaws. These people are well-intended, but they simply lack the expertise to understand what they are actually doing, and don t possess the necessary judgement to decide when an LLM spits out something truly useful and when it is creating mostly garbage. This asymmetry in expertise I think explains the majority of the conflict currently witnessed in open source projects the senior developers are flooded with requests to review code that is bad and a waste of time for everyone involved, while availability of AI grows the pool of people who could contribute and create more code slop at an ever-increasing speed. The information asymmetry could to some degree be evened out if seniors teach juniors to do software engineering well, but it is of course not feasible to quickly mass educate everyone. Also, it seems that many don t want to learn but instead expect to have all understanding outsourced to LLMs. Many seniors have noticed this and have stopped teaching juniors as the seniors don t like the feeling of having their time wasted by teaching people who don t want to learn. Juniors probably all understand that it would be better to learn to design and write software yourself, but using LLMs just feels too easy. I can fully relate to why people choose to take the path of least resistance. Unfortunately, that path often leads to a dead end.

Humans fall too easily for anthropomorphism The human brain is wired to think that inanimate objects are alive and have feelings. Small children talk to their stuffed animals as if they were real, and lots of adults experience feelings of things happening in their surroundings due to some acts of gods or elves being angry or whatever. When we see a machine writing just like a human, or even more convincingly hear it talk and respond to our talk like a living thing, our brain automatically starts assuming it is a living thing with intelligence and feelings. The fact that these creatures live in the abstract cloud and only appear through a portal we hold in our palm and behave in a way that was designed for maximum engagement makes the illusion even stronger. I recommend people try out running LLMs locally on their laptop to see the raw thing spitting out tokens and have some of the illusion shattered. Also stop saying please to an LLM. It does not have any feelings.

Understanding temperature In my experience understanding the concept of temperature in LLMs helps see why an LLM might confidently generate a plausible-looking but totally wrong code change. The large language models are statistical machines that, based on the input (previous tokens) to the neural network, try to predict what to output (next token). When running an LLM, if the temperature is configured to be zero, the output is very predictable and always follows the paths of the strongest connections (a.k.a. weights) between nodes and layers of the neural network. Unlike in living creatures where the brain learns and changes all the time, the weights of an LLM can only change during training. When an LLM is in normal use (during inference, generating next tokens) the weights are fixed, and if temperature is zero, the answer to a specific question will always be exactly the same. This is of course a bit boring and too machine-like, so typically LLMs have a bit of temperature set, which introduces random variation in what connections the neural network traverses. Again, I recommend people try running small LLMs locally where temperature and other settings are fully exposed and configurable to see this themselves. It is a good antidote to falling for the illusion that LLMs would actually be intelligent.

Why benchmarks don t tell the whole story If LLMs continue to produce so much garbage, why are benchmarks showing that they are constantly improving? AI models are indeed improving all the time. For example the CAIS AI dashboard visualizes how frontier models have evolved in the past few years. However, the best models still have a pass rate of only about 50% on the Humanity s Last Exam. On SWE-bench the best model today resolves just under 77%. That means there is a significant number of times when the AI is wrong. This matches my personal experiences, and the renowned Greg Kroah-Hartman recently wrote on the Linux developers mailing list that even with the best of the current and next generation tools, at least 1/3 of the results they generate are flat out wrong or harmful . When generating cat videos the error rate does not matter, but in engineering, things absolutely must be correct. Sure, humans also make mistakes, but well educated and properly incentivized humans are so much more capable than LLMs in many regards. We can achieve complex things that work reliably, such as operating worldwide commercial air traffic without planes falling down every day. There are currently a lot of humans who are incentivized to maintain the narrative that general artificial intelligence is coming soon and will take over everything. In fact, the whole financial system is currently skewed towards such a vision because the promise of falling labour costs and increased profits and monopolistic control of everything attracts capital like nothing before. In this environment we need to remember that machines and economic systems are ultimately servants of humans, and not the other way around.

It s just a tool LLMs are not a scam, but a useful tool and technology that has its uses. But the idea that AI has or will surpass humans any time soon in either capabilities or efficiency is simply not true, and we should listen to the people who created humanity s so far most complex systems (computers and software), who are saying that LLMs are in many cases so bad, that it might be better to ban them in certain places completely for the time being than to waste far more valuable human time on reading the text and code they generate. The time asymmetry is not a new phenomenon as there has been various script kiddies for a long time. As an example, a person running a memory leak scanner without understanding the results and spending 10 minutes to file a bug report could force an open soruce maintainer to spend an hour on proving and explaining that the finding is false. What is new is how much the AI users blindly trust the outputs they get, and open source is uniquely vulnerable as there are no managers protecting developers use of time.

What I do, recommend, and expect to see in the next stages I am using AI tools daily, and constantly experimenting with new models and new ways to use them. Sometimes they work, and often they don t. Sometimes looping AI on itself can make it fix its own errors, but sometimes it just gets derailed and will never arrive at the correct solution. When an LLM fails to make a calendar entry for the right time based on reading my email it is easy for me to spot that it is wrong. I try to avoid using LLMs for anything where I can t exercise judgement myself on whether the result was correct or not. I also really hope that other people would not send me anything where their own effort was less than the effort I have to make reading and understanding it. This principle is not new many have heard the requirement that reading code must require less effort than what it took to write it. I have always kept a high bar on software code and asked fellow developers to make sure their code is well structured, easy to follow and documented. LLMs unfortunately make it easier for people to cheat in this regard, but if cheating is easier, maybe the punishment and deterrence needs to be higher now too. Now with many open source projects adopting policies that put guardrails on AI use, I expect we will soon start witnessing cases where the policies are enforced and it will be interesting to see how violations are judged. As a society we might also need to develop new social standards and rules in what is acceptable treatment of other humans in human-to-machine interactions, and perhaps also new standards in showing what humans are responsible for what machine as the machines start acting more and more independently. I encourage people to take part in these discussions, and in case of doubt, err on the side that favors real human interactions. Contrary to what many business people seem to think, and even though I am in general a techno-optimist myself, I don t feel there is any need to rush with AI adoption.

• Introduction
• A plea to the undecided voter
• Table
• Notes

Also in this series:

• The Four Horsemen of the LLM Apocalypse
• The people vs the AI overlords

The Debian vote context This is not a coming out. I am not using LLMs on a daily basis, and this blog is, again, written out of my cold dead hands in a dying world, with over-engineered hardware and (to a certain extent, hi Emacs!) software, powered by 100% green energy built on stolen land. There is a vote going on in Debian. If you're unfamiliar with it, you can catch up at LWN. So far I've essentially said "LLM is bad" which is not a very balanced or useful opinion. Obviously, people are using LLMs, sometimes unknowing or unwillingly, and we need to take that into account. Furthermore, there has been many different blog posts on Debian planet about this. Some that I found balanced, good summaries, even if I didn't fully agree with them, at least some did the basic civil service of being short. But others were just not only Wrong but also so long that I couldn't finish that I just had to write something.¹ This is not an explanation of the ballots, nor how I will vote. This vote is Debian's failure of framing that debate in a reasonable way: we have 8 options on the ballot with many duplicates. We have failed to do the hard work of summarizing and aggregating options into a meaningful set. I doubt the final vote will represent a readable position we can rally around. I have not read the two months of debates on the topic either. Normally, before voting, I take a cursory look at the debate to see points of view I might have missed. But in this case, it will just make me sad, add noise, and I'm already pretty sure on where I stand on this. So let me describe how I use LLMs and how I think they fit in our work, as computer engineers and hobbyists.

My LLM use

Debian Packaging An astute reader has pointed out that I maintain a package in Debian made to use Anthropic. It's actually multiple packages:

• llm: a CLI utility and Python library for interacting with Large Language Models, with OpenAI as its default API backend
• llm-anthropic: a plugin for llm which allows me to talk to Anthropic's API instead of OpenAI
• anthropic-sdk-python: the SDK llm-anthropic requires to do its work

As I previously explained in response, I am not entirely comfortable with this work: it's a compromise. In fact, I first uploaded llm to the contrib section of Debian, where we keep software that depends on other non-free software, but I was told that, since yt-dlp was in main, llm belonged there as well. So I moved it to main, alongside similarly controversial tools like llama.cpp or the python-openai library.

OpenAI and Anthropic usage An important part of my work is technology watch. I keep tabs on thousands of (new and old) software projects, follow news, and generally try to keep my skills up to date. It's a pretty impossible race, especially as I grow older, but I still think I'm doing the right choices in my job. Testing large language models is part of that work. At first, I was using ChatGPT's web interface, but it was annoying to copy-paste things into a browser, so I looked for different interfaces. For a while I tried gptel, a "simple, extensible LLM client for Emacs" but I found it kind of terrifying. Giving a LLM control over an Emacs buffer seems like a security nightmare, so I stopped doing that. So I use the llm command-line tool to talk to Anthropic's API. I started that in the summer of 2025, when I bought 20$USD of API credits. Before that, I paid for a ChatGPT subscription and then OpenAI credits, which expired and sent me over to Anthropic, which seemed then to have better ethics. As it turns out, Anthropic is also happy to work for the US military (which is a big red line for me). Anthropic also won't let you talk about the genocide in Gaza, it is destroying physical books, and is blackmailing us to use their product for security coverage. Needless to say, Anthropic and "Claude" are not my friends, but they seem like the lesser evil in current "frontier models". So I have renewed, a couple of weeks ago, another 20$USD of API credits with Anthropic.

Actual prompts and responses So what does 20$ give you at Anthropic anyways? What am I using LLMs for and how? The neat thing with llm is that everything is logged in a sqlite database, so there are some answers that are easy to get:

> llm logs status
Logging is ON for all prompts
Found log database at /home/anarcat/.config/io.datasette.llm/logs.db
Number of threads logged:   7
Number of turns logged:     12
Number of legacy conversations: 543
Number of legacy responses: 970
Database file size:         9.61MB

That is 10MB of logs, with about a thousand prompts. My logs go back to 2024-03-07, a little over two years ago, and include a mix of Anthropic and OpenAI responses. I used it more in 2024 than 2025, and if the trend continues, I will have used it less in 2026 again:

> llm logs list -n 0  --json   jq -r .[].datetime_utc   sed 's/-.*//'   sort   uniq -c 
    527 2024
    357 2025
     98 2026

It looks like about 10 prompts per month right now, down from a peak of about 60 per month in 2024. It's pretty difficult to analyze those actual logs to get more patterns and I won't run the prompts through a model again to process them.

How I'm using models now At first, I was using it partly for benchmarking model's capabilities, like Simon Willison does with his pelicans, clearly not trusting its output. But I was impressed by the capacities of the Claude Opus 4.5 model when it wrote this script in January. Impressed, but also scared: it's the first time I felt I could delegate the entirety of my programming to a model. Just run the code, if it works, it works, right? So what do I use it now? As an example, here are the 10 last prompts in my history:

1. there is now Claude 5, and a fable model, maybe you know about it?
2. impress me
3. not impressive, i already know all of this
4. chat
5. in postfix, i have a 300k mailing that happens regularly here. normally, it delivers within about...
6. is there a way i could have drained the maildrop queue faster without removing the milter?
7. the problem was that rspamd was timing out on the FUZZY_CALLBACK check. how do i disable that?
8. how do i disable all spam checks? i just want rspamd to add dkim signatures
9. how do the default_destination_concurrency_limit and initial_destination_concurrency settings int...
10. mic check

The first one was me trying to confirm which model I am using, which is not always obvious when going through the whole llm stack I've been using. The following two are an attempt at seeing what the model is capable of and I was "not impressed", to which Claude answered that I have a "high bar", which, fair enough. The chat is me failing to use a command line, which shows that perhaps I need to readjust that "high bar", again. The next five are a rather embarrassing debacle in a large Postfix mailing that went sideways, and where I couldn't find an actual Postfix expert of my level to help. The fabled Claude Fable 5 answered rather correctly, but dangerously, that I could empty the queue by disabling the non_smtpd_milters. What Fable (and myself) did not realize is that the milter was also adding DKIM signatures, so while the mailing was expedited, it was done without those precious signatures, which got us promptly blocked at Gmail. We have recovered since, and, thanks to the model and reading the Postfix manual for the hundredth time, that pickup(8) is single-threaded and that we needed to review the architecture of that mailing (and our spam filters) a bit. Many tickets ensued. The last one is a test I did to make sure my last uploads of llm-anthropic and its dependency worked correctly.

Note that the above excludes 5 questions I asked Anthropic while writing this article, where I asked for synonyms and "what nanometer scale are arduino processors built from? how is an arduino CPU printed?", a question which Wikipedia furiously evades providing a good answer.

Those prompts are pretty typical of my LLM use: I'm testing the models to see if they work at all, but also, out of desperation, I fire off a prompt after I fire off questions to colleagues or search engines (in that order). It's often weird edge cases like the Prometheus query language, Python's matplotlib, LaTeX, Elisp, optimizations, and so on. I use models for translation a lot. Being fully bilingual, it is common for me to think of a word in French or English and fail to find exactly the right word for that in the other language. Models help with that, and are also useful to find synonyms. Those are low-token uses that seem pretty innocuous to me, but I realize the irony of this after writing about the tower of Babel.

What I am not using models for I am not using models to write prose. I am not using models to read prose. If it's generated with LLMs, I stop reading. I am not using models to write code, with the exception of that single Python script above. I am generally not using models to review code, with exceptions. If I get stuck on a hard problem, I might feed a piece of code to the model. I repeatedly fed asncounter into Claude to try to fix a performance regression I had introduced. It found micro-optimizations that taught me a thing or two about Python's internal implementations, but overall, it was mostly a waste of time. This was in June 2025, so perhaps now models would fare better. I have not tried again. I am not using LLMs to do Debian packaging. When I can, I manually review the diffs of packages I upload into Debian, still, by hand. I do this for the reasons outlined in The Four Horsemen of the LLM Apocalypse, because I refuse to be complicit in the:

1. aggressive and illegal scraping of the servers I steward
2. world-wide computer hardware shortage (making it, by the way, nearly impossible to run presumably clean local models) and the attack on our job conditions (also discussed in The people vs the AI overlords)
3. death of copyright and free software
4. complication and enshifitication of everything, and the destruction of our communities
5. the imperialist Nerd Reich that wants to take over the world

Like I reluctantly use Intel computers, I do fire off a prompt. But I still hold on to the dream that we can build communities of practice that hold human knowledge collectively and not offload that as a utility to some megalomaniac billionaire.

Their LLM use I am forced into So that's me. Clearly, I'm going against the grain here. Everywhere I look, I see LLM-generated code and projects. Slop and botnets have flooded the web. I use Wadamesh, clearly vibe-coded, because it's the best graphical interface for MeshCore that runs on portable devices. I wish it was made by a human, in a community I could participate in, but it isn't, and I don't. I package the above llm toolset, which is more and more vibe-coded, but I still review the diffs. And I have to say: I trust Simon here. The code is verbose as hell, feels overengineered, and llm feels slow, but it generally works, and Simon is still at the gate. The Anthropic SDK is another thing entirely. The 0.91.0 to 0.120 upload, for example, was nuts:

 806 files changed, 72281 insertions(+), 1478 deletions(-)

I explicitly did not review that entire diff. It feels like there's a lot of garbage there to just have a shim between a proprietary API and Python. But this is the hand I've been dealt.

Larger projects LLM use LLMs are being used in the Linux kernel, Firefox, rsync, Rust, and other places. I don't feel good about this, particularly in Rust, but they at least made a decent policy. I am glad GCC made a policy against LLM contributions and I support the human Emacs project. We need to have a set of foundational tools that are "clean" in the sense that they are built upon a community of people that understand how they are built. Maybe that's naive or even impossible. The Linux kernel and GCC, in particular, are massive projects that have long grown past the scale of a single person's understanding. But the theory was that a community of humans can understand collectively. Now we seem to be throwing up our hands and giving up on that community. That LLMs will just fix the problem, whatever it is. But we're all just one rug pull away from being completely incapable of managing those projects. The argument there is that we'll just switch to local models, but no one is actually doing that. All I see is people use local models as a corner case (for privacy) or as in theory, but in reality, everyone uses the centralized frontier models right now. We just can't fallback. We're in the same situation we were, a decade or two ago, when Microsoft decided it would kill free office alternatives by making Office free for non-profits. It worked: thousands, if not millions of schools, community groups and individuals stopped looking for alternatives (including free software but also "piracy") for Office and embraced what seemed like a generous offer. Now Microsoft pulled the plug and Over 170,000 Nonprofits Lost All Their Data. I'm afraid the rug pull on LLMs will be much worse: never mind that Linus won't be able to use his tireless helper to fix obscure kernel bugs; we're looking at a collapse of the economy so large that we are already talking about bailing out the companies responsible. In a sense, the most striking thing about the Debian vote is it has actually no option to completely refuse upstream LLM contributions. It seems the community has taken it for granted that it's now impossible to build Debian entirely without LLMs. We lost the battle even without a fight, it seems.

A plea for small If it has really become impossible for us to manage the complexity we have built, maybe it's time to stop and think about what we're doing in the first place. We're struggling to even bootstrap our current toolchain! This is one of the things I like the most about working on the mesh: it's low tech, small Arduino devices that is built with decades-old semiconductor processes that is understandable by human beings. Maybe the answer lies more in single-purpose devices like those communicators and simpler multi-purpose computers than what we have now, which is what the permacomputing movement is about. Small is beautiful, let's scale it down.

---

1. and yes, I'm sorry this has gotten this long, I hope you will forgive those 3000 words.

> gaussfacts::gaussfact(9)
Gauss once played himself in a zero-sum game and won $50. 
> 

Changes in version 0.0.3 (2026-08-23)

• Several rounds of continuous integration maintenance and enhancements
• Additional README.md badges
• Updates to DESCRIPTION as CRAN requirements change
• A duplicate data entry has been removed (Tim Pokart in #4)
• Documentation prefers https URLs
• Updated continunous integration multiple times
• Correct man page removing an erroneous duplicate word

Changes in version 0.0.2 (2016-08-03)

• Support 'ind' argument to reference by position
• Clean-up encoding and support extended character set (#2 closes #1)
• Updated continunous integration (#3)

Changes in version 0.0.1 (2016-06-19)

• Initial version and CRAN upload

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

:demo
A1 @0,0 prio=4096
A2 @0,1
A3 @0,2
A4 @0,3
B1 @1,0 prio=8192
B2 @1,1
B3 @1,2
B4 @1,3
C1 @2,0 prio=8192
C2 @2,1
C3 @2,2
C4 @2,3
A1 -- A2 hazard=0
A2 -- A3 hazard=0
A3 -- A4 hazard=0
B1 -- B2
B2 -- B3
B3 -- B4
C1 -- C2 hazard=0
C2 -- C3 hazard=0
C3 -- C4 hazard=0
A1 -- B1 cost=10
B1 -- C1 cost=10
A4 -- B4 cost=20
B4 -- C4 cost=20
Leo @-0.3,0.7 proto=none icon= 
Mia @-0.3,1.3 proto=none icon= 
Joy @0.3,0.7  proto=none icon= 
Roy @0.3,1.3  proto=none icon= 
A2 -- Leo hazard=0 A2:edge
A2 -- Mia hazard=0 A2:edge
A2 -- Joy hazard=0 A2:edge
A2 -- Roy hazard=0 A2:edge
Max @-0.3,1.7 proto=none icon= 
Zoe @-0.3,2.3 proto=none icon= 
Ada @0.3,1.7  proto=none icon= 
Amy @0.3,2.3  proto=none icon= 
A3 -- Max hazard=0 A3:edge
A3 -- Zoe hazard=0 A3:edge
A3 -- Ada hazard=0 A3:edge
A3 -- Amy hazard=0 A3:edge
Eli @0.7,0.7 proto=none icon= 
Jay @0.7,1.3 proto=none icon= 
Kai @1.3,0.7  proto=none icon= 
Ben @1.3,1.3  proto=none icon= 
B2 -- Eli hazard=0.2 B2:edge
B2 -- Jay hazard=0.2 B2:edge
B2 -- Kai hazard=0.2 B2:edge
B2 -- Ben hazard=0.2 B2:edge
Ava @0.7,1.7 proto=none icon= 
Lea @0.7,2.3 proto=none icon= 
Ivy @1.3,1.7  proto=none icon= 
Rex @1.3,2.3  proto=none icon= 
B3 -- Ava hazard=0.2 B3:edge
B3 -- Lea hazard=0.2 B3:edge
B3 -- Ivy hazard=0.2 B3:edge
B3 -- Rex hazard=0.2 B3:edge
Ana @1.7,0.7 proto=none icon= 
Eve @1.7,1.3 proto=none icon= 
Abe @2.3,0.7  proto=none icon= 
Ian @2.3,1.3  proto=none icon= 
C2 -- Ana hazard=0 C2:edge
C2 -- Eve hazard=0 C2:edge
C2 -- Abe hazard=0 C2:edge
C2 -- Ian hazard=0 C2:edge
Ned @1.7,1.7 proto=none icon= 
Lou @1.7,2.3 proto=none icon= 
Fay @2.3,1.7  proto=none icon= 
Sue @2.3,2.3  proto=none icon= 
C3 -- Ned hazard=0 C3:edge
C3 -- Lou hazard=0 C3:edge
C3 -- Fay hazard=0 C3:edge
C3 -- Sue hazard=0 C3:edge

The basics Designed in the 80s, the spanning tree protocol has evolved into a rapid flavor (RSTP) and a VLAN-aware variation (MSTP).² Any sound-minded network engineer knows there are better alternatives, like BGP EVPN VXLAN. Yet, because any switch speaks it, the venerable spanning tree protocol still fills a niche. We focus on RSTP: it replaced the original protocol in 2004. To eliminate network loops, RSTP implements a complex state machine. Timers, link state changes, and the link-local control frames a bridge receives from its neighbors drive its transitions. These Ethernet frames are the Bridge Protocol Data Units (BPDUs). You can watch them in action below: hit the Start button.

:protocol rstp
:tx-hold 10
A1 @0,1
C11 @1,0 prio=4096 icon= 
C12 @1,2 prio=4096 icon= 
C21 @2,0 prio=4096 icon= 
C22 @2,2 prio=4096 icon= 
A2 @3,1
H1 @0,0.2 proto=none icon= 
H2 @0,1.8 proto=none icon= 
H3 @3,0.2 proto=none icon= 
H4 @3,1.8 proto=none icon= 
A1 -- C11
A1 -- C12
A2 -- C21
A2 -- C22
C11 -- C12
C11 -- C21
C11 -- C21
C11 -- C22
C12 -- C21
C12 -- C22
C21 -- C22
A1 -- H1 A1:edge
A1 -- H2 A1:edge
A2 -- H3 A2:edge
A2 -- H4 A2:edge

After some time, the topology converges to a tree: from the root C11, there is a path to each bridge³ and no loop. In the upper right corner, the interface displays a tree icon followed by the time it took to reach this state. Cut a link and see how the protocol finds an alternate path to reach C12 in less than a second. You can stop the simulation, move it forward step by step, reset it to its initial state, or slow it down with the snail mode . Don t worry about all the displayed information: I explain it later.

Note While you scroll, the current simulation stays in view so you can look at it while reading. Uncheck this box to disable this behavior: .

All examples run in your browser, powered by MSTPD an open-source user-space⁴ implementation of RSTP.⁵

Historical interlude Radia Perlman, an inductee of the Internet Hall of Fame in 2014, summarized the ancestor of STP she invented at DEC with this poem, later included in a US patent:

I think that I shall never see
A graph more lovely than a tree.
A tree whose crucial property
Is loop-free connectivity.
A tree which must be sure to span
So packets can reach every LAN.
First, the root must be selected.
By ID, it is elected.
Least cost paths from root are traced.
In the tree, these paths are placed.
A mesh is made by folks like me,
Then bridges find a spanning tree. Radia Perlman, Algorhyme.

Electing the root bridge To build a tree, RSTP first elects the bridge with the lowest bridge identifier as the root bridge. The bridge identifier combines the priority and the MAC address: 8192.6e:2b:10:a0:5f:29. In the example below, S1 and S2 have priorities of 4,096 and 8,192: S1 becomes root. S4 has a priority of 12,288, while S3 keeps the default priority of 32,768:⁶ S4 becomes root. S5 and S6 don t have a specific priority, so the lowest MAC address wins and S5 becomes root.

:protocol rstp
S1 @0,0 prio=4096
S2 @0,1 prio=8192
S1 -- S2
S3 @1,0
S4 @1,1 prio=12288
S3 -- S4
S5 @2,0
S6 @2,1
S5 -- S6

Initially, each bridge advertises itself as root:⁷

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    Root Identifier: 8192.02:00:00:01:00:01
    Bridge Identifier: 8192.02:00:00:01:00:01

Once a bridge receives a BPDU advertising a better root bridge, it propagates this new information to its neighbors.

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    Root Identifier: 4096.02:00:00:00:00:00
    Bridge Identifier: 8192.02:00:00:00:00:01

Assigning roles to ports The second step is to assign a role to each port. RSTP defines five roles, each denoted by a letter:

• root (R),
• designated (D),
• alternate (A),
• disabled (X), or
• backup (B).⁸

Each non-root bridge chooses its root port, the one with the lowest-cost path to the root. Unless you override it, each bridge derives the link cost from the speed: 20,000 for 1 Gbps. In case of equality, the lowest port identifier wins. Each remaining port becomes a designated port if the BPDU it sends is better than the BPDU it receives. Otherwise, it becomes an alternate port. Later, if the root port goes down, the best alternate port becomes the new root port. The tiebreakers for the best BPDU are:

1. the lowest root bridge identifier,
2. the lowest accumulated cost to the root,
3. the lowest bridge identifier, and
4. the lowest port identifier.

:protocol rstp
S1 @1,0  prio=4096 icon= 
S2 @0,1
S3 @2,1
S1 -- S2
S1 -- S3
S1 -- S3
S2 -- S3

In the example above, after convergence, S1 is the root bridge because it has a priority of 4,096, while the other bridges have a priority of 32,768. All its ports are designated ports because the accumulated cost to the root is 0. S2 s port facing S1 becomes a root port because it has the lowest accumulated cost to the root 20,000 vs 40,000. S3 has two ports facing S1, and the one with the lowest port identifier becomes the root port 0x8000 vs 0x8001. The other candidate is an alternate port because the remote port on the link sends a better BPDU, with an accumulated cost of 0. On the segment between S2 and S3, S2 s port wins: while both bridges have the same accumulated cost to the root (20,000), S2 s bridge identifier is smaller 32768.02:00:00:00:00:01 vs 32768.02:00:00:00:00:02.

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    Root Identifier: 4096.02:00:00:00:00:00
    Root Path Cost: 20000
    Bridge Identifier: 32768.02:00:00:00:00:01
    Port identifier: 0x8002

If you cut the active link between S1 and S3, S3 promotes the best alternate port to root port. If you also disable the second link, S3 chooses the remaining alternate port as a root port. But if you disable the link between S1 and S2, S2 needs a bit more work to elect a new root port because it does not have an alternate port. Unless a specific event happens, designated ports send BPDUs every 2 seconds.⁹ If a bridge does not receive BPDUs from its neighbor for 3 consecutive hello periods, it considers the neighbor dead and removes the port information.

Port state transition Each port can have one of three states. The diagram displays a background color for each state:

• discarding (red),
• learning (yellow), or
• forwarding (green).

A root port transitions automatically to the forwarding state. An alternate port stays in the discarding state. A designated port has two options to transition from the discarding state to the forwarding state:

• If the port is an edge port, either through configuration or because the remote device does not speak any flavor of STP, the bridge assumes the device won t participate in the protocol and cannot create a loop. In this case, the designated port immediately transitions to the forwarding state.
• Otherwise, it sends a proposal to its downstream neighbor. If the remote bridge agrees that the received BPDU is better than any other BPDU stored for other ports, it elects the receiving port as its root port and starts the synchronization process: it transitions all non-edge non-synced designated ports to the discarding state to avoid a loop. Then, it sends back an agreement. Upon receiving the agreement, the peer designated port transitions to the forwarding state.¹⁰

:protocol rstp
S1 @1,0 prio=4096 icon= 
S2 @1,1
S3 @0,2
S4 @2,2
S5 @0,3 prio=8192 icon= 
S6 @2,3
H1 @0,1.2   proto=none icon= 
H2 @2,1.2   proto=none icon= 
H3 @2.5,1.3 proto=none icon= 
H4 @2.5,2.3 proto=none icon= 
S1 -- S2
S2 -- S3
S2 -- S4
S3 -- S5
S4 -- S6
S4 -- S3
S5 -- S6
S3 -- H1 S3:edge
S4 -- H2 S4:edge
S4 -- H3 S4:edge
S6 -- H4 S6:edge

In the topology above, H1, H2, H3, and H4 are end devices not participating in the protocol. We configure the ports they connect to as edge ports, so these ports immediately move to the forwarding state. Use the step button to move the simulation forward. The clock moves to 1 second. Step again and S1 and S2 send a proposal to each other. Here is the proposal from S2:

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x4e, Agreement, Port Role: Designated, Proposal
        0... .... = Topology Change Acknowledgment: No
        .1.. .... = Agreement: Yes
        ..0. .... = Forwarding: No
        ...0 .... = Learning: No
        .... 11.. = Port Role: Designated (3)
        .... ..1. = Proposal: Yes
        .... ...0 = Topology Change: No
    Root Identifier: 32768.02:00:00:00:00:01
    Root Path Cost: 0
    Bridge Identifier: 32768.02:00:00:00:00:01
    Port identifier: 0x8001

S1 ignores it: its own root identifier is lower. When S2 receives a similar proposal from S1, it accepts S1 as its root bridge. It also elects the port to S1 as the root port and starts the synchronization process. The two designated ports are already discarding, so no change here. Step again and S2 sends two BPDUs to S1. In one of them, the agreement bit is 1 and the proposal bit is 0. It also shows that S2 accepted S1 as the root bridge and its root port is now in the forwarding state. When receiving this BPDU, S1 transitions its own designated port to the forwarding state. From this point, the link between S1 and S2 forwards user traffic.

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x79, Agreement, Forwarding, Learning, Port Role: Root, Topology Change
        0... .... = Topology Change Acknowledgment: No
        .1.. .... = Agreement: Yes
        ..1. .... = Forwarding: Yes
        ...1 .... = Learning: Yes
        .... 10.. = Port Role: Root (2)
        .... ..0. = Proposal: No
        .... ...1 = Topology Change: Yes
    Root Identifier: 4096.02:00:00:00:00:00
    Root Path Cost: 20000
    Bridge Identifier: 32768.02:00:00:00:00:01
    Port identifier: 0x8001

Let s look at what happened to S5. Reset the simulation and step twice. S5 exchanges BPDUs with both S3 and S6. Since S5 has a lower root identifier than S3 and S6, it stays the root bridge, while S3 and S6 accept the proposal and elect their root ports. S3 and S6 start the synchronization process. S6 s port to H4 keeps forwarding because it is an edge port. Move one step. Both S3 and S6 send an agreement back to S5, which transitions both designated ports to the forwarding state. Yet, the link between S5 and S3 keeps discarding user traffic! If you look carefully, S3 s port toward S5 is now a designated port, not a root port. During the same step, S3 also receives a better BPDU from S2 with S1 as the root bridge. It elects its port to S2 as the root port and downgrades the port to S5 to a designated port, which stays in the discarding state. On the next step, things get a bit tricky. S3 sends a proposal to S5:¹¹

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x4f, Agreement, Port Role: Designated, Proposal, Topology Change
        0... .... = Topology Change Acknowledgment: No
        .1.. .... = Agreement: Yes
        ..0. .... = Forwarding: No
        ...0 .... = Learning: No
        .... 11.. = Port Role: Designated (3)
        .... ..1. = Proposal: Yes
        .... ...1 = Topology Change: Yes
    Root Identifier: 4096.02:00:00:00:00:00
    Root Path Cost: 40000
    Bridge Identifier: 32768.02:00:00:00:00:02
    Port identifier: 0x8002

S5 elects S1 as its root bridge and the port toward S3 as its root port. It starts its synchronization process, but the designated port to S6 does not move into the discarding state. Why? That port stays a designated port and its neighbor S6 has already sent an agreement on the link, so the port keeps its synced status. Now, let s step back to look at what happens to S6. At this point, S6 believes S5 is the root bridge. Step once and S4 sends a new proposal to S6. S6 accepts the proposal, elects S1 as the root bridge and the port to S4 as its root port. The role of the port facing S5 changes: from a root port, it becomes a designated port. Because its peer keeps advertising an inferior BPDU on the link, this port becomes disputed and moves to the discarding state. The root port transitions to the forwarding state and the link starts forwarding immediately because S4 s designated port is already in the forwarding state. If we step one more time, S5 and S6 exchange two BPDUs. The one from S5 is better because of its lower bridge identifier. S5 s port stays a designated port, while S6 downgrades its own port to an alternate port. Let s rewind to the start one last time: cut the link between S1 and S2, run the simulation until the topology is stable, stop the simulation, and restore the link between S1 and S2. During the first step, S1 and S2 exchange proposals. S2 elects S1 as the root bridge instead of S5 and the port to S1 as the root port. It downgrades the previous root port to a designated port and moves it into the discarding state. The other designated port stays synced and keeps its forwarding state. At the next step, S2 sends an agreement to S1 and the link between them starts forwarding user traffic. It also sends a proposal to S3, but not to S4. Instead, it sends a regular BPDU to S4. S4 still elects S1 as its root bridge and the port to S2 as its root port. It demotes its previous root port, the one to S3, to a designated port, which transitions to the discarding state because of the root port change. The other alternate port, to S6, also becomes a designated port and stays in the discarding state. The new root port moves to the forwarding state. On the next step, S4 s port to S3 settles as an alternate port after receiving a better BPDU from S3. RSTP is a giant state machine split into smaller ones: bridge detection, port information, port protocol migration, port role selection, port role transitions, port receive, port state transitions, port timers, port transmit, and topology change. Some of them are per bridge, some per port. Each bridge runs an instance. Time, operational port state changes, and the BPDUs it receives from other instances drive the transitions. Being event-driven makes RSTP more efficient but also more difficult to understand.

Placeholder for the Port Information state machine extracted from IEEE 802.1Q-2005, page 182. Pending IEEE authorization for reproduction, this is the blueprint for the Western Australian Government Railways class Msa Garratt articulated steam locomotive.

Topology change notification A bridge populates a MAC address table: it associates each source MAC address with the port that last received it. When forwarding an Ethernet frame, it looks up this table to choose the right port.¹² When a link fails, a connected fridge reachable through one port may become reachable through another one. The affected bridges should flush the MAC addresses they learned, because these entries may now be wrong. For this purpose, RSTP implements topology change notifications using a flooding mechanism. When a non-edge port transitions to the forwarding state, a bridge generates BPDUs with the topology change (TC) bit set. It sends them to all the non-edge designated ports and to the root port. It also flushes the MAC address table on these ports. When a bridge receives such a BPDU, it propagates the notification to all non-edge designated ports and the root port, except the one the notification came from. It also flushes the MAC address table on these ports. In the examples, the BPDUs with the TC bit set to 1 have a red circle.

:protocol rstp
S1 @1,0 prio=4096 icon= 
S2 @0,1
S3 @1,1
S4 @2,1
S5 @1,2
LPT @0.1,2 proto=none icon= 
S1 -- S2
S1 -- S3
S1 -- S4
S2 -- S3
S2 -- S5
S4 -- S5
S5 -- LPT S5:edge

Start the simulation and wait a few seconds for the topology to settle. Stop the simulation and disable the link between S2 and S5. S5 elects the port facing S4 as the root port, which transitions immediately to the forwarding state. Step once and S5 emits a BPDU with the TC bit set to 1:

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x79, Agreement, Forwarding, Learning, Port Role: Root, Topology Change
        0... .... = Topology Change Acknowledgment: No
        .1.. .... = Agreement: Yes
        ..1. .... = Forwarding: Yes
        ...1 .... = Learning: Yes
        .... 10.. = Port Role: Root (2)
        .... ..0. = Proposal: No
        .... ...1 = Topology Change: Yes
    Root Identifier: 4096.02:00:00:00:00:00
    Root Path Cost: 40000
    Bridge Identifier: 32768.02:00:00:00:00:04
    Port identifier: 0x8002

S4 receives this BPDU. It flushes the MAC address table on the port facing S1: while LPT was previously reachable through this port, it is now reachable through S5. Step once. S4 sends S1 a BPDU with the TC bit set to 1. When S1 receives this BPDU, it flushes the MAC address table on the ports facing S2 and S3. Step once and S1 sends a notification to S2 and S3. Step once again and S2 sends a notification to S3, while S3 does nothing because the port toward S2 is an alternate port. S3 does not flush any MAC address table: LPT is still reachable through its port to S1. If you step a bit more, you will see that some of the periodic BPDUs keep the TC bit set to 1. Each port runs a timer equal to the hello timer plus one second.¹³ The timer starts when the port emits a notification. Until it expires, the port sets the TC bit to 1 in every BPDU it sends. You can also see some periodic BPDUs without the TC bit: they originate from a port that only received a notification and therefore did not arm its timer.

Security RSTP is weak against configuration errors and malicious actors. A bridge not talking RSTP can create a loop. An attacker can insert themselves into the topology to disrupt the service, spy on the traffic, or alter it. To mitigate such problems, you need to identify the edge ports. An edge port connects to an end device, like a PC or a printer. Such devices do not generate BPDUs and cannot create a loop. RSTP defines two related flags:

• When true, AdminEdge initializes a port as an edge port. It defaults to false.
• When true, AutoEdge lets a port become an edge port when it does not receive BPDUs for 3 seconds. It defaults to true.

If an edge port receives a BPDU, regardless of the values of these two flags, it reverts to a non-edge port.

R0 @1.5,1.5 prio=8192
# AutoEdge=true, AdminEdge=false, bridge
S1 @3,1.58
R0 -- S1
# AutoEdge=true, AdminEdge=false, end device
H1 @2.84,2.18 icon=  proto=none
R0 -- H1
# AutoEdge=true, AdminEdge=true, bridge
S2 @2.18,2.84
R0 -- S2 R0:edge
# AutoEdge=true, AdminEdge=true, end device
H2 @1.58,3 icon=  proto=none
R0 -- H2 R0:edge
# AutoEdge=false, AdminEdge=true, bridge
S3 @0.68,2.76
R0 -- S3 R0:edge R0:no-auto-edge
# AutoEdge=false, AdminEdge=true, end device
H3 @0.24,2.32 icon=  proto=none
R0 -- H3 R0:edge R0:no-auto-edge
# AutoEdge=false, AdminEdge=false, bridge
S4 @0,1.42
R0 -- S4 R0:no-auto-edge
# AutoEdge=false, AdminEdge=false, end device
H4 @0.16,0.82 icon=  proto=none
R0 -- H4 R0:no-auto-edge
# Network port, bridge
S5 @0.82,0.16
R0 -- S5 R0:network S5:network
# Network port, end device
H5 @1.42,0 icon=  proto=none
R0 -- H5 R0:network
# AdminEdge=true, bpdu-guard=true, bridge
S6 @2.32,0.24
R0 -- S6 R0:bpdu-guard R0:edge
# AdminEdge=true, bpdu-guard=true, end device
H6 @2.76,0.68 icon=  proto=none
R0 -- H6 R0:bpdu-guard R0:edge

In the topology above, S1, S2, S3, S4, S5, and S6 act as bridges, while H1, H2, H3, H4, H5, and H6 act as end devices:

• S1 and H1 are on a port without a specific configuration: AutoEdge is true, AdminEdge is false,
• S2 and H2 are on a port where AdminEdge is true,
• S3 and H3 are on a port where AutoEdge is false and AdminEdge is true,
• S4 and H4 are on a port where AutoEdge is false.

If you start the simulation and wait about 20 seconds, links to S1, S2, S3, S4, H1, H2, H3, and H4 eventually forward user traffic: none of the flags matter. But what about the two remaining pairs? S5 and H5 connect to a network port. Such a port enables a non-standard feature: bridge assurance. The port transmits BPDUs regardless of its role. If it does not receive BPDUs for 3 consecutive hello periods, it transitions to the discarding state. On the link between R0 and S5, you can see BPDUs traveling in both directions, unlike the other links, where only designated ports send BPDUs. S6 and H6 connect to a port where AdminEdge is true and BPDU guard is enabled. This is another non-standard feature that shuts down a port if it receives a BPDU. In summary, if you expect a port to be an edge port, you should set AdminEdge to true and enable BPDU guard. Otherwise, declare it as a network port.

Why RSTP today? A compelling use case for RSTP today is an out-of-band network for a datacenter, since you can tolerate an outage of a few seconds. The configuration is minimal and you can use cheap switches, like a Cisco 2960X.¹⁴ You need two switches acting as root bridges, and you build several loops to connect OOB switches in each cabinet. This simple design survives one failure on each loop.¹⁵

:protocol rstp
:tx-hold 10
# Root bridges
R1 @0,1 prio=0
R2 @0,2 prio=4096
R1 -- R2 cost=200 R1:network R2:network
R1 -- R2 cost=200 R1:network R2:network
# First loop
C1  @1,0 icon= 
C4  @2,0 icon= 
C7  @3,0 icon= 
C10 @4,0 icon= 
C12 @5,0 icon= 
C13 @5,3 icon= 
C15 @4,3 icon= 
C18 @3,3 icon= 
C21 @2,3 icon= 
C24 @1,3 icon= 
R1  -- C1  R1:network C1:network
C1  -- C4  C1:network C4:network
C4  -- C7  C4:network C7:network
C7  -- C10 C7:network C10:network
C10 -- C12 C10:network C12:network
C12 -- C13 C12:network C13:network
C13 -- C15 C13:network C15:network
C15 -- C18 C15:network C18:network
C18 -- C21 C18:network C21:network
C21 -- C24 C21:network C24:network
C24 -- R2  C24:network R2:network
# Second loop
C2  @1,0.5 icon= 
C5  @2,0.5 icon= 
C8  @3,0.5 icon= 
C11 @4,0.5 icon= 
C14 @4,2.5 icon= 
C17 @3,2.5 icon= 
C20 @2,2.5 icon= 
C23 @1,2.5 icon= 
R1  -- C2  R1:network C2:network
C2  -- C5  C2:network C5:network
C5  -- C8  C5:network C8:network
C8  -- C11 C8:network C11:network
C11 -- C14 C11:network C14:network
C14 -- C17 C14:network C17:network
C17 -- C20 C17:network C20:network
C20 -- C23 C20:network C23:network
C23 -- R2  C23:network R2:network
# Third loop
C3  @1,1 icon= 
C6  @2,1 icon= 
C9  @3,1 icon= 
C16 @3,2 icon= 
C19 @2,2 icon= 
C22 @1,2 icon= 
R1  -- C3  R1:network C3:network
C3  -- C6  C3:network C6:network
C6  -- C9  C6:network C9:network
C9  -- C16 C9:network C16:network
C16 -- C19 C16:network C19:network
C19 -- C22 C19:network C22:network
C22 -- R2  C22:network R2:network

This topology converges in about 6 seconds. Each loop should stay small (around 16 bridges) to reduce the probability of a double failure and to avoid sharing too much bandwidth. The design can evolve a bit without adding too much complexity: one VLAN per loop or one bridge domain per loop.

How large can a network be? The maximum age, whose default value is 20, governs the maximum distance of a bridge from the root. The topology below is too big for BPDUs from R1 to reach beyond S20.¹⁶

:protocol rstp
:tx-hold 10
:max-age 20
R1 @0,0 prio=4096 icon= 
R2 @0,5 prio=4096 icon= 
S1  @1,0
S2  @2,0
S3  @3,0
S4  @4,0
S5  @5,0
S6  @6,0
S7  @6,1
S8  @5,1
S9  @4,1
S10 @3,1
S11 @2,1
S12 @1,1
S13 @1,2
S14 @2,2
S15 @3,2
S16 @4,2
S17 @5,2
S18 @6,2
S19 @6,3
S20 @5,3
S21 @4,3
S22 @3,3
S23 @2,3
S24 @1,3
S25 @1,4
S26 @2,4
S27 @3,4
S28 @4,4
S29 @5,4
S30 @6,4
S31 @6,5
S32 @5,5
S33 @4,5
S34 @3,5
S35 @2,5
S36 @1,5
R1  -- S1
S1  -- S2
S2  -- S3
S3  -- S4
S4  -- S5
S5  -- S6
S6  -- S7
S7  -- S8
S8  -- S9
S9  -- S10
S10 -- S11
S11 -- S12
S12 -- S13
S13 -- S14
S14 -- S15
S15 -- S16
S16 -- S17
S17 -- S18
S18 -- S19
S19 -- S20
S20 -- S21
S21 -- S22
S22 -- S23
S23 -- S24
S24 -- S25
S25 -- S26
S26 -- S27
S27 -- S28
S28 -- S29
S29 -- S30
S30 -- S31
S31 -- S32
S32 -- S33
S33 -- S34
S34 -- S35
S35 -- S36
S36 -- R2
R1  -- R2 cost=200 down

Once the topology settles, part of the network considers R1 the root, while the other votes for R2. At the boundary, S20 tries to start a synchronization with S21 to move its designated port to the forwarding state. The BPDU looks like this:

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x4e, Agreement, Port Role: Designated, Proposal
    Root Identifier: 4096.02:00:00:00:00:00
    Root Path Cost: 400000
    Bridge Identifier: 32768.02:00:00:00:00:15
    Port identifier: 0x8002
    Message Age: 20
    Max Age: 20

S21 rejects it because the message age equals the maximum age. On the other hand, the BPDU S21 sends to S20 looks like this:

Spanning Tree Protocol
    Protocol Identifier: Spanning Tree Protocol (0x0000)
    Protocol Version Identifier: Rapid Spanning Tree (2)
    BPDU Type: Rapid/Multiple Spanning Tree (0x02)
    BPDU flags: 0x7c, Agreement, Forwarding, Learning, Port Role: Designated
    Root Identifier: 4096.02:00:00:00:00:01
    Root Path Cost: 320000
    Bridge Identifier: 32768.02:00:00:00:00:16
    Port identifier: 0x8001
    Message Age: 16
    Max Age: 20

This is not enough to change S20 s root port because S20 has a lower root identifier 4096.02:00:00:00:00:00 vs 4096.02:00:00:00:00:01. Fixing the link between R1 and R2 resolves the issue. The maximum message age any packet carries is now 18, below the configured maximum age. But it only works until another link breaks. A plausible fix is to increase the maximum age to 40.¹⁷

How fast is RSTP? RSTP usually converges in a couple of seconds at startup. It often repairs a tree in less than a second. Even the 38-bridge topology takes less than 10 seconds to converge.¹⁸ Some topologies can take a bit more time to recover when the root bridge becomes unavailable.¹⁹

:protocol rstp
R0 @1,0 prio=0
S1 @1,1 prio=4096
S2 @0,2 prio=8192
S3 @2,2
R0 -- S1
S1 -- S2
S2 -- S3
S3 -- S1

In the topology above, start the simulation, wait for convergence, hit stop, and cut the link between R0 and S1. The topology is already optimal, but RSTP has a hard time converging again. First, S1 loses its root port. It has no more information about R0 and elects itself as the root bridge. It keeps its ports to S2 and S3 as designated ports in the forwarding state. Step once and it sends a BPDU to both S2 and S3 to let them know about the root change. When receiving it, S2 accepts S1 as its root because it does not have a better root on another port. It elects the port to S1 as its root port. The other port stays a designated port. Both ports keep forwarding. When receiving the BPDU from S1, S3 behaves differently: it knows R0 as a better root than S1 through its alternate port to S2. It promotes this port to a root port and demotes the port facing S1 to a designated port, which requires a new agreement. Step once and S3 sends a proposal to S1 with R0 as the root bridge. S1 elects R0 as the root bridge and promotes its port to S3 as a root port. During the same step, S3 also receives a BPDU from S2 stating that S1 is the root bridge. Therefore, S3 has no port left with R0 as the root bridge: it elects S1 as the root bridge and its port to S2 as the root port. Step once and its next BPDU to S1 includes this information: S1 elects itself again as the root bridge. But during the same wave, S1 sends a proposal to S2 with R0 as the root bridge. While S1 and S3 agree that S1 is the root bridge, S2 now believes this is R0! In turn, S2 again convinces S3 that R0 is the root bridge, S3 convinces S1, S1 convinces S2, and S2 convinces S3. This could go on forever, but it does not. The BPDUs saying R0 is root eventually age out when the message age goes past the maximum age. In the example above, at the eleventh second, S2 sends a BPDU to S3 with R0 as root, but S3 drops it because its message age reached the maximum. With some luck, the topology can also converge faster if a port stops transmitting new BPDUs after tripping the transmit hold count, whose default value is 6 per second.

About MSTP MSTP is the VLAN-aware version of RSTP: it runs several instances of RSTP and lets the administrator map each VLAN to a specific instance. For example, you can map VLANs 100 to 200 to a first instance, and 300 to 400 to a second instance. The remaining VLANs map to a special instance named the Internal Spanning Tree (IST). MSTP adds its own complexity, but the gist is that you have several logical topologies acting independently. If you want to dig deeper, have a look at MSTP Tutorial Part I: Inside a Region.

About the interactive examples The interactive examples run MSTPD directly in your browser, compiled to WebAssembly with emscripten. A C API replaces the code talking to the Linux kernel: it manages bridges and ports, exports state as JSON, and drives time deterministically. A JavaScript wrapper makes it more user-friendly:

import   loadMSTPD   from "./dist/mstpd.mjs";
const mstp = await loadMSTPD();
// Create 3 bridges
const a = mstp.createBridge("A",   priority: 4096  );
const b = mstp.createBridge("B",   priority: 8192  );
const c = mstp.createBridge("C");
// Each bridge has two ports
const a1 = a.addPort("a-b",   portno: 1  );
const a2 = a.addPort("a-c",   portno: 2  );
const b1 = b.addPort("b-a",   portno: 1  );
const b2 = b.addPort("b-c",   portno: 2  );
const c1 = c.addPort("c-a",   portno: 1  );
const c2 = c.addPort("c-b",   portno: 2  );
// Build a triangle topology
mstp.link(a1, b1);
mstp.link(a2, c1);
mstp.link(b2, c2);
// Enable all bridges and ports
for (const br of [a, b, c]) br.enable();
for (const p of [a1, a2, b1, b2, c1, c2]) p.enable();
// Execute 40 seconds' worth of wall clock and display the topology
mstp.step(40);
console.log("Topology:", mstp.topology());

Several dozen unit tests explore the features of MSTPD and check that they work correctly in this environment:

$ node --test *.test.mjs
  two bridges: lower priority becomes root (41.657342ms)
  triangle loop: exactly one port blocks and all agree on the root (5.832ms)
  breaking the active link reconverges and restoring recovers (18.730753ms)
[ ]
  tests 40
  pass 40
  fail 0
[ ]
  duration_ms 396.190897

Additional JavaScript code looks for specific <pre> blocks containing a topology definition and turns them into interactive widgets. You can inspect and modify the definition by hitting the edit button. There is also a cool trick to tell whether the topology has converged. After each step, we save a snapshot of the simulation memory, play 50 seconds worth of simulation to check if the topology is stable, and travel back in time by restoring that snapshot. The complete code lives on GitHub. I am happy with the result. It can be difficult to follow everything happening during a single step, but stepping forward and backward helps. I plan to use the same approach in future blog posts about networking features.

Note Michael Lynch reviewed a first draft of this article. He authored Refactoring English, a book to sharpen your writing for blog posts, documentation, commit messages, and tutorials. Any errors are still mine!

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1. The sprites for Stan and Blobby come from Craftpix, the coffee cups from Yanin.
2. STP was introduced in IEEE 802.1D-1990. It is still present in IEEE 802.1D-1998 but was withdrawn in IEEE 802.1D-2004 in favor of RSTP, introduced in IEEE 802.1w-2001. MSTP was introduced in IEEE 802.1s-2002 and merged into IEEE 802.1Q-2003. Both of them are part of IEEE 802.1Q-2022 along with SPB a protocol I had never heard of until writing this article.
3. From here, I use bridge instead of the more common word switch.
4. The Linux kernel only runs STP. It delegates the other protocols to user space.
5. MSTPD implements the state machine from IEEE 802.1Q-2005, but on Linux it runs RSTP only. Linux 5.18 added support for forwarding multiple spanning tree, but MSTPD does not use it yet. See PR #150 for progress on this front.
6. The priority is a multiple of 4,096: with MSTP, the lower 12 bits of the bridge priority encode the MST instance identifier, leaving only the upper 4 bits for the configured priority.
7. To inspect the BPDUs crossing a link, select it, click the Download packets button, and open the file with Wireshark.
8. A backup port only exists if the bridge has several ports on the same collision domain. This should not happen in a switched network.
9. This is the value of the hello timer. It used to be configurable, but IEEE 802.1Q-2005 pins it to 2. MSTPD does not allow another value.
10. If the peer port does not receive an agreement after the hello timer elapses or the maximum age if the port has just come up it falls back to the timer-based method for compatibility with STP: it transitions to the learning state, waits again for the hello timer to expire, and transitions to the forwarding state.
11. As in many proposals, S3 also sets the agreement bit to 1. The proposal bit says I am the designated port on this link and I want to transition to the forwarding state. The agreement bit says I am already in sync with the rest of my bridge on this root information. Both can be true.
12. If it finds no entry, the bridge duplicates the Ethernet frame on all ports, except the incoming one. The same happens if the destination MAC address is the broadcast one (ff:ff:ff:ff:ff:ff). This behavior bootstraps the learning process.
13. This timer makes RSTP resistant to packet loss.
14. You can get them for less than US$100 through a broker. All the ports run PVST+ by default and automatically fall back to plain RSTP.
15. An alternative would be Ethernet Ring Protection Switching (ERPS) another protocol I had never heard of until researching this article.
16. If you look closely at what happens at t=2s, you can see that R2 is gaining popularity as root: S17 to S36 believe R2 is the root bridge. S16 does not follow because we hit the maximum age. Later, S17 to S20 reverse their position. I ll let you explore the state of the various bridges to understand the root cause.
17. When increasing the maximum age to 40, you also need to increase the forward delay to 21 (:forward-delay 21), as the standard enforces this condition: 2 (Forward Delay 1) Max Age. For this specific topology, you could also increase the maximum age to 37 and forward-delay to 20.
18. The simulation may seem slow, but it does not run in real time. Look at the current timestamp in the upper right corner to know the wall clock, e.g. t=8s. Once the topology stabilizes, the same corner shows the convergence time, e.g. 2s.
19. Khaled Elmeleegy, Alan Cox, and Eugene Ng formalized this phenomenon in On Count-to-Infinity Induced Forwarding Loops in Ethernet Networks and later in Understanding and Mitigating the Effects of Count to Infinity in Ethernet Networks. They propose a fix that did not find its way into a standard.

Two Debian Days in one week The Debian Project was officially founded by Ian Murdock on August 16, 1993. The Debian community celebrates its birthday, Debian Day, on or around this date every year. This year, I had the chance to attend two of them: one in Jo o Pessoa, Para ba, and another in Bras lia, the capital of Brazil.

Jo o Pessoa In Jo o Pessoa, we had a two-day event. The first day was dedicated entirely to workshops, and I ran a packaging workshop for newcomers. It was the first time I had been responsible for a workshop, and it was a great experience. We didn't have a lot of time, so I decided to start with a 30-minute talk explaining a few things about Debian. For example, I made this image to explain the packaging workflow: This image was based on The Debian Administrator's Handbook, and I think the participants really enjoyed learning about this workflow. When I showed the slide with this image, it was the moment when I received the most questions. After the talk, I explained my way of working and what they were going to do. The hardest part was setting up the environment, since my approach uses sbuild + gbp. They were running different Debian releases and, because of my inexperience with workshops, I had some of them configure sbuild with unshare, even though it is only available in stable through backports. Some of them even managed to learn how to use backports, while others decided to start again using the "old" way. One thing that helped a lot was the Debian Brasil Wiki. It has all the instructions for configuring sbuild in Portuguese, along with great examples. The Brazilian wiki is an opinionated version of the Debian Wiki. We generally prefer to use it for the convenience of having the exact workflow we follow, as well as an up-to-date Portuguese version of our process. If you want to learn more about the Brazilian community, you can find more details in the schedules from previous DebConfs. We almost always had a talk about the community and its activities. In the end, everyone successfully set up their development environment, and all six participants made their first contribution to Debian. If you take a look at my upload tracking page, you will see that every upload made on August 15, 2026 was a sponsored upload from this event. One of them appear twice in the list because I sponsored the upload and also made some other changes. I also asked all of them to put this in their changelog:

* My first contribution!

The idea was to make it clear to other people that they were only working on small Lintian issues as a way of learning and understanding the process. By the way, I made a UDD query to find packages with the following Lintian tag: redundant-rules-requires-root-no-field. To fix this issue, they only had to remove one line from the debian/control file. It is obvious that these uploads are not particularly useful. I call them "motivational uploads" because my goal is to help newcomers understand the process and immediately give them the reward of having made a contribution to Debian. I'll try to keep in touch with them. My plan is to hold another session, this time remotetly, to help them continue contributing to Debian. In fact, I already have another package prepared by one of them waiting for my review. The second day was a full-day event featuring a bunch of talks from the local community. I gave a talk explaining the new members process. I was the only Debian Developer at the event, and I think having a DD there made a real difference. Being there to answer questions, and simply being present, makes Debian feel more tangible and accessible to people. A big shout-out to Rafael Rocha, who put in a lot of work to make this event happen, with the help of many volunteers who contributed along the way.

Bras lia One thing I really like about Debian Days is that each place has its own way of doing things. In Jo o Pessoa, we had a MiniDebConf-like event, while in Bras lia, we had something smaller but still very valuable. We decided to keep things simple: talk to a few students at the University of Bras lia (UnB) and then go somewhere to eat and have a few drinks.

A bit of history For those who don't know, the DebConf 19 was held in Curitiba, Brazil. After the event, Arthur Diniz got really excited about Debian and decided to go back to his University, UnB, to share his experience and encourage more people to contribute to Debian. I attended one of his talks, thanks to Joenio Costa, who invited Arthur to give the talk. Joenio was also my professor at the time and a Debian contributor. I really liked what Arthur had to say about free software, and he did a great job of presenting the Debian community as a friendly and welcoming place. So I decided to attend local meetings of the Debian Bras lia community, which had been inactive for a long time. Lucas Kanashiro was the Debian Developer who answered our questions and, as I mentioned earlier, simply being there made Debian feel more tangible. Everything stopped when the pandemic began. Then, towards the end of 2020, I saw a message in the Debian Bras lia channel saying that the meetings were back, this time remotely. I was hesitant to join because, back in 2019, I hadn't managed to make a packaging contribution, even with their help. I had eventually given up on the process. So this time, I decided to join the meeting with something already prepared for review. I watched all of Eriberto's packaging videos, picked a random package, and joined the meeting. I remember Kanashiro being excited that someone had just shown up with something ready for review. At the time, it was only the second meeting since Debian Bras lia had come back online, and none of the newcomers had started working on contributions yet. During the same meeting, he also convinced us, the newcomers, to give a talk about Debian just three days later. The MiniDebConf Online Brazil 2020 was happening on Sunday, and the meeting was on the Thursday before it. Since he has great convincing skills, I went along with the idea and prepared the talk with Francisco Ferreira. That was the rebirth of the Debian Bras lia community. Since then, we have maintained a close connection with the University of Bras lia, and today, at least seven Debian Developers are from UnB, whether as former students or former professors. The reason I told this story is that, even though the Debian Day we held in Bras lia was smaller, it is part of something that has been working for us for several years: staying close to an University. We've managed to attract and retain many people who share the same values and interests. I've hope you all had a great Debian Day. If you're reading this and aren't part of the Debian community but would like to join, get in touch!

Disclaimers The current discussion in Debian around the AI GR is very heated, and I won t add to that, however, I am very confused about some of the viewpoints there. But, I had no idea how to even try to write this, so did shut up, until I saw Aigars excellent Optimistic take on AI, which motivated me to try, at least. For the record, I fully subscribe to the post, and to the voting suggestions (and I just voted). Also, for full disclosure, I don t think I did any contribution to Debian until now using AI, neither packaging, nor emails, nor bug reports. And this blog post specifically is 100% hand written. With that out of the way there are two points I want to make in this post.

AI is useful, even if it has risks First is, that even if we could put the genie back in the metaphorical bottle, we should not. We do need to continue working towards safe AI, and efficient AI (less environmental impact), but we should not work towards removing the usage of AI. There are already significant advancements in sciences and technology thanks to the use of AI, so desiring AI to not exist (assuming we had a magical wand) is the wrong approach. Sure, AI has significant risks and I can see ways in which AI can do significant damage to society but I don t think we can go from Kardashev I to II without the use of AI, and definitely not to III. And I think, that should be the goal. A few simple examples: Do we want to rollback all the 20 years old security issues that AI found? Do we want to rollback the recent Moderna cancer findings? Do we want to rollback the concept of extremely large scale pattern matchings , just because it runs on chips and no longer in one person s head?

Reading Debian lists The second point is, lately I found less and less enjoyment in reading Debian lists. Even with that already being the case, I feel so disconnected from many of the opinions being voiced in this discussion. On one hand, it s normal and healthy that people have different opinions, disagree, and move forward. On the other hand, looking at one of the proposed options:

• Moderators and disciplinary teams may make narrow and tailored exceptions to rule 4, and decide on interpretation .
• Violations of these requirements should be treated as violations of the relevant Code of Conduct and should result in swift and proportionate disciplinary action .

I already knew Debian, and some large parts of the OSS world, is left leaning. But those phrasings, to me, are too close to socialism/communism. As someone who grew up under communism, this is a much more slippery slope (disciplinary teams? really?) than AI usage. Ask me in person for more details. So, it is possible that Debian continues to evolve in such a way that I don t find myself in any way close to its ongoing culture. I will be sad at that point, but it will be what it is.

Where to? I think that, until such a time that an AI bubble bursts, what any organization should do is try to logically see where and if AI can help. And in an organization that is about computer software, I see hundreds of places that are subject to very large scale pattern matching so the half of the discussion is, to me, mind-boggling. To be clear, it s not about if you can t beat them, join them . As I wrote above, I think AI is useful, so the point is how to use it effectively. Well, will see what Debian votes. I am half curious, half sad already.

• Proposal A(1) - Action: ban all AI-assisted contributions via Social Contract amendment, except from upstreams (so not rolling back the Linux kernel and other software to "pure", pre-AI state). Claims that copyright/licensing status is unclear, quality is bad, community is being destroyed, web resources see extra load and that training consumes "staggering" resources. Needs 2/3rd majority to pass. - IMHO worst and most inconsistent. If copyright and licensing of AI products is unclear, then be consistent - ban ALL software with AI contributions, fork Linux kernel and other software from pre-AI versions, reject all security fixes of issues found with AI. Quality section lists problems that have not existed in the real world since at least a year of rapid AI coding development. Community section assumes that now all Debian contributions will be drive-by AI slop and no one will learn anything anymore. Ethics section mixes up effects of badly configured systems (AI web load is no different from load from a badly configured Perl script) with claimed "resource" usage without any context, taking on trust project ambitions of startups and assuming exponential growth. And then concludes that delivering less is in the interest of our users somehow.
• Proposal B(2) - Action: allow AI-assisted contributions, with conditions of: legality, accountability, disclosure, no uncoordinated bulk actions, privacy. Concerns on quality and legal status as well as environmental impact and scraper load are noted, but not really addressed beyond labelling them as concerns. - IMHO it is an ok starting position as it establishes that each contributing person must still be fully responsible for their contribution (both legally and technically) and for that has to also understand (and review) what they submit. Disclosure lets others know to watch out for other classes of problems when code was changed with AI assistance. Prior discussion for bulk changes just says that the (already established) practice should not be neglected just because now large changes are easier to do. And the privacy part warns against accidentally sending private or confidential data (like a not yet published security bug) to a public service where it could become public. Personally I would have liked a stronger statement to encourage use of environmentally responsible AI services and local AI tools. Possibly a preference for open-weight models with a clear path forward to preferring truly free AI models, when such a category of products could be clearly delineated and established.
• Proposal C(3) - Action: reject AI-assisted contributions at Code of Conduct level. Claims all the world's evils come from LLMs and that "Ethical and safe use of this technology is almost impossible". Goes as far as banning any use of LLMs even in Debian mailing list emails and Debian Planet blog posts - if you do, it's a CoC violation and may result in exclusion from the project. Additionally mandates the disclosure of the usage ... presumably to ban you more efficiently for it. - IMHO truly a dictatorial nightmare option. Zero actual reasoning or basis for such a decision. Zero sources. Nothing claimed in this option's rationale is even close to reality and nothing claimed there is in any way related to the actual technology being discussed. Like, an "LLM" does not automagically commit "fraud" when you use it, like this proposal claims, as if that was a well-known fact. LLMs are not all "owned by horrible people and companies". Even if some include a (prominent Debian user, long-time supporter and sponsor) Google into "horrible companies" (which is what this proposal implies!), there are plenty of LLMs owned by all kinds of companies all over the world and there are plenty of open-weight LLMs that are not really owned by anyone. Most invasive and dishonest option on the ballot.
• Proposal D(4) - Action: allow AI-assisted contributions, with conditions of: legality, accountability, disclosure, privacy. IMHO same as B, just shorter. Adds a "we don't recommend" towards others developing software with AI assistance. Seems pretty weird to add that and then immediately accept Debian contributors doing so. Assumes that the bulk change bit of B is implied as AI is just tooling, so bulk changes should be pre-discussed just like today - so no change and thus no point in mentioning that. Fair. D is a bit more explicit on expected technical details - like that the "person" submitting the change is supposed to sign it, not AI. Notable is the complete absence of resource usage or the environment from concerns. IMHO it would be better to have that and also recommendations on how to avoid causing environmental damage when using AI.
• Proposal E(5) - Action: no action as such - AI-assisted contributions must follow the same rules as all other contributions and those rules are sufficient. IMHO despite its length this is a very well-worded position statement that describes how and why AI-assisted contributions already work perfectly fine in the Debian context when all the same rules that apply to all contributions are also consistently applied to AI-assisted contributions. It describes how the same legality, accountability, no bulk change and privacy requirements are already in place and still apply and how AI-assisted contributions can and must still satisfy them. I could add again that some guidance would be nice here for both legal and environmental decisions when using AI, but in this case it does not really belong in this proposal itself. We as Debian do not have a document that requires that our non-AI-assisted contributions be made with only sustainably sourced electricity, for example. So why should AI be special one way or another? IMHO Debian should have a datacenter sustainability policy, regardless of the AI discussion.
• Proposal F(6) - Action: discourage AI, but allow it based on existing processes (similar idea to E). Dances a bit around the question of disclosure of AI use (as a courtesy) and accepting that some people may still ban all contributions where any AI was involved in any way. Which in turn discourages disclosure to avoid pointless rejection of valuable contributions (like security patches). IMHO this option is ok, but so watered down that it is bound to bring up further discussions and conflicts on details.
• Proposal G(7) - Action: ban non-humans from directly contributing to Debian. IMHO - another bizarre and self-contradictory option. It bans all Debian interactions with AI assistance, including email messages to Debian mailing lists and (supposedly) blog posts on Planet Debian. It "reminds" people who "use such tools assistively" of the DFSG and Social Contract - isn't that a threat of a ban and expulsion similar to C? The proposal does take pains to delineate where a contribution comes from AI as output (bad) vs when you are assisted by AI in the process of exploring, researching or maybe even reviewing the code, but you actually type all the code yourself and use the AI just as a taskmaster with a whip (good). And just like A or C it completely ignores how this inherently evil and unstable AI-generated code becomes perfectly fine and good as soon as someone develops that outside of the Debian project. Even if the same person then packages it for Debian the next day. It is hypocritical, unsustainable and ignores the needs of our users. Just like C it also bans someone writing an email or bug report in their native language and using a modern translation tool or service (that uses LLMs nowadays for better grammatical clarity) to translate that to English before sending it to a Debian mailing list or BTS. Heavy-handed and invasive. And the only reasoning provided for this is some unnamed "concerns" of "extra work" being borne by "other people"? Kind of does not feel right to bear such draconian restrictions for some unspecified concerns.
• Proposal H(8) - Action: condemn usage, but not actually ban anything. And then it goes on to claim (without any evidence or elaboration) that LLM usage accelerates the destruction of "planet earth" (sic). IMHO this proposal is at the same time the loudest ("The planet is burning") and also the one that demands the least action. It dances a really twisty line between raising "significant" concerns in all areas and even claiming that use of LLMs destroys the planet, flies by explicit condemnation of LLM usage and then suddenly collapses with not condemning LLM users and swinging to lamentations that it is actually impossible to impose policies on LLM usage or even detect when an LLM was used (which kind of directly contradicts bad quality claims from A, C and G) and lands on "encouraging" contributors not to use LLMs (where practical) and otherwise do nothing else. It's like this is a 5th draft that started off with the rationale and total ban like in C, but then got defanged so far that its action side no longer matches the rationale stated.

• Proposal E(5) - solid hack of integrating AI into already existing Debian rules and conventions
• Proposal B(2) - explicit and detailed
• Proposal D(4) - lower because of discouragement to others on what we agreed to do ourselves
• Proposal F(6) - I am not a fan of dancing around with disclosures
• Further discussion(9) - I do not want any option below this to succeed as they would do more harm than good
• Proposal H(8) - loud, but not doing anything actually
• Proposal A(1) - at least this one does not set rules for emails
• Proposal G(7) - at least this one allows an AI overseer to tell you what to write with your own fingers
• Proposal C(3) - the most draconic and invasive one that explicitly wants to kick people out of the project

• information on which AI services have Terms and Conditions that make them problematic for free software development, legally speaking
• information on which AI services do (or do not) achieve a sufficient level of sustainability to be worth recommending (and then do the same for other data centers we already use)
• information on which local AI models were trained in sustainable ways
• base-level prompts to set technical expectations on various types of contributions, like bug reports or patches to packaging or translations
• default configuration for AI-assisted code reviews on Salsa that projects could enable and supplement with their own instructions on top

• encourage them to improve sustainability (where needed)
• investigate and fix problems causing excessive scraping load on systems
• provide AI resources for Debian usage, for example in CI infrastructure or to provide equal development support opportunities for Debian developers who cannot afford paid AI services
• improve coding outputs of their models in the Debian context if/when systematic deficiencies in the output are found by us

Also in this series:

• The Four Horsemen of the LLM Apocalypse
• A more nuanced view of LLMs

How people use models People using LLMs in their workflow have radically changed how programming works, even for people who claim to avoid vibe-coding. And I'm sorry to single out one poor maintainer here: it's not you, Brian, you're just one example among many. But this is typical use of those models nowadays:

Once it s done, I ll use /code-review and let Claude spawn sub-agents to do a full review of the new code. This usually finds some problems, even problems that the main Claude instance didn t find during its validation. I usually keep running /code-review again and again after finding and fixing issues, until there aren t any left.

Think about what that means for a minute. This is automation built to fire up dozens of agents crunching at a problem for minutes if not hours of GPU compute time, in parallel. This is essentially a couple of shelves in a datacenter rack, totally maxed out on power and cooling, abstracted behind a cute little /code-review command. The author, here, is rightly concerned that "Anthropic could pull the rug out and require API pricing", which is perhaps a code word for "charging something closer to actual costs". Brian also pays lip service to environmental and societal costs but those are largely abstracted away, so let's keep that conversation aside here as well, as we have discussed it before anyways. But clearly, this way of working has an (externalized) cost, to say the least.

Paying for non-free tools For decades my work has been focused on free and open source software. I've long stopped using proprietary operating systems like Windows or Mac, and even before that switch, I was mostly using free software on those platforms, partly out of principle, but also because I was too poor. So the tools of my trade are free, and I build free tools with them. It feels like we're going backwards: when I was in school, a millennia ago, my classmates didn't have access to a compiler and were wondering how they would scrape the money to buy a compiler like Borland's or Microsoft's. I had a compiler built into my operating system (FreeBSD at the time), so that wasn't a problem for me. For them, it was a significant expense, but at least those expenses (or more shady sourcing of programs) were a one-shot deal. Fast forward 30 years, and software is rented: you pay monthly for Adobe's Photoshop and Microsoft's office suite just like you pay for Netflix, Disney+ or Spotify². And now you need to add dozens (if not hundreds of dollars) of monthly credits to access LLMs on top of that. So, now we have to pay to get anything done? This is peak enshitification of our job: first they steal our work to train their models, and then they sell it back to us at a profit.

Attacking the engineers AI is coming for our jobs, as engineers, if not everyone, according to the narrative. For a while now, our job market has deteriorated: less jobs, for less pay. Lots of skilled engineers looking for work and finding crap jobs then still looking while working. This is not by accident.³ We engineers have a lot of power, it is not organized, but that's just a couple of unions away (easy!). Tech overlords know this, so they are attacking our profession, directly, by forcing us to train and use models that they can control. Even in environments where programmers are not forced to use LLMs, the mere pressure of other people's LLM-generated work is huge. One can be forced to review LLM outputs, or just peer pressured you into producing more. We're now supposed to accelerate delivery, because models can presumably do things so much better and faster. With supply chain security becoming such a large vector that we now have worms crawling around developers accounts on NPM, increasing the delivery cadence seems like a really bad idea.⁴ The LLM hype is part of the larger wave of cyberwar against workers, against water, against the Earth, against all the people. This is not a matter of individually "adapting to the reality" or personal choice, but a political, social, hard problem we need to address collectively.

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1. I again prefer the term LLM to "AI" because models do not possess intelligence. I did use it in the title because click baiting is apparently important, but I stopped short of calling this one "Rage Against the Machines" because that would be the title of every blog post I have ever made.
2. Yes, I know that Visual Studio is kind of free now, but I wouldn't be surprised if they turn that into a rental as well, because why not.
3. Beyond sabotaging the job market, Sam Altman event wants to sell "intelligence as a utility" something that is just a really bad idea but especially shows how megalomaniac those people are.
4. This brings back memories of another era, walking us back decades in terms of computer security.

For human developers, using coding LLMs magnifies their difference in skill levels.

• Packaging upstream software for Debian (by far the largest task)
• Writing Debian-specific code (eg, apt or the Debian installer)
• Maintaining Debian infrastructure (build systems, for instance)
• Writing documentation and translations

• Proposal A: seeks to amend the social contract, which I am opposed to for reasons already laid out above. It names some real concerns about AI that I agree with, but implies that all LLM uses and models are guilty of the problems, which is not the case with all of the claims. It also sets us behind the curve on security and stability by forbidding the use or assistance of those tools, even if run by others. It requires us to ignore reports of actual security bugs, or correct fixes, if those reports were generated with the assistance of an LLM, which I find to be absolutely untenable.
• Proposal B: This is the AI with accountability approach. It notes the real concerns with LLMs without painting with an overbroad brush. It strikes me as level-headed and sensible.
• Proposal C: It paints with an over-broad brush and makes some non-binding requests. Then it winds up largely like proposal B, though while it is worded more strongly, has fewer binding requirements (for instance, it lacks proposal B s prohibition on transmitting sensitive information to untrusted providers)
• Proposal D: Seems broadly similar to proposal B, an AI with accountability approach. I m not really clear why we need both.
• Proposal E: Largely the status quo. It is like proposals B and D in that it says humans are accountable for their contributions. It encourages disclosure of LLM use, but does not mandate it. Like proposal B, it prohibits disclosing sensitive information to third-party AI services. Note that both proposals B and D have an appropriate nuance: a local model is fine, a third-party one is not.
• Proposal F: This seems really similar to proposal E. I m not sure why we have these two.
• Proposal G: Disallows the output of generative AI as direct contributions to Debian. This is something of a weakened proposal A; it doesn t seek to amend the social contract, nor does it ban all use; it simply bans the use as a direct contribution.
• Proposal H: Ban due to climate impacts. How is this even an argument is disrespectful to reasoned conversation. I have already noted that LLMs can be and are used in ways that are not climate-harming. It explicitly contains no binding requirements at all, and is effectively a rant. While I agree with the sentiment that climate change is an urgent problem, and that some LLMs are exacerbating it, I disagree with that all LLM usage does so and therefore disagree with the conclusion.

Welcome to the July 2026 report from the Reproducible Builds project! In our reports, we try to outline the most important things that we have been up to over the past month. As a quick recap about what problem our project intends to solve, whilst anyone may inspect the source code of free software for malicious flaws, almost all software is distributed to end users as pre-compiled binaries. The motivation behind the reproducible builds effort is to ensure no flaws have been introduced during this compilation process by promising identical results are always generated from a given source, thus allowing multiple third-parties to come to a consensus on whether a build was compromised or not. If you are interested in contributing to the project, please visit the Contribute page on our website. In this month s report, we cover:

1. Tool development
2. Distribution work
3. Three new scholarly papers
4. Patches
5. Misc news

Tool development diffoscope is our in-depth and content-aware diff utility that can locate and diagnose reproducibility issues. This month, Chris Lamb made the following changes, including preparing and uploading versions 324, 325 and 326 to Debian:

• Fix tests to work with zipdetails 4.0008. (#1141359)
• Bump debhelper compatibility level to 13. [ ]
• Update copyright years. [ ]

In addition, Paul Spooren made changes to allow trailing garbage in Gzip files [ ] and Vagrant Cascadian added an external tool reference for the pedump binary to use the mono package under GNU Guix. [ ]
disorderfs is our FUSE-based filesystem that deliberately introduces non-determinism into system calls to reliably flush out reproducibility issues. This month, Christelle Gloor added the option to sort by ctime as returned by the lstat(2) syscall. [ ], which Chris Lamb uploaded whilst bumping the Standards-Version to version 4.7.4 [ ]. Bernhard Wiedemann also updated disorderfs to version 0.7.0 in openSUSE.
Yet again, there were a number of improvements made to our website this month as well. For example, Chris Lamb, by request of Digital Ocean, changed the target of a referral link so that they can manage incoming referrers [ ] and pushed a number of changes to the Tools page [ ].

Distribution work In Debian this month, 32 reviews of Debian packages were added, 26 were updated and a total of 21 were removed this month, adding to our extensive knowledge about identified issues. A number of issue types were added by Chris Lamb, including:

• python_towncrier_build_date [ ][ ]
• log_files_installed_in_package [ ]
• fontforge_varies_by_timezone [ ][ ]

Chris also added a further note for the build_date_in_manpage_generated_by_spf13_cobra issue. [ ]
In addition, there is a new page showing verification rebuilds of OpenWrt APK packages and firmware images, powered by rebuilderd:

Three new scholarly papers Yan Li, Nan Jiang, Qihang Zhou, Shaowen Xu, Yamin Xie and Xiaoqi Jia of the Chinese Academy of Sciences published a paper titled VCAligner: Aligning Source Distribution Versions with Upstream Git Commits to Secure Supply Chain:

We present VCAligner, a content-based alignment methodology that constructs inverted indexes over VCS histories to precisely map released artifacts to their originating commits, independent of fragile version tags. We evaluated VCAligner on a dataset of 2,984 verifiable PyPI packages derived from the 4,000 most-downloaded projects linked to public GitHub upstreams. Our results reveal a critical weakness in conventional tag-based heuristics: while they appear effective on 85% of the dataset, the residual 15% failure rate generates a catastrophic downstream audit workload of over 10.3 million commits. In contrast, VCAligner reduces this burden by two orders of magnitude ( 158 ), bounding the total workload to under 65,000 commits. Furthermore, we provide the large-scale characterization of Packaging Noise, classifying artifact divergence into structural additions (Path Phantoms) and content mutations (Blob Phantoms), thereby isolating the distinct attack surfaces of malicious injection and code tampering.

Jens Dietrich and Spencer Sun from the Victoria University of Wellington together with Tim W. White and Behnaz Hassanshahi from Oracle Inc pre-published their paper No Snake Oil: Verifying Python Package Builds (PDF):

Python has become the default language for interacting with AI, with packages being distributed through registries like the Python Package Index (PyPI). This creates a need to analyse supply chains comprising such packages. One such analysis is to rebuild packages in order to identify compromised builds injecting malware. Independent rebuilds in hardened environments have the added advantage that they can generate and record provenance in order to increase the trustworthiness of packages. Two tools that are designed to automate such rebuilds and run them at scale are macaron and oss-rebuild. We study 12,180 popular releases from PyPI and find that the byte-for-byte equivalence rate is generally low. We analyse the reasons why they produce different wheels, and find that equivalence between the original and rebuilt wheels can often still be established, preserving most of the guarantees users expect from rebuildable releases. We present and evaluate daleq4py, a tool to establish the equivalence of Python wheels through the kernel of a normalisation function that is based on provenance-preserving datalog rules. Experimental results show that daleq4py substantially expands the set of rebuilds that can be accepted as equivalent. Although only 15.4% of macaron rebuilds and 19.1% of oss-rebuild rebuilds are byte-for-byte identical to the published PyPI wheels, daleq4py establishes wheel equivalence for 60.2% and 78.9% of source-equivalent rebuilds, respectively.

Denise Nanni, Julien Malka, Stefano Zacchiroli and Th o Zimmermann from T l com Paris together with Gabriele D Angelo from the University of Bologna pre-published their paper Understanding Build Reproducibility in the F-Droid Ecosystem (PDF), which was accepted at the 2026 ACM Conference on Reproducibility and Replicability:

The security of open source applications benefits considerably from the possibility of rebuilding their source and verifying the output. F-Droid, a prominent distribution for open source Android applications, systematically rebuilds them from source and tests their bitwise reproducibility at app publishing time. However, F-Droid offers no guarantee that app reproducibility will continue to hold in the future. As software ecosystems evolve, reproducibility may degrade, with potential negative consequences for software preservation and security. We present the first empirical study of build reproducibility in the F-Droid app ecosystem. Analyzing historical reproducibility logs, we find that the overall bitwise reproducibility rate has been steadily increasing over time (as new versions of apps are published). We then evaluate how reproducibility holds in time for fixed app versions, by attempting to rebuild 18 904 app versions that F-Droid had previously confirmed bitwise reproducible, published between September 2018 and February 2026, achieving an 83% rebuild success rate, and identify missing dependencies as the dominant cause of failure, accounting for 76% of non-rebuildable cases. Among successfully rebuilt apps, 94% are also bitwise reproducible-i.e., they still yield bitwise identical artifacts upon rebuild. Together, these results show that while bitwise reproducibility largely holds for apps that can be rebuilt, rebuildability itself is highly sensitive to temporal decay.

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:

• openSUSE monthly
• Arnout Engelen:
  • ivy
  • pekko-grpc
  • sbt-ivy
  • scala
• Bernhard M. Wiedemann:
  • angelfish
  • cpython
  • efl
  • erlang+ex_doc
  • eww/glib-macros
  • intel-graphics-compiler
  • java-11-openjdk
  • java-17-openjdk
  • java-1_8_0-openjdk
  • java-21-openjdk
  • mono-core
  • nasm/rav1e
  • python-langsmith
  • zathura*
  • zig0.15
• Chris Lamb:
  • #1141505 filed against golang-github-tidwall-wal.
  • #1141506 filed against lightproof.
  • #1141582 filed against libslow5lib.
  • #1141687 filed against siso.
  • #1141841 filed against grout.
  • #1142126 filed against libpsl.
  • #1142492 filed against node-grunt-contrib-internal.
  • #1142495 filed against fontforge.
  • #1142496 filed against spopt.
  • #1142887 filed against go-dlib.
  • #1143147 filed against towncrier.
• Jochen Sprickerhof:
  • #1141412 filed against python-sphinx-chango.
  • #1141553 filed against gasnet.
  • #1141577 filed against yubihsm-connector.
  • #1141663 filed against dh-fortran.
  • #1142000 filed against watcher.
  • #1142001 filed against rakudo.
  • #1142128 filed against kf6-breeze-icons.
  • #1142141 filed against oxygen-icons.
  • #1142256 filed against gnu-apl.
  • #1142513 filed against barvinok.
  • #1143169 filed against ecbuild.

Misc news On our mailing list this month, Colin Winter of Markovian Protocol wrote to our mailing list on the topic of Reproducible verification for retained logs:

Reproducible builds remove trust in the builder: anyone re-derives the same artifact from the same source, byte for byte. The same shape applies one layer over, to a retained record. Most record-keeping regimes (the EU AI Act s Article 12 logging is the current example) require that events be recorded and logs retained, but not that a retained log be verifiable, by a party who was not present, as unaltered and existing when claimed. That leaves an integrity obligation resting on trusting the party being audited.

(Full thread)

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

$ ipython3 -c 'import httpx;print(httpx.URL("https://example.com/foo/bar/../../baz"))'
https://example.com/baz

$ ipython3 -c 'import httpx;print(httpx.URL("https://example.com/../../baz"))'
https://example.com/baz

$ python3 -c 'import httpx;print(httpx.URL("https://example.com/public/api/public/resources/harmless/../../../../../../../../../internal/data"))'
https://example.com/internal/data

Estonians value health, education and entrepreneurship I moved to Estonia about one and a half years ago. In my observations Estonia strikes me as a country that values health, education (in particular programming and natural sciences) and entrepreneurship highly. I don t know how Estonians achieve it, but they look pretty fit and rarely obese. Estonia has rye bread and sauna in their culture just like Finland, and in addition the flat terrain and well-planned bike routes and extensive network of parks (and pull-up bars everywhere) seem to create an environment where it is easy to live in a healthier way. The consumption of processed foods and candy also seems relatively low among Estonians. The gym chain MyFitness also seems to be present everywhere. Even the Tallinn airport has a calisthenics workout station right at the departure gates, which anyone is free to use while waiting for their flight to take off. One of the top longevity influencers in Europe, Siim Land, is Estonian. Estonians also seem to value the school system highly. The government has been actively raising teacher pay and has a stated goal of reaching 120% of the national average by 2027. The students are also expected to value the education and respect their teachers. According to the TALIS 2024 survey (OECD s international teacher survey), Estonian teachers spend significantly more time on actual teaching and learning and waste less time on interruptions or keeping classroom order compared to the OECD average. This is among the highest rates internationally, meaning they spend relatively little time on maintaining order or dealing with disruptions. While the international education benchmark PISA scores have been dropping globally, Estonia has consistently been climbing the ranks in past decades. In the latest PISA study (from 2022), Estonia ranked number one in Europe for reading, mathematics and science. In the overall results, Estonia ranked seventh globally, only behind countries such as Japan, Korea and Singapore. Valuing entrepreneurship is evident in how the taxation system is set up in Estonia. Famously, in Estonia, companies can defer taxes on annual earnings and reinvest all of their profit in growing the company. Taxes are due only later, when paid out from the company, for example as dividends. For individuals, receiving dividends from any Estonian or foreign company is tax-free as long as the company paying dividends already paid corporate tax on the same income. The tax system is also very simple. For all individuals, all types of income, including salary and capital gains, are always taxed at a flat rate of 22%. This removes the incentive for anyone to try to convert income into different types, setting up holding company structures and other optimizations as there is no gain. All entrepreneurs can simply focus on growing their business and forget extra bureaucracy. There is also no marginal tax rate cliff to stop working at everyone is encouraged to always try to produce as much value as they can. A simple tax system is also reflected in the fact that anyone can easily read all tax rules that apply to individuals in plain English on the Estonian tax authority website, and one does not need to hire any accountants simply to file taxes. Estonia also has a very straightforward investment account system: any person can freely open a self-directed investment account at any brokerage at no extra cost and report it as such to the tax authority, and then use it to save for an apartment, retirement, or other purposes, and defer all income taxes until withdrawal. There are no caps or time limits, and all residents are encouraged to save and invest as much as they can and thus take responsibility for their own wealth accumulation. It seems that culturally Estonians respect people who are active and progress in their careers and businesses more than in other countries. Unlike in Finland, successful people are admired and living on government welfare is not romanticized. At the same time, the government benefits are less generous so people can t live comfortably on them and, for example, many of the asylum seekers Estonia accepted have since left on their own initiative to other European countries in search of better benefits.

Low crime, high trust Another thing that strikes me when walking the streets of Tallinn is that there are no drug addicts, beggars, thugs or the like. The difference compared to, for example, Vancouver (where I lived previously) is stark. In public buildings, people leave their coats and bags hanging in the lobby while visiting. Private houses and apartment block yards are not fenced. In my building, I noticed people even leave their bikes unlocked in the bike shed. I have also seen the staff of a coffee stall in a shopping mall going for a break and leaving everything unattended, not worrying that anyone would take anything while the staff is away. This is not just my personal experience. According to the Numbeo crime index, Estonia has one of the lowest crime rates in the world. Also, comparing drug and property crime stats, for example, Finland has twice as much crime per capita, and places like Vancouver in Canada almost five times more. I don t have any clear explanation for why crime is so much lower in Estonia, but some suggest that higher social cohesion and lower levels of welfare contribute to people standing to lose more if they behave antisocially. Compared to Finland, Estonia also more readily jails repeat offenders, and those who are put on trial will experience a swifter court process thanks to simplified legal processes and more efficient governance.

Moving to Estonia: quick checklist Moving to Estonia is very easy for any EU citizen, in particular if your work is not location-dependent (e.g., remote work or an online business) and you are simply looking for the cleanest and safest environment to live in. First, check into a hotel in Tallinn, check out various neighborhoods to figure out what area you like (my favorites are Kalaranna, Kalamaja, Noblessner and Volta) and start browsing available apartments in English at kv.ee. Most professionals speak fluent English, so there should not be any difficulty in reaching out to people by email or phone. The next step is to buy a local prepaid SIM card at e.g., an R-Kiosk or a convenience store as signing up for other matters later on will require an Estonian phone number. Once you have an apartment and e.g., signed a rental agreement, you can register in the population registry online. After that, you have proof you are a local resident with an address and telephone number in Estonia. With local resident status, you can go to the police station to get a local ID card. Don t bother scheduling an appointment, just go to the Tammesaare police station in Tallinn, take a queue number and wait. Once it is your turn, they will guide you on how to use the photo booth, fingerprint registration device, and file your application. A few days later you will receive an email confirming whether your application was accepted, and after a few more days, you will get another email notifying you that your ID card has been printed and is available for pick-up at the same location. This will also be your first practical experience of how fast and efficient the government in Estonia is. Once you have the local ID card, you can use the smart card feature to log into all the government eServices and sort out the rest of the relocation process, such as registering tax residency and getting a family doctor.

How did Estonia evolve to be like this? After Estonia regained its independence after the fall of the Soviet Union in 1991, the first elected government in 1992 was led by a very progressive 31-year-old Prime Minister Mart Laar, who managed to set up some very good policies and laid the foundation of a society that has evolved well in the decades since. Estonia was very lucky to have people in power in the 1990s who didn t simply copy what other Western countries were doing, but who tried to think about things from first principles and create Estonia s own model for efficient and fair governance. As a post-Soviet country, the population had also been vaccinated against overly socialist and unrealistic ideals, and everyone had a healthy distrust of the government s ability to solve problems and emphasis was placed on people s liberty to work for themselves as they best see fit. The improvement in living standards over the past 35+ years has also been witnessed by the population, and voting behavior supports keeping the country on the same trajectory. General living standards still continue to improve as the nominal wage growth sits at around 6%, clearly above the annual inflation rate of about 3%. In 2026, the Estonian economy is expected to grow about 2.4%, which is faster than the EU average. The growth in Estonia is not the result of any accounting tricks - Estonia is part of the euro and can t print its own currency, nor has it been funding the public sector with excessive debt. With a 24% debt-to-GDP ratio, Estonia consistently ranks as one of the most responsibly managed countries among advanced Western economies. As wages in Estonia soon catch up with the EU average, and higher defence spending has forced the government to raise taxes in recent years, the economic growth that Estonia has enjoyed for 35+ years since it exited the Soviet Union might slow down a bit in future years. The policies that fueled this growth in living standards, however, are likely to stay.

The tiger leap There is one specific government policy in Estonia s history that I think should be highlighted in particular. Estonia was very progressive by announcing the Tiigrih pe (Tiger Leap) program in 1996 with the goal of equipping all schools with computers and teaching all students the basics of programming. This surely had a large influence on why Estonia has so many successful software companies, why the government eServices are so mature that even neighboring countries like Finland are striving to copy the Estonian government s IT architecture called X-road. The Tiigrih pe project was originally suggested in the mid-1990s by Toomas Hendrik Ilves, then ambassador of Estonia to the United States, Canada and Mexico, and later President of Estonia in 2006 2016. While he was a psychologist by education, he was also a self-taught amateur programmer and used his political influence to promote sensible adoption of information technology in both Estonia and the EU. The history of Estonia has several prominent figures who were not lawyers by profession but engineers, scientists and historians who were very practical in their political decisions, which I think is now reflected in how government processes were formed. The video below shows how the Estonian government advertises itself and what values they choose to highlight:

Should other countries adopt policies from Estonia? Of course, not everything is perfect in Estonia either. The fertility rate of 1.16 in Estonia is very low. This trend is present globally, but in Estonia it is way below the EU average. Also, the service culture is something that needs to improve in Estonia. While services are in general fast and efficient, the attitude of people working in cafes and stores does not reflect a willingness to fill in gaps if the standard process falls short, nor are visitors actively made to feel welcome as individual humans, but are treated as mere process inputs. However, many of the things listed earlier I think should be studied by policymakers elsewhere. Societies are complex systems and there is of course no guarantee that copying a single policy to another country with different ethnicities, history and ingrained culture would lead to the same policy outcomes. But considering that Estonia is a small country without favorable geography and no natural resources, and that it started out from a place of total chaos, low economic activity and high crime in 1992 to rise to what it is now in 2026, the success it has seen is surely largely a result of good policies, governance and culture that other countries can and should mimic.

You can construct an entropic argument that there are simply more ways for a harddrive to be full than ways in which it can be empty.

The other part of the equation is that a full disk isn t a problem until it s so full you can t put more stuff on it, and at the point it s so irredeemably cluttered that when you do clean it up, you only have the patience to clean up enough to bide your time, judging the fate of every file on the harddrive is simply too much work.

1. Any files that are stored in git-annex. This is one of git-annex's superpowers; you can git-annex drop any file and stop it using disk space, but the file is still there (as a broken symlink) so you don't risk losing or forgetting about it.
2. Caches.
3. Files in ~/tmp/, which is reserved for any files I only want to have a passing acquaintance with. If I'm not comfortable with something being deleted at any time, I don't put it there.

if (dir.exists(".git"))  
    ## development from a .git directory can use these flags
    xtraflags <- "-Wno-nonnull -Wno-deprecated-declarations"
  else  
    ## else build from tarball so stick with existing flags
    xtraflags <- ""
 
win <- if (Sys.info()[["sysname"]] == "Windows") ".win" else ""
infile <- file.path("src", paste0("Makevars", win, ".in"))
outfile <- file.path("src", paste0("Makevars", win))
lines <- readLines(infile)
lines <- gsub("@XTRAFLAGS@", xtraflags, lines)
writeLines(lines, outfile)

# PKG_CXXFLAGS initialized earlier ...

## Check if building locally
AC_MSG_CHECKING([whether .git/ exists])
if test -d "$srcdir/.git"; then
    AC_MSG_RESULT([yes, adding extra flags])
    AC_SUBST([PKG_CXXFLAGS],["$ PKG_CXXFLAGS  -Wno-ignored-attributes -Wno-maybe-uninitialized"])
else
    AC_MSG_RESULT([no, consider adding '-Wno-ignored-attributes -Wno-maybe-uninitialized' to ~/.R/Makevars])
fi

AC_SUBST([PKG_CXXFLAGS], ["$ PKG_CXXFLAGS "])
AC_CONFIG_FILES([src/Makevars])
AC_OUTPUT

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can now sponsor me at GitHub.