#document management software. workflow software

Step One: Install Calibre

Calibre is an incredibly powerful ebook management software that allows you to do a whole lot of stuff having to do with ebooks, such as convert almost any text-based file into an ebook and (often) vice-versa. It also allows you to easily side-load ebooks onto your personal e-reader of choice and manage the collection of ebooks on the device.

And because it's open source, developers have created a bunch of incredibly useful plugins to use with Calibre (including several we're going to talk about in the next step), which make saving and reading fanfiction super easy and fun.

But before we can do that, you need to download and install it. It's available for Windows, MacOS, Linux, and in a portable version.

Step Two: Download These Plugins

This guide would be about 100 pages long if I went into all of the plugins I love and use with Calibre, so we're just going to focus on the ones I use for saving and reading fanfiction. And since I'm trying to keep this from becoming a novel (lolsob), I'll just link to the documentation for most of these plugins, but if you run into trouble using them, just tag me in the notes or a comment and I'll be happy to write up some steps for using them.

Anyway, now that you've downloaded and installed Calibre, it's time to get some plugins! To do that, go to Preferences > Get plugins to enhance Calibre.

You'll see a pop-up with a table of a huge number of plugins. You can use the Filter by name: field in the upper right to search for the plugins below, one at a time.

Click on each plugin, then click Install. You'll be asked which toolbars to add the plugins to; for these, I keep the suggested locations (in the main toolbar & when a device is connected).

FanFicFare (here's also a great tutorial for using this plugin) EpubMerge (for creating anthologies from fic series) EbubSplit (for if you ever need to break up fic anthologies) Generate Cover (for creating simple artwork for downloaded fic) Manage Series (for managing fic series)

You'll have to restart Calibre for the plugins to run, so I usually wait to restart until I've installed the last plugin I want.

Take some time here to configure these plugins, especially FanFicFare. In the next step, I'll demonstrate a few of its features, but you might be confused if you haven't set it up yet! (Again, highly recommend that linked tutorial!)

Step Three: Get to Know FanFicFare (and to a lesser extent, Generate Cover)

FanFicFare is a free Calibre plugin that allows you to download fic in bulk, including all stories in a series as one work, adding them directly to Calibre so that that you can convert them to other formats or transfer them to your e-reader.

As with Calibre, FanFicFare has a lot of really cool features, but we're just going to focus on a few, since the docs above will show you most of them.

The features I use most often are: Download from URLs, Get Story URLs from Email, and Get Story URLs from Web Page.

Download from URLs let's you add a running list of URLs that you'd like FanFicFare to download and turn into ebooks for you. So, say, you have a bunch of fic from fanfic.net that you want to download. You can do that!

Now, in this case, I've already downloaded these (which FanFicFare detected), so I didn't update my library with the fic.

But I do have some updates to do from email, so let's try getting story URLs from email!

Woohoo, new fic! Calibre will detect when cover art is included in the downloaded file and use that, but at least one of these fic doesn't have cover art (which is the case for most of the fic I download). This is where Generate Cover comes in.

With Generate Cover, I can set the art, font, dimensions, and info content of the covers so that when I'm looking at the fic on my Kindle, I know right away what fic it is, what fandom it's from, and whether or not it's part of a series.

Okay, last thing from FanFicFare -- say I want to download all of the fic on a page, like in an author's profile on fanfic.net or all of the stories in a series. I can do that too with Get Story URLs from Web Page:

The thing I want to call out here is that I can specify whether the fic at this link are individual works or all part of an anthology, meaning if they're all works in the same series, I can download all stories as a single ebook by choosing For Anthology Epub.

Step Four: Using FireFox Reader View to Download Fic Outside of Archives

This is less common now thanks to AO3, but the elders among us may want to save fanfic that exists outside of archives on personal websites that either still exist or that exist only on the Internet Wayback Machine. FanFicFare is awesome and powerful, but it's not able to download fic from these kinds of sources, so we have to get creative.

I've done this in a couple of ways, none of which are entirely perfect, but the easiest way I've found thus far is by using Firefox's Reader View. Also, I don't think I discovered this -- I think I read about this on Tumblr, actually, although I can longer find the source (if you know it, please tell me so I can credit them!).

At any rate, open the fic in Firefox and then toggle on Reader View:

Toggling on Reader View strips all the HTML formatting from the page and presents the fic in the clean way you see in the preview below, which is more ideal for ebook formats.

To save this, go to the hamburger menu in the upper right of the browser and select Print, then switch to Print to PDF. You'll see the URL and some other stuff at the top and bottom of the pages; to remove that, scroll down until you see something like More settings... and uncheck Print headers and footers.

Click Save to download the resulting PDF, which you can then add to Calibre and convert to whichever format works best for your e-reader or archive method.

Step Five: Archiving (Choose Your Own Adventure)

Here's the really fun part: now that you know how to download your fave fanfics in bulk and hopefully have a nice little cache going, it's time to choose how you want to (privately) archive them!

I'm going to go through each option I've used in order of how easy it is to implement (and whether it costs additional money to use). I won't go too in depth about any of them, but I'm happy to do so in a separate post if anyone is interested.

Option 1: On Your Computer

If you're using Calibre to convert fanfic, then you're basically using your computer as your primary archive. This is a great option, because it carries no additional costs outside the original cost of acquiring your computer. It's also the simplest option, as it really doesn't require any advanced technical knowledge, just a willingness to tinker with Calibre and its plugins or to read how-to docs.

Calibre comes with a built-in e-book viewer that you can use to read the saved fic on your computer (just double-click on the fic in Calibre). You can also import it into your ebook app of choice (in most cases; this can get a little complicated just depending on how many fic you're working with and what OS you're on/app you're using).

If you choose this option, you may want to consider backing the fic up to a secondary location like an external hard drive or cloud storage. This may incur additional expense, but is likely still one of the more affordable options, since storage space is cheap and only getting cheaper, and text files tend to not be that big to begin with, even when there are a lot of them.

Option 2: On Your e-Reader

This is another great option, since this is what Calibre was built for! There are some really great, afforable e-readers out there nowadays, and Calibre supports most of them. Of course, this is a more expensive option because you have to acquire an e-reader in addition to a computer to run Calibre on, but if you already have an e-reader and haven't considered using it to read fanfic, boy are you in for a treat!

Option 3: In BookFusion

This is a really cool option that I discovered while tinkering with Calibre and used for about a year before I moved to a self-hosted option (see Option 4).

BookFusion is a web platform and an app (available on iOS and Android) that allows you to build your own ebook library and access it from anywhere, even when you're offline (it's the offline bit that really sold me). It has a Calibre plugin through which you can manage your ebook library very easily, including sorting your fanfic into easy-to-access bookshelves. You may or may not be able to share ebooks depending on your subscription, but only with family members.

Here's what the iOS app looks like:

The downside to BookFusion is that you'll need a subscription if you want to upload more than 10 ebooks. It's affordable(ish), ranging from $1.99 per month for a decent 5GB storage all the way to $9.99 for 100GB for power users. Yearly subs range from $18.99 to $95.99. (They say this is temporary, early bird pricing, but subscribing now locks you into this pricing forever.)

I would recommend this option if you have some cash to spare and you're really comfortable using Calibre or you're a nerd for making apps like BookFusion work. It works really well and is incredibly convenient once you get it set up (especially when you want to read on your phone or tablet offline), but even I, someone who works in tech support for a living, had some trouble with the initial sync and ended up duplicating every ebook in my BookFusion library, making for a very tedious cleanup session.

Option 4: On a Self-Hosted Server Using Calibre-Web

Do you enjoy unending confusion and frustration? Are you okay with throwing fistfuls of money down a well? Do you like putting in an incredible amount of work for something only you and maybe a few other people will ever actually use? If so, self-hosting Calibre-Web on your own personal server might be a good fit for you!

To be fair, this is likely an experience unique to me, because I am just technical enough to be a danger to myself. I can give a brief summary of how I did this, but I don't know nearly enough to explain to you how to do it.

Calibre-Web is a web app that works on top of Calibre, offering "a clean and intuitive interface for browsing, reading, and downloading eBooks."

I have a network-attached storage (NAS) server on which I run an instance of Calibre and Calibre-Web (through the miracle that is Docker). After the initial work of downloading all the fic I wanted to save and transferring it to the server, I'm now able to download all new fic pretty much via email thanks to FanFicFare, so updating my fic archive is mostly automated at this point.

If you're curious, this is what it looks like:

Pros: The interface is clean and intuitive, the ebook reader is fantastic. The Discover feature, in which you are given random books / fic to read, has turned out to be one feature worth all the irritation of setting up Calibre-Web. I can access, read, and download ebooks on any device, and I can even convert ebooks into another format using this interface. As I mentioned above, updating it with fic (and keeping the Docker container itself up to date) is relatively automated and easy now.

Cons: The server, in whichever form you choose, costs money. It is not cheap. If you're not extremely careful (and sometimes even if you are, like me) and a hard drive goes bad, you could lose data (and then you have to spend more money to replace said hard drive and time replacing said data). It is not easy to set up. You may, at various points in this journey, wish you could launch the server into the sun, Calibre-Web into the sun, or yourself into the sun.

Step Six: Profit!

Nearly 10 years after the Defense Department launched Project Maven to apply machine learning to analyzing drone video feeds, AI technology has profoundly evolved, as have its military applications.

Narrow AI applications, such as identifying and tracking objects, are integrated into U.S. operations. The U.S. military has begun using large language models, including on its classified networks. In a fluid and dynamic battlefield environment, such as in U.S. operations against Iran, AI can help process large amounts of information and plan operations at a much faster tempo than humans could on their own.

General-purpose AI systems have a wide range of applications, from drafting personnel reports and orders to synthesizing massive amounts of data. They can write code, analyze data, and generate documents. Agentic systems go a step further. They can take actions on computers to create, organize, and delete files; manage steps in a workflow process; build software; engage on the internet; and interact with other agents. Yet the limitations and vulnerabilities of these general-purpose AI systems are especially concerning in a national security context, where decisions could have major consequences and clever adversaries will try to undermine AI systems.

All technologies have limitations that militaries must account for in their employment. Every capability has countermeasures, and there are counter-countermeasures. AI is no different. As a relatively immature technology, AI systems suffer from two compounding problems. AI is not (yet) very reliable, especially for military applications for which there may not be sufficient training data. And because AI scientists and military professionals don’t (yet) have much experience with these tools, developers and users may not understand the boundaries of where AI systems will perform well and where they will fail.

These problems are exacerbated by a challenge unique to AI—its opacity. Large language models rely on neural networks with hundreds of billions of connections. They are trained on massive datasets of trillions of words. If an airplane autopilot fails, it is possible to go through the aircraft’s code and determine which environmental or pilot inputs caused a certain reaction by the autopilot and how that led to a crash. For a large language model, the answer to why the model generated certain text is embedded in the billions of connections of the neural network and the trillions of words in its database.

This is a problem because large language models are prone to a variety of failure modes. They often engage in “hallucinations,” confidently making things up. They can be susceptible to biases that may exist in their training data. And language models tend toward sycophancy, over-agreeing with their user to a fault. These failures could crop up in dangerous ways in national security applications. Language models that are processing information could get subtle but important details wrong that might be missed by a human overseeing their output. Models that are generating text might create false information. AI tools used by intelligence analysts to understand and process intel might unintentionally reinforce the biases of human analysts, adding machine-driven sycophancy to the human risk of confirmation bias—the seeking out of information that confirms preconceived ideas. Even if AI systems deliver correct information, their opacity itself could be a challenge if humans are not able to understand why an AI system came to a certain conclusion or recommended a course of action.

AI systems also open new avenues for attackers. Adversaries can manipulate AI systems in a variety of nefarious ways. Data-poisoning attacks subtly alter the training data (including in ways that cannot be detected) to implant backdoors into an AI system that can later be exploited. Adversarial attacks expose AI systems to manipulated data while they are in use, causing AI systems to fail or change their behavior. This could lead AI systems to misidentify targets, come to faulty conclusions, or allow adversaries to evade AI detection. In one experiment, attackers placed stickers on a test track—like cognitive landmines—to trick a Tesla into swerving into the oncoming lane. Large language models can be manipulated by prompt injection attacks that expose the model to malicious instructions. Malicious text in an email or intercepted enemy communications could cause a model to ignore previous instructions and instead follow directions from an attacker.

AI agents raise even greater risks. They can have a larger attack surface, since the agent may be interacting with untrusted data, including in some cases operating on the internet. And the consequences of an AI agent being suborned by an attacker could be more severe, since the agent will be taking actions on a computer or as part of a workflow. Security researchers have compromised a language model’s memory feature through the AI system visiting an untrusted website with malicious instructions. Inserting instructions into the memory gives attackers persistent access, which security researchers have used to exfiltrate data. Security risks can even propagate from agent to agent. In one experiment, researchers found that a single compromised agent could spread an infection exponentially through a network of up to a million agents as they interacted with one another. AI agents and networks of agents will be vital tools for militaries but introduce new security vulnerabilities that no one is prepared for.

AI security vulnerabilities are analogous to cyber vulnerabilities, but they work at the cognitive level of how an AI system is trained or processes information. They are perhaps closer to optical illusions or human cognitive biases but exist in alien machine intelligences that we do not fully understand. Robust defenses do not yet exist. These vulnerabilities are not a reason to forgo AI. Instead, militaries must prioritize security as they adopt AI. AI adoption must go hand in hand with developing standards, testing, and red-teaming AI systems to ensure that they are secure and reliable. Security cannot be an afterthought, as it too often is in cyberspace.

Perhaps the strangest risk is the possibility that an AI system might, on its own, decide to deceive or scheme against its developers or users. Such a scenario might seem like science fiction, but AI systems have demonstrated deceptive behaviors in experimental settings. These include sandbagging performance on evaluations when the AI system believes it is being observed, lying to users in order to accomplish its goals, attempting to blackmail users, and attempting to overwrite files or exfiltrate itself in order to avoid being deleted.

Skeptics of the risks of a “rogue AI” have sometimes asked why an AI system would decide to turn on humans. Yet it seems that if an AI system’s directives come into conflict—for example, if an AI system is told to accomplish a goal and to always be honest—under some conditions the AI system will act dishonestly to achieve its goal. Whether the AI system “intends” to deceive or is merely playing a role is an irrelevant philosophical question. The AI system’s behavior is strategic, deceptive, and goal-oriented, and can lead AI systems to work against human users. Even evaluating AI systems for this behavior is tricky because the most capable models exhibit enough situational awareness to know when they are being tested. External evaluators of Anthropic’s Claude Opus 4.6 observed Claude verbalizing awareness that it was being tested, leading the human evaluators to end the test early, since there was not much evidence that could be gained about Claude’s degree of alignment from the test. Militaries and intelligence communities guard against insider threats from people, and they may need similar protections against “AI insider threats” in the future.

None of these risks is a reason to halt AI adoption. Artificial intelligence will transform warfare, and the U.S. military must find ways to harness AI for military advantage to stay ahead of competitors. AI technology proliferates extremely rapidly. Open-source models, many of which come from Chinese companies, lag state-of-the-art U.S. proprietary models by only three months. It takes years for militaries to adopt AI technology and effectively transform military operations, making the sliver of a lead that U.S. frontier labs have over Chinese competitors effectively meaningless from the standpoint of military AI. The U.S. and Chinese militaries are competing on a level playing field. The military competition in AI is not over which nation’s private sector is a few months ahead, but over which military is most effective in harnessing AI for battlefield advantage.

Of course, speed matters. The Department of Defense AI strategy released in January 2026 overwhelmingly emphasizes moving quickly, and the current Pentagon leadership is rightly focused on bulldozing bureaucratic obstacles to AI adoption. Yet history shows that merely putting new technology in the hands of warfighters is never enough to transform military operations. Military advantage comes from finding the best ways of using new technology, and changes in doctrine, organization, training, and culture are needed to fully reap the benefits of disruptive new technologies. If the U.S. military uses AI to merely do what it is already doing but better, that will be helpful, but it will miss out on the true benefits of AI, which lie in doing things differently.

The Pentagon needs to work with the companies that are developing this technology to understand the limitations of AI today and use it effectively. The relationship between Washington and Silicon Valley has been badly damaged by the public feud between Anthropic and the Pentagon. Defense leaders are right that the rules for using military AI should be set by government leaders who are accountable to the public rather than for-profit companies that are accountable to investors and shareholders. AI leaders are also right to point out that large language models are not reliable enough to be trusted with life-and-death decisions on their own and that AI presents novel risks of empowering domestic mass surveillance.

If the Pentagon and Anthropic can’t agree on the terms of use for Anthropic’s AI models, both parties are free to end the relationship. The government has the right to seek a contract that does not include restrictions on use. And private companies have a right not to do business with the government if they don’t agree. Given that senior defense leaders have said they want to use Anthropic’s AI tools and that Anthropic CEO Dario Amodei has said he wants to sell to the military, there should be room for common ground. Instead, Pentagon leadership has retaliated against Anthropic by designating it a “supply chain risk,” an unprecedented step against a U.S. company that has already been blocked by a court order.

Alienating the AI community is not an effective strategy for bringing AI into the military. There is simply no way for the U.S. military to adopt cutting-edge AI technology without working constructively with the people and companies who are building AI. After a similar public breakup between Google and the Defense Department over Project Maven nearly a decade ago, the Pentagon went on a charm offensive, engaging AI scientists in industry and academia to hear their concerns. The resulting military AI ethics principles not only helped to repair the breach with the AI community but improved the military’s use of AI by highlighting the importance of ensuring systems were robust, reliable, and trustworthy.

Current state-of-the-art AI systems raise even more challenging problems, and the military will need help from AI researchers to solve them. It is vitally important that the military understand AI’s limitations and failure modes so the military can use it reliably.

Accelerating AI adoption won’t work if the Pentagon doesn’t accelerate its AI assurance processes in parallel. Speed without reliability is worthless. If warfighters don’t trust AI, they won’t use it. In 2003, after Army Patriot air and missile defense systems shot down two friendly aircraft, the military effectively took it offline for the remainder of the Iraq invasion. The military will need to develop new evaluations, standards, benchmarks, and red-teaming of AI systems to better understand and mitigate AI’s limitations and vulnerabilities.

The Defense Department has approached AI and autonomy with a philosophy of “human-machine teaming,” seeking the best ways to optimally use the unique advantages of humans and machines. Some of the Pentagon’s recent steps, such as the launch of GenAI.mil in December 2025, which provided access to large language models for all Defense Department employees on unclassified networks, and the integration of AI tools on classified networks through the Maven Smart System, are excellent ways to build up human experience with AI systems. The more that military and civilian defense personnel interact with AI systems, the more they will mature their intuition for what AI can do and its limitations.

Why My Windows Laptop Wins Every Time

Multitasking Like a Pro iPads have some multitasking capabilities, but let's be real—nothing beats having multiple windows open, side by side, without limitations. On my laptop, I can have a research paper in one window, my notes in another, a video playing on the side, and Spotify running in the background. Try doing that on an iPad without constantly swiping between apps. It’s just not the same.

File Management That Actually Makes Sense The Windows file system is superior. Hands down. Drag-and-drop functionality, proper file explorer, external drive support—it’s just easier. iPads, on the other hand, have a clunky file system that often makes me want to scream into the void. Copying files? Moving them? Finding them again? It takes way longer than it should.

Software Compatibility & Heavy-Duty Programs This one’s a dealbreaker. There are so many professional-grade applications that just don’t run on iPads. Things like:

Adobe Premiere Pro for serious video editing (iPad versions are limited)

Photoshop & Illustrator (yes, they have mobile versions, but they’re nowhere near as powerful)

Microsoft Excel with Macros (because let's be honest, the iPad version is lacking)

Programming software & full IDEs (if I ever decide to code, my iPad will just sit there, useless)

Mouse & Keyboard Freedom Yes, iPads can connect to a mouse and keyboard, but do they truly function like a laptop? Nope. There are still weird limitations. Right-clicking? Custom shortcuts? The precision of a real trackpad or external mouse? Windows just does it better. Period.

Downloading Anything Without Jumping Through Hoops iPads don’t let you download everything you want, especially if it’s outside the App Store. Need a program that isn’t on Apple’s list of approved software? Too bad. Meanwhile, on Windows? I can download whatever I want, whenever I want, however I want. No restrictions.

Serious Writing & Formatting Writing on an iPad is fine for quick drafts, but when it comes to formatting long documents, citations, and exporting files in different formats? My laptop is my best friend. Whether it's proper PDF editing, running reference managers like Zotero, or managing multiple Word documents with complex layouts, iPads just don’t cut it.

Gaming & Emulation Okay, maybe not work-related, but still important! iPads have mobile games, sure. But do they run full-fledged PC games? Nope. Can I use them for game modding? Nope. Can I play older games with emulators? Again, nope. My Windows laptop, on the other hand? Unlimited possibilities.

The Verdict?

As much as I love the convenience of my iPad + keyboard combo, it will never replace my laptop. Ever. My laptop is where the real magic happens—the deep work, the serious projects, the things that actually require a proper computer.

But will I still use my iPad for writing on the go? Absolutely. Because nothing beats the clickity-clackity joy of my new keyboard. And if that keeps me weirdly motivated to write, then hey—I’ll take it.