I don't really write about my job. Maybe I should.

The last 15 years as an IT analyst and systems administrator have taught me that anything requiring more complex implementation than what is strictly demanded by the technical limitations of a computer – anything requiring human judgment or restraint or empathy – will be considered extraneous when someone feels it can be automated by a system. This isn't necessarily a consequence of technology, or of any desire for efficiency. If efficiency were the real goal, computer systems could be an immense boon, due to the speed with which they complete math. We would have so much information, many means to analyze it mathematically in a variety of ways, and tons of resources to use when making human discernments.

But: information doesn't always make decision-making easier. Sometimes, it makes the decision immensely more complicated, because more information means more considerations and more awareness of the impact any one decision might make. There is such a thing as having too much information – information that obfuscates, information that distracts. A photography teacher I had in college referred to the process of burning and dodging as things you could only use when you had "the right amount of information" in your exposure. The process of photography is one of capturing information – information from the light and how objects in our environment intercept it. The nature of the light causes a chemical process to take place where the image is created, and the photographer makes the choice of how long to expose it, where to take the picture from, and what type of equipment and film to use. When you are burning or dodging to change the quality of light in some area of your photograph, you are manipulating the image, but you can only work with what was captured already – the information that you initially gathered. If you overexposed your sky, you instead see blown-out white instead of the texture of the clouds, and you can't use darkroom tricks to fix it. Nothing short of invention can bring it back. And that process makes the image no longer a photograph.

I wrote about the automations of photography as a measuring stick for "AI" three years ago. But there is another level to it, beyond automation and in regard to our understanding and perception of reality. Still photography takes information from the light, from the tangible world, and creates a depiction of just one moment in time. This ability is extraordinary – to create a single image of a moment in time that can be referred back to forever. Motion pictures are also extraordinary in this way, but the singular effect of a still photograph still fascinates me. Photographs can be duplicated as many times as we wish because of computers and the internet, so the significance of an original photographic print can feel diminished (even though I have some and I love them). This infinite duplication hasn't, to me, diminished the impact of photographic images themselves. This isn't to say that photographs can't be misleading, or depict something that didn't actually happen, or that there's any value-based distinction between photography as art or documentary or historical object. All photographs feel significant because they represent a single moment in the photographer's lived reality. Regardless of any technical "mistakes", misplaced intention, or misfiring of the shutter, the photograph exists and it can only contain the information that it was able to capture in that moment. If you accidentally take a picture of a subway platform while trying to stick your phone in your bag, you'll probably delete it. I would, I delete too. But damn, there's never going to be another photograph exactly like it.

But you delete it. You spend your life developing ways to understand what is important and what isn't. It's called becoming self-assured. Maybe when you were an insecure 12-year-old, you thought you had to like that band your friends liked even though you really hated that kind of music. You engage in a process of becoming. You develop political beliefs and principles. You try to get into relationships with people who delight you and value you and whom you likewise delight and value. You curate. You listen to the music you want to listen to even if someone else thinks it's corny or stupid. You learn to filter. You learn how to deal with different kinds of people. Sometimes you need to let it go. This choice to move on is significant, because it's also a kind of truth, a personal truth. You didn't like that novel. You didn't want to go on a date with her.

LLMs, "agentic AI" systems – they have trained on a body of data (text, images, code, videos) without any way of knowing what was important and what wasn't (because they cannot "know" anything, or experience anything). When this was "discovered" – the beautiful and somewhat obvious fact that there isn't a way to mathematize truth and falsehood, to make a determination about reality and which information is important to include based solely on algorithms – "AI" companies were not deterred. This is because their goals are not to provide truth. Certainly, machine learning can surface patterns in large data sets and these types of patterns can be used for analysis of information in those data sets. But the pattern is not a substitute for the analysis itself. This is what, to me, exposes the intention of "AI" companies with their LLMs and agents. They think that the analysis can be automated, that the understanding of the data and its meaning can be automated, that a discernment can be automated. The goal is not efficiency for the sake of getting things done. It is the very human goal of subjugation, and LLMs can make subjugation very efficient. They implicitly create conditions where discernment is taken from the "user" and thus from everyone impacted by their actions with the LLM. They do it with stolen information, stolen discernments, which were meant for the moments in time they took place in.

The LLM has access to every piece of information on Earth but it cannot provide truth, since information is not truth. The truth requires context and memory. Only you know that when a photograph was taken of you smiling, that you were having a terrible time. Only you know that later that night, you called a friend to complain about the terrible time you had, and felt better. Only you know the right amount of information. And the right amount of information is not a problem or question of efficiency.

The efficiency of information systems under capitalism means the speed with which they can be used to take money from other people. In imperial capitalism, it means taking money from people in new and inventive ways that undermine their ability to engage in self-determination.

As an IT professional, I have come to think of my job as a kind of translation. I translate technology products into solutions for business or educational needs, I translate computer programs for end users ("click the three dots to get to the Settings menu"), I translate technology concepts for everyone. In my job, at least, I don't always need to know the exact technical reason why something is the way it is – all I need to know is how to use it and how to implement it. I also need to know its shortcomings, what it's good for and what it's not good for, and how to troubleshoot it. This is the difference between a translator and a morphologist, maybe. A translator does not need to be a morphologist to be a good translator. But a certain level of expertise in both language and software makes this process grimmer by the day.

LLMs mimic language and code in a way that is apparently very convincing to a lot of people. It seems obvious that language is not language without intended meanings, without a framework for truth. Language works because each living, sensing creature on Earth has a sense of reality that they operate with. My cats and I do not speak the same verbal language, but it is a kind of language when I rub a cat's chest while he's sleeping, like I am right now as I write this.  A type of communication is taking place. LLMs, in fact, are a specific kind of machine learning that inherently does not have an idea of reality implemented by their designers – their function is to create synthetic language, whether it's American English, Microsoft Powershell, C++, or Mandarin Chinese. But synthetic language comes with its own set of problems – namely, nobody thought of it themselves or had intent when putting it out into the world.

So – increasingly as an IT professional, I am forced to work in environments that were not designed by people and were not intended to be used by people, but by "agentic AI." Allegedly, I am still translating, but the workload of translating and solution architecting has been drastically increased.

This is a fundamental shift in how software is being designed, how people use and encounter software, and how IT professionals have to support software, happening all at the same time and with little regard to how these things are actually progressing. If a user in my organization has a compromised account, I used to get a pretty straightforward email alert from Microsoft that the account had suspicious activity. Great – an automated monitoring system with a component of human oversight. I would click on the notification, see a list of "risky" users, and click on the user's name to get a list of their sign-in activity. Visually, a table of sign-in activity is great for an IT professional to ascertain whether a user's behavior is "normal" or not. Microsoft would automatically flag things like "atypical" or impossible travel (i.e. the user is probably not logging in from Philadelphia an hour before they're logging in from Chelyabinsk). It's pretty straightforward to look through these logs and make a determination if the sign-in is actually malicious. Sometimes, people use their personal VPN to watch anime in another country and log in to their school email at the same time. If the device details match a device they've used previously, it's not immediately cause for concern even if the IP address is from Seoul. But trying repeatedly to access an account via Azure CLI in Russia and repeatedly using bad passwords? Different issue. Actual threat. Conditional access policies help with this, but when you work with a lot of international users who access their accounts with personal devices, they can only go so far – you need a certain level of human involvement to secure the environment.

The ability to visually see this data was useful, and the recent updates to the Microsoft monitoring tools obfuscate the data – requiring more clicks and digging to get to the logs you actually want to see. I'm unsure who the dashboards are for. They are not for a person who understands the sign-in behaviors in their own environment. My organization might be small, but a lot of organizations our size or smaller also use Microsoft's tools. The tools have been created and designed not for individual human admins, but for huge organizations using "agents" to automate processes. Microsoft has decided that this is how their product works now. Those of us who use it, who have to work with it, did not get a say.

Microsoft says that implementing phishing-resistant authentication like passkeys by default will reduce this workload, and this is probably true. However, I think it also provides an opportunity to reflect at how we have changed or technological environments to be hostile to human beings and have only created interventions that increase and normalize the hostility.

Microsoft's Learn article about the implementation of passkeys by default is a defining document on this topic for me. The value proposition is to "help enterprises adopt AI at scale" rather than to provide a secure and safe experience for the human user or systems administrator. The baselines and defaults that Microsoft implements, with minimal transparency or forewarning to a busy IT admin, are fully designed for automated systems and not for human beings. This poses a significant problem to an IT administrator who wants to understand the systems they manage, make them work for their end users, and continue to translate the behavior of those systems to a person who may not understand the "why" and "how" of things like multifactor authentication or conditional access. All of us in the field understand that we have to learn on the job, adopt new systems on the fly, and implement necessary changes at times that are inconvenient or unreasonable – it's not ideal, but it is the reality of the job. But the tack that Microsoft is taking with "AI" adoption adds a pretty grave level of insult to the already-constant injury of being in IT support and systems administration. If you work at a small shop, you already manage a lot and it is increasingly difficult to keep up with Microsoft's mercurial and obscure changes to their internal systems.

Small shops are common and so are solo IT admins for relatively large organizations. The subreddit r/sysadmin is a daily vignette into IT professionals' protracted mental health crises. Alcohol abuse, depression, and anxiety are common topics. Workplace environments are often downright abusive towards IT, often as a side effect of simply not understanding the work people in the department are doing or why they do it. The common joke is that users and bosses question what the fuck they're paying IT to do regardless of whether things are going right or wrong. Regardless of whether things are broken or chugging along at status quo, we're invisible – unlike building maintenance, no one sees us coming in to fix the leak, and they might think we aren't doing anything if they haven't had to call us in awhile. Organizations generally don't want to spend money on in-house IT if they can help it, so they often contract with MSPs (managed service providers) to manage their environments – usually workers without a lot of experience who get thrust into managing virtual servers or Microsoft Entra for a company they might interact with once a month, in an environment designed by somebody who was probably laid off years ago or drank himself to death.

I wish I were being hyperbolic but I'm really not. Technical debt, infrastructure rot, and documentation gaps are common. There are companies and individuals running very tight ships with clean environments, great security practices, and excellent systems management processes. It's possible to do it on a shoestring, if you have the time and energy, but most of us do not. A good IT environment comes from investment in people, just like everything else in the workplace. You need robust staffing and clear processes, so people have time and incentive to do the necessary work of project management and change management without burning out and cutting corners. You need hardware – good hardware with good support, which is getting more and more expensive because "AI" data centers are taking all of our hardware and in many cases keeping it in a warehouse because the data center hasn't been built yet and may never be built (god willing).

As an IT professional, you need the time to document what you're doing, respond to end-user requests and problems, handle incidents, and come up with solutions to new questions which are posed to you daily. If you work in a small shop or as a solo admin, you have to do a little bit of everything, and your day is constant problem-solving, translation, and task-switching. LLMs and "agents" don't make this easier in any way and in fact make it a hell of a lot harder. Your environment is changing all the time, often without meaningful notice, because Microsoft thinks overworked IT admins the world over are their beta testers and QA team and that a line item in a blog post they wrote about the upcoming change eight months ago is the same as an emergency alert text that everybody read. LLMs are creating software exploits faster than vendors can patch them and companies like Anthropic can essentially hold the entire industry for ransom as a result, making Claude Code both the novel, fatal poison and the priceless antidote to everyone's security posture. The information both you and your end users receive from the Internet is increasingly unreliable and confusing.

In fact, there is an ever-escalating protection racket on the ability to use the Internet which is both monetary and skill-based. The raw Internet is essentially unusable and unsafe, which constantly assaults the user with deceptive advertising, malicious code, and outright scams. LLMs have made it possible to target individuals with zero-click exploits, delivered through code in webpage "advertisements." They can fake your child's voice on the phone, a federal warrant for your arrest, or an eviction letter from your landlord. Educating users about scams takes time, but is easier and more straightforward than having to explain how to use an adblocker, VPN or proxy service, password manager, and hardware-based multifactor authentication.

As a professional computer toucher, I get a little dopamine hit out of setting up my unique passwords or using my VPN on the coffee shop wifi, but to the average user, it's an obstacle course. Increasingly, the obstacles are in place as a deterrent to automated computer systems which are carrying out malicious actions on behalf of their faceless human operators, and this has an overwhelming, demoralizing effect – a sort of emotional death. Nobody in a position of power seems to meaningfully care about how LLMs are enabling scammers and malicious actors, because the protection racket is the point, the ongoing process of enclosure to ensure that our communication and information diets are fully managed and surveilled, and vulnerability is the natural consequence of mass, blanket surveillance. When the tactics required to avoid surveillance are inaccessible to the vast majority of people, it doesn't really matter how much you as an individual try to protect yourself. You're in the general population. You are vulnerable, too. There are eight Flock cameras within two blocks of my house. Any computer I operate that is connected to the Internet is more vulnerable to undisclosed exploits than ever. This is why prompt fondlers are doomsday prepping – because the simple solution of "not operating a platform that allows any motherfucker in the world to LARP as a pen tester on production systems at unprecedented speeds" hasn't occurred to them.

IT professionals charged with keeping businesses and institutions operational do not have the time, bandwidth, or emotional energy to manage the devastation that is being wrought on our systems and users. IT departments are almost as a rule under-resourced and under-staffed, even ones that generally operate very well, because they are seen as a cost center and not an investment. Most of us in the industry are usually one bad week away from a full-blown mental health crisis. Users think we control the environment, but we really don't – we merely hold the beasts back from the door, with varying levels of success. It can be rewarding work, but those moments of true satisfaction are fewer and farther between. It's in the little things, of course – learning the correct syntax for a script that helps me deploy software, or teaching someone how to properly format their mail merge for envelopes. All of these things work better when the person doing them understands what is actually happening. The tech industry wants all of us using an LLM instead for these tasks, and in fact wants it to be mandatory. I find that proposition antithetical to the idea of the computer as a tool for humans – which makes sense, since it comes from a vision and worldview which seeks only to subjugate.

I went to school to study writing but ended up in the IT department because I was the girl teaching herself CSS, installing her own wireless adapter in her iBook, and watching TechTV for hours every day after school, and it turned out that this is something I'm good at that has become an actual career. I didn't have to hustle for it in a way that felt abstract. The only career advice I ever got about writing in college was that I had to send pitches, and because I started college during the 2008 financial crisis and at a time when digital media was rapidly accelerating and thus adopting a digital-advertising-based economy, the process of pitching and getting writing jobs on the merit or strength of your work had, almost overnight, become obsolete. The reactionary movement that has completely taken over our economy and politics in the United States was already seeded and healthily germinating. I started a hockey fan blog in 2008 from my dorm room at the corner of Boylston and Tremont Streets in Boston, the year after Barstool Sports launched its website in the same city. I knew I wasn't going to be able to pay rent by placing short stories in literary journals, and I quickly learned that writing about sports wouldn't work as a real job, either (even though I did it for more than a decade at great personal expense). With writing, it was never about whether I did it well, but whether it "fit" what someone was "looking for", and it seemed like "what the editor was looking for" was an abstract concept that I didn't want to be responsible for knowing or answering to.

In IT work, I could show up to a job interview and demonstrate that I understood the technical concepts and also apparently have a natural talent for talking to users and explaining technical concepts in non-technical terms. I'm also a really, really good problem-solver and can usually figure out why something isn't working in a managed environment. I write good documentation. I can talk through workflows with people and figure out what makes the most sense for them and help them make that workflow as easy as possible. At the root of that process is trying to make the user understand what it is that they are doing, because by understanding, they form habits that are based in a theory of reality. LLMs make maintaining this type of reality-based skillset impossible whether you use them or not, because they are fracturing our understanding of reality in real time. They greatly increase the emotional labor of IT work, and make my skillset inefficacious in the face of constant unplanned and untested changes.

The "efficiency" proposition falls flat when the only thing LLMs have really increased in my own world is the rate of break-fix interactions and changes. Documentation I created for my users about how to do something in Teams that Microsoft doesn't meaningfully document themselves becomes outdated within weeks. Patches for load-bearing systems (like the firewall or network access controller) that end users never actually interact with have to be installed with minimal preparation. Everything is frantic, immediate, and abstract. You have to make quick adjustments and you pass the frustration on to your users, no matter how much you don't want to, because you're not the one who made or necessitated the change – and it's not even Microsoft, or your Linux distro, or your boss, or your boss's boss who are to blame. It's the fucking LLM. It's the Silicon Valley assholes and their effective-altruist sex cult. And none of them care that the rest of us have to get up every fucking day and go to work.

There is no grace or dignity in this work anymore. No matter how many sandbags you throw down, the water only rises; you are told you need to be using an LLM to keep up; you will be "left behind." The surrender expected of you feels enormous. To some, I bet it does feel like a relief to be completely irresponsible for whatever happens next, because it will be automated and mediated. To me, it feels like a type of suicide. I'm not disabused of this notion by evaluating the professional community's mood online, or in my own office. Most of us love problem-solving – but these are no longer problems posited by a real, lived, human environment. It's just fighting against accelerationism for which no one will claim responsibility, and which is described as both "inevitable" and "necessary" by tech executives who do not generally participate in polite, civil society with normal people and invariably have some kind of connection to eugenics or Nazism.

The technology industry as a whole is wildly unregulated, and requires no formal education, professional certification, or ethics training to enter – and certainly not to advance. We live in a society and economy that promotes and values the loudest person in the room rather than the most thoughtful or the most skilled, and this is nowhere truer than in Silicon Valley. There is little public interest in the technical underpinnings of our global networked infrastructure and many pieces of critical and common software are maintained and documented in part or in whole by volunteers. The best systems management tools and documentation I have encountered in my professional career are provided open-source and for free. The people who actually do the work in this space are some of the most generous, brilliant, and thoughtful people alive. Many of them are even using LLMs to work with coding now – but this only works well for them because they already have the foundational skillset to understand what good code looks like. I don't know where my career will be, if I still have a career, when the people who maintain these codebases age out of the industry and retire to an off-grid cabin in the Canadian wilderness, which I imagine many of them will do and increasingly seems like the only reasonable path forward.

With LLMs, people have already, quite willingly, stopped learning how to do things, and the idea of "learning how to do something" and "teaching someone else how to do something" is the only reason this job is even worth having. Otherwise, I'm translating nothing into nothing for no one, because whatever information I'm trying to make sense of simply gets drowned out in a cacophony of instant gratification. To return to the photograph: the clouds can no longer be described as overexposed or missing due to too much light in the exposure. Your memory of them being there is irrelevant. The clouds were never there.