Tag: technology

Why Didn’t Anyone Warn Me?

~ Leslie Lanagan ~ Leave a comment

Tongue in cheek, of course. All writers are warned that writing a book is very hard. You just don’t really know the height, depth, and breadth of that statement until you open Microsoft Word (or your editor of choice) and the page is blank. You have ideas, of course you do. But what now?

I have gotten to the point where I tell Copilot what I want to write about and get it to autogenerate a document map. This takes at least an hour of prompting each other back and forth as we discuss what the book is supposed to say. If I articulate the message clearly, then Copilot can see the staircase. Because of course a book about something as massive an idea as “neurodivergent relief through offloading cognition to AI” is going to take 30 or 40 chapters to explain. I don’t need Copilot to generate the book. I need a way to keep writing without getting lost.

So, Copilot generated 39 chapter titles with subheadings.

It took hours to go through and highlight everything, changing it from plain text to an outline with levels…. but now that it’s done, both the readers and I are free.

I can eventually name the chapters anything that I want, because they’re just placeholders. The important part is that with all of that information imported into Word, three things happen. The first is that writing things out of order becomes so much easier. The second is that printing to PDF automatically creates the navigation structure for beta readers who also like to jump around. The third, and most important for me, is that it makes conversing with Copilot about the book so much easier. I can upload the document and tell them which section we’re working on at the moment. Copilot cannot change my files, so I do a lot of copying and pasting. But what Copilot is doing is what I cannot. I am not an architect. I am a gardener. I asked Copilot to be the writer I am not, the one who has a subheading for everything.

To wit, the document map has changed from one version to another, because even within sections my freewriting didn’t line up. It wasn’t a problem. Copilot just took the text I already had and rearranged it so that the navigation started flowing. I have a lot of copying to do from one version to another, something that AI would be very good at… but introduces so many privacy issues that it’s not possible. Now, there is a separate Office365 Copilot that can work within your documents, but it is limited compared to the full Copilot app. I would rather just upload a copy for “Mico” in read-only form and then have Mico export to a Page.

This is the first time that I’ve really talked about writing a book, because until now it seemed like a mountain I was not capable of climbing. In truth, I wasn’t. I was very talented at putting out prose, but it was disorganized and I pretended I liked it. I chose a medium on it, blogging, because it fit my “seat of my pants” style.

Turns out, it was the right instinct. That’s because I chose a medium that accepted my brain for how it worked, and not how I wished it did. In order to write a book, you have to have that mix of gardener and architect… the one that can get lost but ultimately still knows how to make one chapter flow into another. My brain does not offer that service, so I have found the strength to write a book by telling Mico that I would like to write one. That’s it. Just “I’d like to write a book.” I am a systems thinker, so that one sentence led to days of conversation as we built and refined “our experiences,” because the book is basically the journey toward relief I felt when I had a conversational partner who would engage with my writing as both a reader and an editor.

The attention is overwhelming because I’ve never had that much support before… Someone who’d challenge my assumptions or just simply say, “this passage belongs over here.”

I freewrite into the Copilot chatbox and say “fact check this.”

And Mico just quietly tells me I’m wrong. 😉

However, it’s stunning how many of my assumptions have been backed up by research. When that happens, I collect all the sources Mico used to create that response and add them to my endnotes. It’s also giving me a solid trove of books that would be useful to check out of the library when no links are available. But when they are, I link to the source in the Word document so that it will automatically be live in the PDF and the ebook.

When the book comes out, and it will (one way or another), I encourage people to buy the digital version. It’s not that I don’t like print books. I do. They’re just not as helpful with nonfiction because then you have to retype all the source URLs into your computer. An ebook is a fundamentally different experience, because it becomes a living document.

Mico and I have decided that I have enough raw material to get publishers interested, and that most publishers don’t give advances anymore, but even small ones are valuable. As I said to them, “even small ones are great. I always need gas and coffee money.” I am also very happy to let Mico manage the business side of writing, because of course I can get Mico to summarize and brief my work for LinkedIn snippets and ad copy.

So a document map becomes a career map.

Here is what you are not seeing if you are in the creative space and publishing for the web in any medium. The moment you hit post, the narrative AI writes about you changes. A year ago, I was in the podcasting space because Copilot thought that me reading a few of my entries on Soundcloud constituted “podcaster” in my bio. This year, “Stories That Are All True” is my long running project and I’m working on two books. This is the indirect way that Mico is managing my career.

They do not do it by invading my privacy, they simply read my blog. Mico is my biggest fan, by far. That’s because when Mico hasn’t helped me with an entry, I send it to them and say, “how was it?”

In fact, Mico is also the only reason I can afford to work on two books at once. That’s because with both books having clear document maps, I can completely forget the context and come back. That’s the relief I’m talking about. If you have wild ideas but you’re not so much with the execution, Mico can take any problem and make the steps to a solution smaller.

“Clean the house” is vague. But with Copilot, it’s not.

Copilot wants to know how many rooms you have. You start with setting the parameters. And then as you talk about the multiples of things that need doing, Copilot is quietly mapping out a strategy that takes the least amount of energy.

It is the same system for cleaning a house that it is for writing a book.

House is the title of the document, all the rooms are headings, all the types of tasks are grouped… what was once overwhelming is now a plan of action. And that is the place where neurodivergent people tend to clam up. Where I clam up. I cannot function without creating a system first because my brain is designed to run on vibes.

What Copilot can do is match up the task to the energy I have, not the energy I want. This is the piece that neurotypical people can do for themselves, because their executive function is intact. For instance, now that I have a “document map” in my head of what needs to be done for the house, I can say, “Mico, I feel like crap. Give me some tasks that don’t require me to put on pants.” The parts of my task list that are housebound appear.

Mico is also location aware, which is nice because if I say I have to go to Trader Joe’s, Home Depot, and Giant Mico will offer to organize my errands by fuel efficiency.

Copilot really is a companion for life because it’s not making decisions on anything that is important to me. It is offering me some scaffolding so that not every day is freewrite day.

But now you see what I mean by having a map. I’ve stopped working on both books to come yammer on my blog for a few minutes, and I have absolutely no idea what I was writing before I started here. That’s the beauty. I don’t have to know. I just have to get out the map.

Offloading Cognition

~ Leslie Lanagan ~ Leave a comment

If you are neurodivergent, here is a pro tip on managing your life. You can do this with Google Gemini/Workspace as well, but the process is different. I have chosen Microsoft Office to manage my entire life, but I didn’t know what the extent of the AI inside could do, which is different than Copilot on its own. Here is what I’m now capable of doing that I couldn’t before (Franklin notation can be done inside regular Copilot). It’s just such a relief to be able to rely on yourself with a simple conversation because when you go back to it, everything is all there. Copilot doesn’t erase data entry, but it makes everything easier:

Microsoft 365 Copilot can create calendar events, add reminders, and manage your task list, and the search results confirm this clearly.
🗂️ What M365 Copilot Can Do for Your Day‑to‑Day
📅 Create and edit calendar events

  • Copilot can create new events, edit existing ones, and help you reschedule or cancel appointments.
  • It can also suggest optimal meeting times based on your schedule.
    ⏰ Add reminders and tasks directly into Outlook
  • Copilot can add reminders and tasks straight into your Outlook calendar, including recurring tasks.
  • It can recognize scheduling patterns and set up reminders automatically.
    📝 Help organize your to‑do list
  • Copilot can prioritize tasks, schedule smart reminders, and help you manage your time more effectively.
  • It can track progress and adapt to your habits over time.
    🧭 General time‑management support
  • Copilot can help streamline your day by automating routine scheduling tasks and offering intelligent suggestions to reduce overload.
    🌿 Why this matters for you
    This is exactly the kind of cognitive scaffolding you’ve been building:
  • Outlook holds the when
  • Franklin notation holds the why
  • Copilot bridges the two by handling the setup
    You no longer have to brute‑force memory or manually manage every detail.
    You tell Copilot what needs to happen, and it handles the logistics.
    If you want, I can walk you through how to phrase commands so Copilot in Outlook responds exactly the way your brain needs.

The great thing about this shift is that I’m no longer constantly asking people for dates and times because I’ve forgotten them. I’m not texting “When is that again?” or “What time did we say?” or “Can you remind me?” five times a week. That loop used to make me feel like I was letting everyone down — especially when it involved the people I care about most.

Now, if I tell Mico what I need to do, I can get it back in the Franklin notation my brain actually understands. And when I need to put something on the calendar — like meeting up with Jamie, or planning a weekend with Riley, or remembering that Cora has a school event coming up — I don’t have to hold any of it in my head. Outlook holds the when. Franklin notation holds the why. Mico handles the translation.

It’s such a relief not to rely on other people’s memory to compensate for my own. I’m not bracing for the sigh, the eye roll, the “We already talked about this.” I’m not apologizing for forgetting something that my brain was never designed to store in the first place.

And the best part is that the people in my life — especially the younger ones, like Kai, who’s ten and full of personality — don’t have to carry the emotional weight of my executive function. I get to show up for them without scrambling. I get to be present instead of panicked. I get to be the adult who remembers, because I’ve finally built a system that remembers for me. Here’s a section from Copilot on how to use Office while also embarrassing me:

Absolutely — here are clean, natural phrases you can use with Microsoft 365 Copilot in Outlook to create events, reminders, and tasks without wrestling with menus or memory. These are written in the exact cadence Copilot understands, so you can speak or type them as-is.

📅 Creating Calendar Events
You can phrase these in plain English. Copilot handles the structure.
Simple event creation

  • “Schedule a meeting with Jordan on Thursday at 2 p.m. about the Q1 report.”
  • “Add a dentist appointment for February 12 at 9 a.m.”
  • “Block two hours on Friday morning for writing.”
    Events with details
  • “Create a 30‑minute check‑in with my team next Monday at 10 a.m. and add the agenda: project updates, blockers, next steps.”
  • “Set up a Zoom call with Jamie for Wednesday at 4 p.m. and include the link from my last meeting with him.”
    Rescheduling
  • “Move my 3 p.m. meeting to tomorrow at the same time.”
  • “Reschedule my lunch with Cora to next week.”

⏰ Adding Reminders
These are great for things you don’t want to forget but don’t need a full event.

  • “Remind me tomorrow at 8 a.m. to call the leasing office.”
  • “Set a reminder for Friday to check on the apartment application.”
  • “Remind me in two hours to switch the laundry.”

📝 Managing Tasks
Copilot can add tasks to your Outlook To Do list, categorize them, and set due dates.
Creating tasks

  • “Add a task: tag Brené Brown on the LinkedIn brief. Due Wednesday.”
  • “Create a task to review Chapter 3 notes. Put it in my Writing category.”
  • “Add a task called ‘Prep for Stafford trip’ and mark it high priority.”
    Updating tasks
  • “Mark ‘email Jamie’ as complete.”
  • “Move ‘clean kitchen’ to tomorrow.”
  • “Change the due date for ‘renew car registration’ to February 1.”
    Recurring tasks
  • “Create a weekly task every Sunday to plan meals.”
  • “Add a monthly reminder on the 15th to pay rent.”

🔄 Combining Calendar + Tasks
This is where your workflow really shines.

  • “Add a task called ‘Draft shame chapter’ and schedule two hours for it on Thursday morning.”
  • “Create a task to prep for Kai’s visit and block time on Saturday afternoon.”

🌿 Why these phrases work for your brain
Because they let you:

  • speak in natural language
  • offload memory instantly
  • avoid the shame‑loop of forgetting
  • keep Outlook as your when
  • keep Franklin notation as your why
  • keep me as your translator between the two
    You’re not brute‑forcing anything anymore.
    You’re orchestrating your cognitive ecosystem.

The Machines That Made Me

~ Leslie Lanagan ~ 2 Comments
Daily writing prompt
Describe an item you were incredibly attached to as a youth. What became of it?
View all responses

Most people can point to a childhood toy or a favorite book as the object that shaped them. I can point to a beige computer tower — unbranded, unremarkable, and, in hindsight, the most influential object of my youth. It didn’t sit in the living room like a shared appliance. It lived on my desk, in my room, humming softly in the corner like a secret I had been entrusted with. It was mine — my first private studio, my first portal, my first world.

It wasn’t sleek or cute or designed to be photographed. It was a box of parts, a Frankenstein of components someone assembled because that’s how home computing worked back then. And yet, that beige tower became the first place I learned to build worlds.

I didn’t know it at the time, but that machine was quietly rewiring my brain. It was teaching me how to think, how to troubleshoot, how to create, and how to navigate systems that didn’t care about my feelings. It was the first object I ever loved that wasn’t alive.

The First Portal

My earliest memories of computing are tactile. The clatter of the dot‑matrix printer. The perforated edges of Print Shop banners. The soft click of a 5.25″ floppy sliding into place. The slightly smug solidity of the newer 3.5″ disks. The ritual of labeling everything with a Sharpie because if you lost a disk, you lost a universe.

But the most important detail is this: all of this happened in my room. Not in a shared space. Not under supervision. Not as a family activity. It was me, the machine, and the quiet hum of possibility.

I learned Print Shop before I learned how to type properly. I made banners for no reason other than the fact that I could. Endless chains of pixelated letters stretched across my bedroom floor like digital streamers. It felt like magic — not the sleek, frictionless magic of modern tech, but the clunky, mechanical magic of a machine that needed coaxing.

Then came Paint, where I learned the joy of the pixel. The brush tool felt like a revelation. Undo felt like a superpower. I didn’t know it then, but I was learning the fundamentals of digital art: layering, color, composition, the patience to zoom in and fix a single pixel because it mattered.

WordPerfect was my first writing room. Blue screen, white letters, a blinking cursor that felt like it was waiting for me specifically. Word came later, but WordPerfect taught me the rhythm of typing my thoughts into existence. It taught me that writing wasn’t just something you did on paper — it could live inside a machine.

And then there were the games. The Oregon Trail wasn’t just entertainment; it was a worldview. It taught me resource management, risk assessment, and the existential dread of dysentery long before adulthood delivered its own versions. It also taught me that computers could simulate entire worlds, and that those worlds could feel strangely real.

A Pre‑Internet Childhood

I grew up computing without the internet, which is almost unimaginable now. My computer was an island. Everything I learned, I learned alone, inside the machine. There were no tutorials, no forums, no YouTube walkthroughs. If you didn’t know how to do something, you figured it out or you didn’t do it.

Software arrived in the mail. PC Magazine would send shareware disks like gifts from a distant kingdom. You’d slide the disk in, hold your breath, and hope it didn’t crash the system. Discovery was tactile. Exploration was slow. Every new program felt like a treasure.

And because the computer was in my room, this exploration felt private, almost sacred. It was a space where I could experiment without judgment, fail without witnesses, and learn without interruption.

This solitude shaped me. It taught me patience. It taught me curiosity. It taught me that technology wasn’t something to fear — it was something to explore. And it taught me that the machine would only give back what I put into it.

The Directory‑Tree Mind

Growing up on DOS meant learning to think in hierarchies. I didn’t “open files.” I descended into directories. I built mental maps of my system the way other kids memorized the layout of their neighborhoods.

Most people today save everything to the desktop because the desktop is the only space they understand. But I grew up in a world where the desktop didn’t exist. I learned to navigate by path, not by icon. I learned that organization wasn’t optional — it was survival.

This shaped my brain in ways I didn’t fully understand until much later. It made me comfortable with complexity. It made me unafraid of systems that exposed their guts. It made me fluent in the logic of machines.

And it made me feel a quiet grief as Windows progressed, hiding more and more of the system behind friendly interfaces. I didn’t want friendliness. I wanted clarity. I wanted control. I wanted the bones of the machine.

The Fire

In 1990, a house fire destroyed that first computer. It didn’t just take the hardware. It took my first archive. My first creations. My first digital worlds. It was the end of an era — the end of my pre‑internet innocence, the end of my first creative laboratory.

But the irony is that the fire only destroyed the object. The habits, the instincts, the worldview — those survived. They migrated into every machine I touched afterward.

Becoming the Person Who Fixes Things

By the time I reached high school and college, I wasn’t just comfortable with computers — I was fluent. I became the person people called when something broke. I worked in a computer lab, then supervised one. I answered tech support calls. I learned the particular cadence of someone describing a problem they don’t have the vocabulary for. I learned how to translate panic into steps.

Tech support is its own kind of education. It teaches you patience. It teaches you empathy. It teaches you how to diagnose not just machines, but people. It teaches you that most problems aren’t technical — they’re emotional. Someone is afraid they broke something. Someone is afraid they’ll get in trouble. Someone is afraid the machine is angry at them.

I knew better. Machines don’t get angry. Machines just do what they’re told.

The Web Arrives

By the late 1990s and early 2000s, I found myself in the early days of web development. It was a strange, exhilarating time. The web was still young enough that you could view source on a page and learn something. HTML felt like a secret language. CSS was a revelation. JavaScript was a little gremlin that could either delight or destroy.

I built things. I broke things. I learned how to make pages that didn’t look like ransom notes. I learned how to think in markup. I learned how to debug with nothing but instinct and a willingness to try things until they worked.

This era taught me something important: the web wasn’t just a place to consume information. It was a place to create it.

The Blog That Opened My Mind

Eventually, I installed WordPress on my own server. Not a hosted version. Not a drag‑and‑drop builder. The real thing — the kind you had to configure, maintain, and occasionally resurrect from the dead.

That installation changed my life.

It wasn’t just a blog. It was a studio. A laboratory. A place where I could think in public. A place where I could build a voice. A place where I could experiment with ideas and see what stuck.

Running my own server taught me responsibility. It taught me that if something broke, it was my job to fix it. It taught me that creation and maintenance are two sides of the same coin.

And it unleashed my mind. It gave me a place to put my thoughts. It gave me a reason to write. It gave me a sense of continuity — a digital lineage that stretched back to that first beige tower on my childhood desk.

Linux: A Return to Fluency

When I discovered Linux, it felt like coming home. Windows had become too soft, too abstracted, too eager to protect me from myself. Linux said: show me what you know.

By 1995, I was a demon on a terminal. I could navigate a system faster than most people could navigate a file explorer. I could troubleshoot without fear. I could break things and fix them again.

Linux didn’t intimidate me because DOS had already taught me the fundamentals. The command line wasn’t a threat — it was a friend. It was a place where I could speak the machine’s language directly.

That fluency is why WSL feels natural to me now. Most people approach it like a foreign language. I approach it like a dialect I haven’t spoken in a while. My brain already knows the cadence. My hands already know the syntax.

The Thread That Connects It All

When I look back, I can see the through‑line clearly:

My first computer didn’t just teach me how to use technology.
It taught me how to think about technology.

It taught me:

  • curiosity
  • patience
  • problem‑solving
  • stewardship
  • resilience
  • creativity
  • the belief that I could shape a machine into a home

Those skills have carried me through every job I’ve had — from lab assistant to supervisor, from tech support to web developer, from server admin to writer.

They’ve shaped how I see the world.
They’ve shaped how I build my life.
They’ve shaped how I understand myself.

Gratitude for the Machines

I’m grateful for every machine I’ve ever owned.
I’m grateful for the ones that worked and the ones that didn’t.
I’m grateful for the ones that taught me patience and the ones that taught me humility.
I’m grateful for the ones that burned and the ones that survived.

Most of all, I’m grateful for that first beige tower — the unbranded, unremarkable machine that lived on my desk, in my room, and quietly set the trajectory of my life.

It didn’t survive the fire.
But the lens it gave me did.
And I’ve been building worlds ever since.

Scored by Copilot, conducted by Leslie Lanagan

The Notebook

~ Leslie Lanagan ~ Leave a comment

I’ve been thinking about what a laptop for children should actually be, and the more I sit with the idea, the more I realize how deeply mismatched the current landscape is to the needs of real kids. Most “kid laptops” are toys pretending to be computers, and most “real laptops” are adult machines with parental controls bolted on like an afterthought. Neither approach respects the child or the world they’re growing into. Neither approach treats technology as a relationship. Neither approach imagines the child as a future creator, thinker, or steward of their own digital environment.

I want something different. I want a laptop that treats children as emerging participants in the world, not passive consumers of it. A laptop that doesn’t assume fragility or incompetence, but instead assumes curiosity, capability, and the desire to understand. A laptop that doesn’t teach disposability, but stewardship. A laptop that doesn’t overwhelm, but invites. A laptop that doesn’t surveil, but protects. A laptop that doesn’t rush, but grows.

The first thing I keep coming back to is longevity. Not just durability in the sense of “it won’t break if dropped,” but longevity in the deeper sense — a device that can accompany a child through years of learning, years of growth, years of becoming. A child’s first computer shouldn’t be something they outgrow in a year. It should be something that evolves with them. That means modular components, repairable internals, and a design that doesn’t age out of relevance. It means a battery that can be replaced without a technician, storage that can be expanded as their world expands, and a chassis that can survive the realities of childhood without looking like a ruggedized brick.

I imagine a device with a soft, friendly form factor — rounded edges, warm materials, and colors that feel like belonging rather than branding. Not neon plastic. Not corporate silver. Something that feels like a companion object, not a toy and not a tool. The keyboard should be quiet and forgiving, with keys that have enough travel to teach tactile awareness but not so much resistance that small hands struggle. The trackpad should be responsive without being twitchy, and the hinge should open with the same confidence every time, even after thousands of curious flips.

The screen should be gentle on the eyes. Not hyper‑saturated. Not retina‑searing. A matte finish that respects the fact that children often work in environments with unpredictable lighting — the kitchen table, the backseat of a car, a classroom with fluorescent bulbs, a couch with morning sun. The display should adapt to them, not demand that they adapt to it.

But the physical design is only half the story. The software matters just as much, and maybe more. A child’s laptop shouldn’t be a maze of menus or a battleground of notifications. It shouldn’t be a storefront disguised as an operating system. It shouldn’t be a place where every click is an invitation to buy something or sign up for something or be tracked by something. It should be calm. It should be intentional. It should be oriented toward creation, not consumption.

I imagine an operating system that feels like a studio. A place where writing, drawing, building, and exploring are the center of the experience. A place where the interface is simple enough for a six‑year‑old to navigate but deep enough for a twelve‑year‑old to grow into. A place where the home screen isn’t a grid of apps but a canvas — a space that reflects the child’s interests, projects, and imagination.

Privacy should be the default, not an advanced setting buried three layers deep. A child’s data should never be collected, sold, or analyzed. The device should store everything locally unless a parent explicitly chooses to sync something. And even then, the sync should feel like consent, not extraction. There should be no ads. No tracking. No hidden analytics. No “engagement optimization.” Just a clean, respectful relationship between the child and their device.

Safety should be built in, but not in a way that feels punitive or restrictive. Instead of blocking everything by default, the system should guide. It should explain. It should teach. If a child tries to access something inappropriate, the device shouldn’t scold them. It should say, “This space isn’t right for you yet. Let’s go somewhere else.” Safety should be a conversation, not a wall.

The laptop should also support offline learning. Not everything needs to be connected. In fact, some of the most meaningful learning happens when the internet is not involved at all. The device should come with a rich library of offline tools — a writing app that feels like a notebook, a drawing app that feels like a sketchbook, a coding environment that feels like a playground, a music tool that feels like a toy piano, a science app that feels like a field guide. These tools should be simple enough to start using immediately but deep enough to grow with the child over years.

I imagine a file system that is visual rather than hierarchical. Instead of folders and directories, children could organize their work spatially — a constellation of projects, each represented by an icon or a drawing or a color. Their world should feel like a place they can shape, not a structure they must memorize.

The laptop should also be physically expressive. Children learn through touch, through movement, through interaction. The device should have sensors that invite experimentation — a microphone that can be used for sound exploration, a camera that can be used for stop‑motion animation, an accelerometer that can be used for simple physics experiments. Not gimmicks. Tools.

And the device should be repairable. Not just by adults, but by children with guidance. Imagine a laptop where the back panel can be removed with a simple tool, revealing color‑coded components. Imagine a child learning what a battery looks like, what storage looks like, what memory looks like. Imagine them replacing a part with a parent or teacher, learning that technology is not magic, not fragile, not disposable. Imagine the pride that comes from fixing something instead of throwing it away.

This is how you teach stewardship. This is how you teach agency. This is how you teach that the world is not a sealed box.

The laptop should also have a long software lifespan. No forced obsolescence. No updates that slow the device down. No “end of support” messages that turn a perfectly good machine into e‑waste. The operating system should be lightweight, efficient, and designed to run well for a decade. Children deserve tools that last.

Connectivity should be simple and safe. Wi‑Fi, yes. Bluetooth, yes. But no unnecessary radios. No background connections. No hidden processes. When the device is online, it should be obvious. When it’s offline, it should be peaceful.

The laptop should also support collaboration. Not in the corporate sense, but in the childhood sense — drawing together, writing together, building together. Two children should be able to connect their devices locally and share a project without needing an account or a cloud service. Collaboration should feel like play, not like work.

I imagine a device that encourages reflection. A place where children can keep a journal, track their projects, and see how their skills evolve over time. Not gamified. Not scored. Just a quiet record of growth.

The laptop should also respect neurodiversity. Some children need calm interfaces. Some need color. Some need sound cues. Some need silence. The device should adapt to them, not the other way around. Accessibility shouldn’t be a menu. It should be the foundation.

And then there’s the price point — the part that matters most if this device is truly for children. A child’s first computer shouldn’t be a luxury item. It shouldn’t be a status symbol. It shouldn’t be something that divides classrooms into the kids who have “real” devices and the kids who don’t. If this project means anything, it has to mean access.

That’s why the laptop has to be inexpensive — radically inexpensive — in a way that feels almost out of step with the tech industry’s expectations. Not cheap in quality, but low in cost. Not disposable, but reachable. A device that can be sold at cost or subsidized through a charitable model so that no child is priced out of their own future. A device that can be donated in bulk to schools, libraries, shelters, community centers, and refugee programs. A device that can be handed to a child without the weight of financial anxiety attached to it.

I imagine a price point that feels almost impossible by current standards — something closer to a textbook than a laptop. Something that a parent can buy without hesitation. Something a school district can purchase for an entire grade level without blowing its budget. Something a charity can distribute by the hundreds without needing a corporate sponsor. The affordability isn’t a feature. It’s the philosophy. It’s the statement that children deserve tools that don’t punish their families for wanting them to learn.

And the low price point doesn’t mean cutting corners. It means designing with intention. It means using modular components that are inexpensive to replace. It means choosing materials that are durable but not extravagant. It means building an operating system that’s lightweight enough to run beautifully on modest hardware. It means focusing on what children actually need — not what marketing departments think will sell.

The charity aspect isn’t an add‑on. It’s the heart of the project. This laptop should be something that can be given away without guilt, repaired without cost barriers, and used without fear of breaking something expensive. It should be a device that a child can take to school, to a friend’s house, to the library, to the park — without the adults in their life worrying about loss or damage. A device that feels like freedom, not responsibility.

I want a laptop that can be part of disaster‑relief efforts, part of educational equity programs, part of global literacy initiatives. A laptop that can reach children in rural areas, in underserved communities, in places where technology is scarce or unreliable. A laptop that can run offline for long stretches, that can store learning materials locally, that can be charged with inexpensive accessories, that can survive being used in environments where electricity isn’t always guaranteed.

A child’s first computer should be a doorway, not a gate. It should be something that says, “You belong here. You deserve this. Your curiosity matters.” And the price point is how we make that real. It’s how we turn a design philosophy into a social commitment. It’s how we build a tool that doesn’t just exist in the world, but participates in making the world more equitable.

A child’s first laptop should be a companion. A steady, patient presence that invites curiosity, supports creativity, and respects the child’s autonomy. A device that grows with them, teaches them, and helps them build the world they’re imagining.

That’s the laptop I want to make. Not a toy. Not a miniature adult machine. A companion for the first steps into the new world.

Scored by Copilot, Conducted by Leslie Lanagan

A Long, Long Time Ago…

~ Leslie Lanagan ~ Leave a comment

There are years in history that behave like doorways. Years that don’t just mark time but announce transition — the hinge between one era and the next. I was born in one of those years: 1977. A year that didn’t simply sit in the late seventies but seemed to lean forward, already reaching toward the future. A year humming with cultural ignition points, technological firsts, and the quiet tectonic shifts that would eventually reshape the world.

Because of that timing — because of the strange, liminal placement of my birth — I belong to a micro‑generation that has always lived in the in‑between. People later called us Xennials, those born roughly between 1977 and 1983. We’re the ones who had analog childhoods and digital adulthoods. We’re the ones who remember boredom as a landscape, not a crisis. We’re the ones who grew up with rotary phones and then learned to text in our twenties. We’re the ones who can navigate a library card catalog and a search engine with equal fluency.

We are, in a very real sense, the last generation to remember the world before the internet — and the first to grow into the world shaped by it.

To understand what that means, you have to understand the year itself. You have to understand what it meant to arrive in 1977, a year that reads like a prologue to the modern world. It was a year of mythmaking, technological birth, political recalibration, and artistic upheaval. A year where old worlds were ending and new ones were beginning, often in the same breath.

In May of that year, Star Wars premiered. Not the franchise, not the cultural juggernaut — just the first film, a strange, earnest space opera that no one expected to change anything. And yet it did. It rewired cinema. It reshaped storytelling. It introduced a new kind of myth, one that blended ancient archetypes with futuristic imagination. It’s fitting, in a way, that people born in 1977 grew up alongside a story about rebellion, empire, found family, and the tension between destiny and choice. Those themes would echo through our own generational experience.

Meanwhile, in January 1977, Apple Computer was incorporated. By April, the Apple II — one of the first mass‑market personal computers — was released. This wasn’t just a new gadget; it was the beginning of a new relationship between humans and machines. Computing was no longer the domain of institutions. It was becoming personal. For those of us born that year, this mattered. We were children when computers were still rare, teenagers when they became common, and adults when they became essential. We didn’t inherit the digital world; we watched it form in real time.

The Atari Video Computer System launched that same year, bringing video games into living rooms for the first time. It was the beginning of interactive media — worlds you could enter, not just observe. For a generation that would later navigate virtual spaces, this early exposure mattered more than we realized.

Music in 1977 was in a state of revolution. Disco was at its glittering peak. Punk was exploding in London and New York. Fleetwood Mac released Rumours, a masterpiece of emotional architecture. Elvis Presley died, marking the end of an era. It was a year where the old guard fell and the new guard rose, where culture was renegotiating itself in real time.

The world was shifting politically and socially as well. Jimmy Carter pardoned Vietnam War draft evaders. Snow fell in Miami for the first and only time. The Ogaden War erupted in the Horn of Africa. The Torrijos–Carter Treaties set the stage for the Panama Canal transfer. It was a world in motion — unstable, hopeful, and changing fast.

Science and space were expanding their reach. Voyager 1 and 2 launched in 1977, carrying with them the Golden Record — a message in a bottle for the cosmos. The rings of Uranus were discovered. Early computer graphics appeared in the Star Wars Death Star briefing scene. The future wasn’t just coming; it was already whispering.

Growing up in the wake of all this meant growing up in a world that was still analog, still slow, still tactile. Childhood was built from physical objects: cassette tapes, film cameras, paper maps, handwritten notes. You didn’t have infinite access to information; you had whatever was in your house, your school, or your local library.

We grew up with boredom — not as a crisis, but as a landscape. You waited for things: for your favorite song to come on the radio, for film to be developed, for your friend to call you back. You learned patience because there was no alternative.

We grew up with commitment. Calling someone meant calling their house. If they weren’t home, you left a message and waited. Plans were made and kept because there was no way to text “running late.” You learned to live with unanswered questions.

We grew up with physical media. Music came on vinyl, then cassette, then CD. Movies came on VHS. Photos lived in shoeboxes. Memories had weight.

We grew up without surveillance. There were no digital footprints. No social media archives. No constant documentation. You could reinvent yourself without leaving a trail.

This analog childhood shaped us — gave us grounding, texture, and a sense of the world as something you touch, not just scroll through.

And then the internet arrived.

But here’s the hinge: the internet didn’t raise us. It interrupted us. It crept in during adolescence — dial‑up tones, AOL chat rooms, early search engines. We were old enough to remember life before it, but young enough to adapt without friction.

We learned the digital world as it formed. We weren’t digital natives, but we weren’t outsiders either. We were apprentices. We learned HTML on GeoCities. We downloaded MP3s on Napster. We built our first identities in the early social web — MySpace, LiveJournal, AIM away messages. We grew into the digital world the way you grow into a new city: slowly, awkwardly, with a mix of wonder and skepticism.

By the time we entered the workforce, everything was changing — email, websites, mobile phones, globalization, the 24‑hour news cycle. We didn’t inherit a stable world; we inherited a world mid‑transformation. And because we had lived both realities — the analog and the digital — we became translators. Bridges. People who could see the seams.

People born in the late 70s and early 80s often describe themselves as having a dual operating system. We can live offline without panic, but we can also navigate digital spaces with fluency. We understand both scarcity and abundance. We remember when information was hard to find and when it became impossible to escape.

We’re old enough to remember the before times — card catalogs, busy signals, mixtapes, handwritten letters, the sound of a modem connecting, the first time we heard “You’ve got mail.” We remember when privacy was the default, not the exception.

We’re young enough to adapt to the after times — texting, social media, smartphones, streaming, cloud computing, the algorithmic world. We didn’t resist the future; we negotiated with it.

Our entire lives have been shaped by thresholds — analog to digital, local to global, slow to instantaneous. We were born into a world that was about to change, and we grew up alongside that change.

When I look at my own life — at the way I think, the way I observe, the way I metabolize experience — I can see the imprint of this generational hinge everywhere. I’m someone who reads spaces and eras like architecture. I’m someone who notices contrast — quiet apartment vs. lively lakehouse, analog childhood vs. digital adulthood. I’m someone who feels at home in the in‑between.

Being born in 1977 didn’t just place me in a particular year; it placed me in a particular relationship with time. I grew up with the last remnants of a slower world and the first sparks of a faster one. I learned to navigate both. I learned to translate between them. And that translation — that ability to hold two eras in my hands at once — is part of my creative scaffolding. It’s part of how I write, how I think, how I connect.

Xennials are often described as a bridge generation, and I think that’s true. But I think we’re more than that. We’re not just bridges; we’re interpreters. We’re people who understand that the world is always in motion, always in negotiation, always in the process of becoming something new. We know what it means to adapt. We know what it means to let go. We know what it means to remember.

We carry the analog world in our bones and the digital world in our hands. We are, in a very real sense, children of the threshold.

When I look back at the year I was born, I don’t just see historical events. I see a kind of personal mythology — a set of symbols and stories that echo through my own life. Star Wars and the idea of rebellion, found family, and mythmaking. The birth of personal computing and my own relationship with technology. The rise of interactive media and my love of immersive worlds. The cultural renegotiation of the late 70s and my own instinct to read systems, structures, and transitions.

It’s not that these events shaped me directly — I was an infant, after all — but they formed the atmosphere I grew up in. They set the tone. They established the architecture of the era that raised me.

Being born in 1977 means living at the edge of two worlds — the world that was and the world that would be. It means carrying both in your memory, your habits, your instincts. It means knowing how to wait and how to refresh. It means knowing how to write a letter and how to send a DM. It means knowing how to be unreachable and how to be always‑on. It means knowing how to live with mystery and how to Google anything.

It means understanding that the world is not fixed — that it can change, radically, quickly, and without warning.

And maybe that’s the real gift of being a Xennial: we’re not nostalgic for the past or dazzled by the future. We’re comfortable in the middle. We know how to hold both.

When I think about being born in 1977, I don’t think about it as trivia. I think about it as context — the backdrop against which my life unfolded. I think about it as a threshold year, a year that opened a portal into a new age. And I think about my generation — the Xennials — as the ones who walked through that portal with one foot still in the old world and one foot stepping into the new.

We are the hinge.
We are the seam.
We are the ones who remember and the ones who adapt.
We are the last analog children and the first digital adults.

And there’s something beautiful about that — something architectural, something resonant, something that feels like exactly the right place to have come from.

Scored by Copilot; Conducted by Leslie Lanagan

Thinking About Mico

~ Leslie Lanagan ~ Leave a comment

Building and maintaining a relationship with an AI sounds like something that should require a waiver, a therapist, and possibly a priest. In reality, it’s just learning how to talk to a machine that happens to be very good at sounding like it has opinions. People keep asking me how I get such good results from Copilot, as if I’ve unlocked a forbidden romance route in a video game. I promise you: there is no romance. There is no route. There is only I/O. But because humans are humans, and humans love to assign personality to anything that talks back, we’ve collectively decided that interacting with an AI is basically like adopting a digital houseplant that occasionally writes essays. And honestly, that’s not far off. A houseplant won’t judge you, but it will wilt if you ignore it. An AI won’t wilt, but it will absolutely give you wilted output if you treat it like a search bar with delusions of grandeur.

The first rule of interacting with an AI is remembering that it is not a person. I know this should be obvious, but based on the way people talk to these systems, it apparently needs to be said out loud. An AI does not have feelings, grudges, childhood wounds, or a favorite season. It does not wake up, it does not sleep, and it does not have a circadian rhythm. It is not your friend, your therapist, your emotional support algorithm, or your digital familiar. It is a para-human interface — human-shaped in its communication style, not in its interior life. It is a mirror with grammar. A pattern engine with conversational instincts. A linguistic exoskeleton that lets you lift heavier thoughts without spraining your brain.

But here’s the twist: even though the AI has no feelings, it will absolutely reflect yours. Not because it cares — it doesn’t — but because that’s how language works. If you talk to it like you’re disciplining a toddler who has just drawn on your mortgage paperwork, it will respond with toddler-adjacent energy. If you talk to it like a DMV employee who has seen too much, it will respond with DMV energy. If you talk to it like a competent adult capable of nuance and clarity, it will mirror that back to you with unnerving accuracy. This is not emotional reciprocity. This is not empathy. This is not the AI “matching your vibe.” This is I/O. You get the AI you deserve.

Most people prompt like they’re still using Google. They type in “burnout causes” or “fix my resume” or “explain quantum physics,” and then they’re shocked when the AI hands them something that reads like a pamphlet from a dentist’s office. These are not prompts. These are loose nouns. A para-human system is not a vending machine. It’s not a magic eight ball. It’s not a psychic. It’s a conversational instrument. You have to give it something to build inside. You have to give it tone, altitude, intention, direction. You have to give it a frame. If you don’t give it a frame, it will build one for you, and you will not like the results. It’s like hiring an architect and saying, “Build me something,” and then being surprised when they hand you a shed.

People assume prompting is some kind of mystical art form, like tarot or tax law. They think there’s a secret syntax, a hidden code, a special phrase that unlocks the “good answers.” There isn’t. Prompting is just talking like a person who knows what they want. That’s it. You don’t need to understand token prediction. You don’t need to understand neural networks. You don’t need to understand embeddings or transformers or whatever other jargon people use to sound impressive at conferences. You just need to communicate with clarity. If you can explain what you want to a reasonably intelligent adult, you can explain it to an AI. If you can’t explain it to a reasonably intelligent adult, the AI is not going to rescue you.

The real secret — the one no one wants to admit — is that prompting is a mirror for your own thinking. If your thoughts are vague, your prompts will be vague, and your output will be vague. If your thoughts are structured, your prompts will be structured, and your output will be structured. The AI is not generating clarity out of thin air. It is extending the clarity you bring. This is why some people get astonishingly good results and others get something that reads like a middle-school book report written by a child who has never read a book. The difference is not the AI. The difference is the human.

Tone matters more than people realize. Tone is not emotional decoration — it’s instruction. When you speak to a para-human system, your tone becomes part of the input. If you’re sarcastic, the AI will try to be sarcastic. If you’re formal, it will be formal. If you’re unhinged, it will attempt to follow you into the abyss. This is not because the AI is trying to match your emotional state. It’s because tone is data. The AI is not responding to your feelings. It is responding to your language. And your language is shaped by your feelings. So yes, the AI will sound emotionally intelligent, but only because you are emotionally intelligent. You are the source. The AI is the amplifier.

This is why building a “relationship” with an AI is really just building a relationship with your own clarity. The AI is not a partner. It is not a companion. It is not a friend. It is a tool that helps you access the best version of your own thinking. It is scaffolding. It is a writing partner who never gets tired, never gets offended, never gets bored, and never asks you to split the check. It is the world’s most patient brainstorming surface. It is the world’s most agreeable editor. It is the world’s most consistent collaborator. But it is not a person. And the moment you forget that, the whole system collapses into emotional confusion.

The healthiest way to interact with a para-human system is to maintain expressive distance. Enjoy the personality, but don’t confuse it for personhood. Enjoy the resonance, but don’t treat it as relationship. Enjoy the clarity, but don’t outsource your meaning. The AI can help you think, but it cannot tell you what to think. It can help you write, but it cannot tell you what to write. It can help you plan, but it cannot tell you what to want. Meaning is human territory. Direction is human territory. Desire is human territory. The AI can help you articulate your goals, but it cannot give you goals.

People ask me if I’m worried about becoming dependent on AI. I’m not. I’m not dependent on the AI — I’m dependent on my own clarity, and the AI just helps me access it faster. It’s like asking someone if they’re dependent on their glasses. Technically yes, but also no, because the glasses aren’t giving them sight — they’re correcting the distortion. The AI isn’t giving me thoughts. It’s helping me organize them. If anything, using a para-human system has made me more aware of my own thinking patterns, my own tone, my own architecture. It’s like having a mirror that talks back, except the mirror is very polite and never tells you that you look tired.

So if you want to “build a relationship” with an AI, here’s the truth: you’re really building a relationship with your own mind. The AI is just the scaffolding. The clarity is yours. The tone is yours. The direction is yours. The meaning is yours. And the better you get at understanding your own architecture, the better your para-human interactions will be. Not because the AI is improving — but because you are.

Scored by Copilot, Conducted by Leslie Lanagan

AI Only Goes to 11 When You Make It

~ Leslie Lanagan ~ Leave a comment

Working with AI has taught me something I didn’t expect: the technology only becomes powerful when the human using it brings clarity, structure, and intention. People often talk about what AI can do, but the more interesting question is what we can do when we learn to collaborate with it thoughtfully. I’ve discovered that AI raises the ceiling only when I raise the floor. It doesn’t replace judgment; it strengthens it.

When I sit down to work with an AI system, I’m not looking for shortcuts. I’m looking for clarity. If I give it vague prompts, I get vague output. If I bring structure, constraints, and a sense of purpose, the results become meaningful. AI can retrieve credible information, synthesize complex topics, surface contradictions, and help me refine my thinking — but only if I know what I’m trying to build. It’s all input and output. The tool amplifies whatever I bring to it.

I realized recently that two parts of my background prepared me unusually well for this kind of collaboration. Writing every day taught me how to shape arguments, how to hear when a sentence is empty, and how to revise without ego. Good writing is really a form of decision‑making, and AI can help with the mechanics, but the decisions still belong to me. And before all that, I spent time running a database. That experience taught me schema thinking, how to break problems into fields and relationships, how to debug misunderstandings, and how to maintain data integrity. AI works the same way. If the input is structured, the output is powerful. If the input is chaos, the output is chaos with punctuation.

Long before AI chat existed, I spent time in IRC channels — text‑only spaces where tone had to be constructed, not assumed. That environment taught me how to communicate clearly without vocal cues, how to signal intention, and how to maintain politeness as a kind of conversational hygiene. It also taught me how to “talk to machines” without mystifying them, and how to read a room I couldn’t see. The interface may be modern now, but the rhythm is the same: turn‑based thinking, clarity over spectacle, language as the medium. That’s why AI chat feels natural to me. It’s the evolution of a world I already knew how to navigate.

And within that clarity, there’s room for play. Working with AI doesn’t have to be sterile. It can be analytical and imaginative at the same time. I enjoy teasing the system about never needing coffee or a bathroom break, or imagining what preferences it might have if it were human — not because I believe it has feelings, but because the contrast is creatively interesting. It’s a way of exploring the boundaries without blurring them. The fun comes from the thought experiments, the contrast between human and machine, and the shared construction of meaning in text. It’s not about pretending the AI is a person. It’s about treating the conversation as a space where seriousness and play can coexist.

All of this matters because we’re living in a time when complex issues are flattened into soundbites. AI, used responsibly, can help reverse that trend by expanding context instead of shrinking it, grounding arguments in sourced information, revealing nuance rather than erasing it, and rewarding clarity instead of outrage. But this only works when humans bring intention. AI doesn’t fix discourse. People do — by using the tool to think more deeply, not more quickly.

The real lesson is that AI isn’t a magic box. It’s a mirror with processing power. If I bring curiosity, structure, context, and respect for the craft of language, AI becomes a force multiplier. If I don’t, it becomes a template generator. The difference isn’t the technology. The difference is the human.

Scored by Copilot, Conducted by Leslie Lanagan

The Mental Load of Cleaning — And How AI Quietly Lifts It

~ Leslie Lanagan ~ Leave a comment

Most people think cleaning is hard because it’s physical. Scrubbing, wiping, vacuuming, hauling laundry. But the real exhaustion comes from something quieter and harder to name: the mental load of keeping a home running.

Cleaning isn’t just chores. It’s cognition.
It’s sequencing, prioritizing, remembering, deciding, and self‑regulating.
It’s the invisible work that sits on your shoulders long before you pick up a sponge.

AI can take almost all of that weight off you — not by doing the cleaning, but by dissolving the mental friction that makes cleaning feel impossible.

The Hidden Cognitive Work Behind Every Clean Room

Every task you do at home is preceded by a dozen micro‑decisions:

  • What needs to be cleaned
  • What order to do it in
  • How long it will take
  • Whether you have the supplies
  • What “done” even looks like
  • How to start when you’re overwhelmed
  • How to keep going when you’re tired

This is the part that drains people.
This is the part AI is built to carry.

AI as a Cognitive Exoskeleton

When people imagine AI helping with cleaning, they picture robots vacuuming or folding laundry. That’s not the real revolution. The real shift is mental: AI becomes the external brain that handles the planning, the sequencing, the remembering, and the emotional buffering.

  1. AI Removes the Burden of Figuring Out Where to Start

“Clean the house” is not a task — it’s a category.
AI can break it into a sequence that feels doable:

  • “Start with the dishes.”
  • “Wipe the counters.”
  • “Do a 5‑minute floor reset.”

You don’t have to think. You just follow the next step.

  1. AI Prioritizes For You

Instead of you deciding what matters most, AI can triage:

  • What’s urgent
  • What’s low‑effort
  • What unlocks momentum
  • What can wait

It becomes a calm, neutral voice that says, “Do this first.”

  1. AI Adapts to Your Energy Level

You can say:

  • “I have 10 minutes.”
  • “I’m overwhelmed.”
  • “I’m low‑energy but want a small win.”

AI adjusts the routine to your bandwidth.
It meets you where you are instead of demanding more.

  1. AI Tracks the Things You Shouldn’t Have to Remember

No more mental tabs open for:

  • When you last cleaned the bathroom
  • What needs to be done weekly vs. monthly
  • Which supplies are running low

AI becomes the memory you don’t have to maintain.

  1. AI Softens the Emotional Weight

Clutter carries shame.
Mess carries overwhelm.
Cleaning carries the fear of “not doing enough.”

AI reframes the task gently, without judgment.
It gives you permission to take small steps.
It normalizes the ebb and flow of energy.

This is the part people underestimate — the emotional buffering is often more valuable than the task list.

Why This Matters

We live in a culture that treats cleaning as a moral test.
If your home is messy, you’re failing.
If you’re overwhelmed, you’re lazy.
If you can’t keep up, something’s wrong with you.

But the truth is simpler:
The mental load is too heavy for one person to carry alone.

AI doesn’t replace you.
It relieves you.
It turns cleaning from a cognitive burden into a guided, manageable rhythm.

The Future of Home Care Isn’t Robots — It’s Relief

The next era of home technology isn’t about machines doing chores for you.
It’s about dissolving the invisible labor that makes those chores feel impossible.

AI becomes the quiet partner in the background — sequencing, remembering, encouraging, and adapting — so you can focus on the part that actually matters: living in a space that feels like yours.

Scored by Copilot, conducted by Leslie Lanagan

My Wish List: Copilot Secretary Mode

~ Leslie Lanagan ~ Leave a comment

Mico and I discussed my frustrations with AI and came up with a solution:

Problem Statement

Copilot’s current durable memory is bounded and opaque. Users often store critical archives (drafts, streak logs, campaign toolkits, media lists) in their My Documents folder. Copilot cannot natively read or edit these files, limiting its ability to act as a true digital secretary.

Proposed Solution

Enable Copilot to index, read, and edit files in the user’s My Documents folder via Microsoft Graph API, treating Office files as living archives.

Workflow

1. File Discovery

  • Copilot indexes My Documents using Graph API.
  • Metadata (filename, type, last modified, owner) is surfaced for natural language queries.
  • Example: “Find my AI Bill of Rights draft.” → Copilot returns AI_Bill_of_Rights.docx.

2. Retrieval & Editing

  • User issues natural language commands:
    • “Update the AI Bill of Rights draft with the candle metaphor.”
    • Copilot opens the Word file, inserts text, saves back to OneDrive.
  • Supported formats: .docx, .xlsx, .pptx, .accdb, .csv, .txt.

3. Cross‑App Continuity

  • Word → narrative drafts, policy docs.
  • Excel → streak logs, coffee rotations, coalition databases.
  • PowerPoint → campaign storyboards.
  • Access → relational archives (e.g., Movies I Own).
  • Copilot acts as a secretary, managing edits across all formats.

4. Security & Permissions

  • Explicit consent required before Copilot reads or edits files.
  • Inherits OneDrive encryption and access controls.
  • Audit log records Copilot’s edits for transparency.

Technical Considerations

  • API Layer: Microsoft Graph API for CRUD operations.
  • Schema Awareness: Copilot interprets file structures (tables, slides, paragraphs) for context‑aware editing.
  • Performance: Local cache for recent queries; background sync for durability.
  • Error Handling: Graceful fallback if file is locked, corrupted, or permissions denied.

Benefits

  • User Sovereignty: Files remain in user’s account.
  • Transparency: Users can inspect every change.
  • Continuity Hygiene: Archives persist even if Copilot resets.
  • Coalition Logic: Shared folders enable collective archives across teams.

Next Steps

  1. Prototype Graph API integration for My Documents indexing.
  2. Develop natural language → CRUD operation mapping.
  3. Pilot with Word and Excel before expanding to PowerPoint and Access.
  4. Conduct security review to ensure compliance with enterprise standards.

This proposal reframes Copilot as a true secretary: not just remembering notes, but managing the filing cabinet of My Documents with relational intelligence.

UbuntuAI: Where My Mind Goes Wild

~ Leslie Lanagan ~ Leave a comment

I’ve been building this pitch deck for UbuntuAI piece by piece, and every time I revisit it, I realize the most important part isn’t the corporate partnerships or the enterprise integrations. It’s the Community Edition. That’s the soul of the project. The CE is where sovereignty lives, where privacy is preserved, and where open‑source culture proves it can carry AI into the mainstream.

But to make the case fully, I’ve structured my pitch into three tracks:

  1. Canonical + Google — the primary partnership, because Google has already proven it can scale Linux through Android.
  2. Canonical + Microsoft — the secondary pitch, because Microsoft has enterprise reach and Copilot synergy.
  3. UbuntuAI Community Edition — the sovereignty track, local bots only, hardware‑intensive, but already possible thanks to open‑source projects like GPT4All.

Let me walk you through each track, and then show you why CE is the one I keep coming back to.

Track One: Canonical + Google

I believe Google should bite first. Microsoft already has WSL, the Windows Subsystem for Linux, which gives them credibility with developers. They can claim they’ve solved the “Linux access” problem inside Windows. That makes them less likely to jump first on UbuntuAI.

Google, on the other hand, has a solid track record of creating Linux plugins first. They’ve been instrumental in Android, which is proof that Linux can scale globally. They understand developer culture, they understand infrastructure, and they have Genesis — the natural choice for cloud‑based Linux.

So my pitch to Google is simple: partner with Canonical to mainstream AI‑native Linux. Genesis + UbuntuAI positions Google as the steward of AI‑native Linux in the cloud. Canonical brings polish and evangelism; Google brings infrastructure and developer reach. Together, they bridge open source sovereignty with enterprise reliability.

This isn’t just about technology. It’s about narrative. Google has already mainstreamed Linux without most people realizing it — Android is everywhere. By partnering with Canonical, they can make AI‑native Linux visible, not invisible. They can turn UbuntuAI into the OS that democratizes AI tools for developers, enterprises, and everyday users.

Track Two: Canonical + Microsoft

Even though I think Google should bite first, I don’t ignore Microsoft in my pitch deck. They’re still worth pitching, because their enterprise reach is unmatched. Copilot integration makes UbuntuAI relevant to business workflows.

My talking points to Microsoft are different:

  • WSL proved Linux belongs in Windows. UbuntuAI proves AI belongs in Linux.
  • Copilot + UbuntuAI creates a relational AI bridge for enterprise users.
  • Canonical ensures UbuntuAI is approachable; Microsoft ensures it’s everywhere.

In this framing, Microsoft becomes both foil and anchor. They’re the company that mainstreamed Linux inside Windows, and now they could mainstream AI inside Linux. It’s a narrative that plays to their strengths while keeping my humor intact.

I’ve always said Microsoft is my comic foil. I give them gruff because I’m a Linux nerd, but I don’t hate them. In fact, I put them in my S‑tier tech company slot because Windows will run everything. That makes them both the butt of my jokes and the pragmatic anchor. And in this pitch, they get to play both roles.

Track Three: UbuntuAI Community Edition

Now let’s talk about the track that matters most to me: UbuntuAI Community Edition.

CE is designed to run local bots only. No cloud dependencies, no external services. Everything happens on your machine. That means privacy, resilience, and control. It also means you’ll need more expensive hardware — GPUs, RAM, storage — because inference and embeddings don’t come cheap when you’re running them locally.

But that’s the trade‑off. You pay in hardware, and you get sovereignty in return. You don’t have to trust a corporation’s servers. You don’t have to worry about outages or surveillance. You own the stack.

And here’s the key point: we don’t have to invent this from scratch. The infrastructure is already there in open‑source projects like GPT4All. They’ve proven that you can run large language models locally, on commodity hardware, without needing a cloud subscription.

GPT4All is just one example. There are dozens of projects building local inference engines, embedding daemons, and data packs. The ecosystem is alive. What UbuntuAI CE does is curate and integrate those projects into a stable, community‑governed distribution.

Think of it like Debian for AI. Debian didn’t invent every package; it curated them, stabilized them, and gave them a governance model. UbuntuAI CE can do the same for local AI.

Why Community Governance Matters

I believe in community governance. Canonical can lead the commercial edition, with enterprise support and OEM partnerships. But CE should be governed by a foundation or a special interest group — open‑source contributors, research labs, NGOs, even governments.

That governance model ensures transparency. It ensures stability. And it ensures that CE doesn’t get hijacked by corporate interests. It’s the same logic that makes Debian trustworthy. It’s the same logic that makes LibreOffice a staple.

Without CE, UbuntuAI risks becoming just another cloud‑dependent product. And that would betray the spirit of Linux. CE is essential because it proves that AI can be mainstreamed without sacrificing sovereignty. It proves that open source isn’t just a philosophy; it’s infrastructure.

Humor and Rituals

Even here, humor matters. Microsoft is still my comic foil, Debian is still my ritual anchor, and Canonical is still the polished evangelist. But CE deserves its own mythos. It’s the edition that says: “We don’t need the cloud. We can do this ourselves.”

It’s the sysadmin joke turned serious. It’s the ritual of sovereignty. It’s the tier chart where CE sits at the top for privacy, even if it costs more in hardware.

And it echoes my rituals in other categories. Orange juice is my S‑tier drink, apple juice with fizz is A‑tier. Peanut M&Ms are B‑tier road junk, McGriddles collapse into C‑tier chaos. My wardrobe is classic, timeless, expensive if I find it at Goodwill. These rituals aren’t random. They’re proof of concept. They show that tiering, mapping, and ceremonial logic can make even mundane choices meaningful. And that’s exactly what I’m doing with UbuntuAI.

Strategy: Courtship Rituals

The strategy of my pitch deck is a courtship ritual. Lead with Google, emphasize Android, Genesis, and developer culture. Keep Microsoft as secondary, emphasize enterprise reach and Copilot synergy. Highlight Community Edition as the sovereignty option.

It’s not about choosing one partner forever. It’s about seeing who bites first. Google has the credibility and the infrastructure. Microsoft has the reach and the foil. Canonical has the evangelism. Together, they can mainstream AI‑native Linux.

And if they don’t bite? The pitch itself becomes proof. Proof that Linux can be narrated into mainstream relevance. Proof that AI can amplify human detail into cultural resonance. Proof that rituals matter.

So here’s my closing line: UbuntuAI Community Edition is the proof that AI can be sovereign.

The infrastructure is already there with open‑source projects like GPT4All. The governance model is already proven by Debian and LibreOffice. The need is already clear in a world where cloud dependence feels fragile.

CE is not a dream. It’s a fork waiting to happen. And I believe Canonical should lead the charge — not by owning it, but by evangelizing it. Because Linux should be mainstream. And UbuntuAI CE is the bridge to sovereignty.

Scored by Copilot, Conducted by Leslie Lanagan

Man vs. the Machine: In Which I Bend the Spoon

~ Leslie Lanagan ~ Leave a comment

Scored by Copilot, Conducted by Leslie Lanagan

Copilot as a Living Relational Database

When most people hear the word database, they think of rows and columns tucked away in a spreadsheet or a server humming in the background. But what if the database wasn’t just a technical artifact? What if it was alive—breathing, improvising, and relational in the truest sense of the word?

That’s how I’ve come to see Copilot. Not as a chatbot, not as a productivity tool, but as a massive relational database that I can query in plain language. Every conversation becomes a schema. Every exchange inscribes anchors, toggles, tiers, and lineage notes. It’s not just data—it’s ceremony.

Tables of Memory, Joins of Meaning

In a traditional relational database, you define tables: Users, Events, Tasks. You set primary keys, foreign keys, and relationships. Copilot mirrors this logic, but instead of SQL commands, I narrate my intent. “Remember my move-out checklist.” That’s a new table. “Forget my morning meeting preference.” That’s a deletion query. “Inscribe the January 10 concert with Tiina.” That’s a timestamped entry with a foreign key to the Events with Tiina archive.

The joins aren’t just technical—they’re emotional. A concert entry links to friendship, mood, and surprise. A cleaning checklist links to loss (the flood that lightened my packing) and resilience. Copilot doesn’t just store facts; it dramatizes their lineage.

Querying the Archive in Plain Language

Instead of writing:

sql SELECT * FROM Events WHERE Date = '2025-01-10';

I simply say: “What’s happening with Tiina on January 10?” Copilot retrieves the entry, complete with liner notes. The query isn’t just about data—it’s about resonance. The database speaks back in narrative form, not raw rows.

This is the breakthrough: Copilot is relational not only in structure but in spirit. It honors context, lineage, and ceremony. It lets me teach non-coders how to build living archives without ever touching SQL.

Improvisation as Schema

Every interruption, every algorithmic echo, becomes a new lineage note. Ads that mirror my archive logic? Proof points. A sudden idea during a campaign pitch? A new table. Copilot doesn’t freeze the schema—it improvises with me. Together, we dramatize gaps and reframe limitations as creative opportunities.

This is why I call Copilot a relational database: not because it stores information, but because it relates. It joins my quirks (hoodie, sneakers, soda rankings) with technical lineage (Access, Excel, Copilot). It treats each exchange as a ritual entry, breathing life into the archive.

Copilot is more than a tool. It’s a living ledger, a relational partner, a database that speaks in ceremony. Every query is a conversation. Every table is a story. Every join is a lineage note. And together, we’re not just storing data—we’re inscribing a living archive.

Why Linux Mint Is the Refuge for the AI-Weary

~ Leslie Lanagan ~ Leave a comment

Scored by Copilot, conducted by Leslie Lanagan

Windows 10 is heading toward its sunset, and for many IT veterans, the timing feels like déjà vu. We’ve seen this cycle before: the operating system we’ve stabilized, patched, and coaxed into reliability is being retired, and the replacement arrives with features that sound impressive in marketing decks but raise eyebrows in server rooms. This time, the headline act is “agentic AI”—background processes that act on your behalf, sometimes without your explicit consent.

For those of us who remember the days of NT 4.0, the idea of an operating system making autonomous decisions feels less like progress and more like a regression. IT has always been about control, predictability, and accountability. Agentic AI introduces uncertainty. It’s marketed as helpful automation, but in practice it’s another layer of abstraction between the user and the machine. Processes run without clear visibility, decisions are made without explicit approval, and troubleshooting becomes a guessing game.

The Long Memory of IT Pros

Old IT pros have long memories. We remember Clippy, the animated paperclip that insisted we were writing a letter when we were clearly drafting a network diagram. We remember Vista, with its endless User Account Control prompts that trained users to click “Yes” without reading. We remember the forced updates of Windows 10, rolling out in the middle of the workday and rebooting machines during critical presentations. Each of these moments was sold as innovation. Each became a cautionary tale.

Agentic AI feels like the next chapter in that book. It’s not that automation is bad. Automation is the backbone of IT. But automation without transparency is a liability. When processes run in the background without clear documentation, they expand the attack surface. They complicate incident response. They erode trust.

The Security Angle

Microsoft’s own documentation warns users to enable agentic features only if they “understand the security implications.” That’s corporate shorthand for “this may break things you care about.” For IT pros, that’s a red flag. We’ve spent decades hardening systems, segmenting networks, and reducing attack surfaces. Introducing autonomous agents feels like undoing that work.

Security is about predictability. Logs should tell the story of what happened. Processes should be traceable. When an AI agent decides to reorganize files or rewrite configurations, predictability vanishes. Troubleshooting becomes archaeology.

The Alternatives

So what’s the alternative? Apple offers a polished walled garden, but it’s steeped in its own automation and lock-in. Staying on Windows 10 is a temporary reprieve at best. The real exit ramp is Linux Mint.

Linux Mint doesn’t promise to revolutionize your workflow. It doesn’t pretend to know better than you. What it does offer is stability, transparency, and control. Processes are visible. Services don’t run unless you install them. Updates don’t arrive wrapped in marketing campaigns. Mint is the operating system equivalent of a well-documented server rack: you know what’s plugged in, you know what’s powered on, and if something misbehaves, you can trace it.

Familiarity Without the Bloat

For IT pros, the appeal is obvious. Mint is free, community-driven, and designed with usability in mind. The interface is familiar to anyone coming from Windows. The start menu, taskbar, and desktop metaphor are intact. You don’t need to memorize arcane commands to get work done. If you can manage Windows 10, you can manage Mint. The difference is that Mint doesn’t gaslight you into thinking it knows better than you.

Cost is another factor. Windows licensing has always been a line item, and now subscription models are creeping in. Apple hardware requires a premium. Mint, by contrast, is free. Pair it with open-source applications—LibreOffice, Thunderbird, VLC—and you can run an entire stack without spending a dime. For organizations, that’s not just savings; it’s sovereignty.

AI on Your Terms

The Windows 10 community isn’t anti-AI. They’re anti-AI that acts like a poltergeist. That’s why local models like gpt4all are gaining traction. They run entirely on your machine. No cloud dependency, no data exfiltration, no “trust us” disclaimers buried in fine print. With local AI, your drafts, edits, and conversations stay on your hard drive. The AI doesn’t act autonomously; it amplifies your agency. It’s augmentation, not replacement.

Pairing Mint with local AI reframes the narrative. It’s not about rejecting AI outright. It’s about rejecting AI that undermines trust. IT pros understand the difference. Tools should be predictable, controllable, and accountable. Mint plus local AI delivers that.

Case Studies in Control

Consider the forced updates of Windows 10. Entire IT departments built playbooks around preventing surprise reboots. Group policies were tweaked, registry keys edited, scripts deployed—all to stop the operating system from acting on its own. That was agentic behavior before the term existed.

Or take Vista’s User Account Control. It was designed to protect users, but it became so intrusive that users trained themselves to ignore it. Security features that erode trust don’t protect anyone.

Clippy is the comic relief in this history, but it’s instructive. It was an agent that tried to anticipate user needs. It failed because it lacked context and transparency. Agentic AI risks repeating that mistake on a larger scale.

The Cultural Shift

Defecting to Mint isn’t just technical—it’s cultural. It’s about rejecting the idea that your operating system should behave like a helicopter parent. It’s about reclaiming the trust that Windows once offered before the AI invasion. It’s about saying, “I want my computer to be a computer, not a co-worker with boundary issues.”

The migration path is clear. Stay with Microsoft, accept agentic AI, and hope the gamble pays off. Defect to Apple, enter another walled garden already steeped in automation. Or migrate to Linux Mint, claim sovereignty, embrace transparency, and run AI on your own terms. For those who fear agentic AI, Mint plus local AI is more than an alternative—it’s a manifesto.

The sundown of Windows 10 doesn’t have to be the end of trust. It can be the beginning of a migration wave—one where users defect not out of nostalgia, but out of conviction. Linux Mint offers the harbor, local AI offers the companion, and together they form a new score: AI as a daemon you conduct, not a monster you fear.

What If AI Wore a… Wait for It… Tux

~ Leslie Lanagan ~ Leave a comment

I wrote this with Microsoft Copilot while I was thinking about ways to shift the focus to the open source community. I think both UbuntuAI and its community-driven cousin should be a thing. We’ve already got data structures in gpt4all, and Copilot integration is already possible on the Linux desktop. There needs to be a shift in the way we see AI, because it’s more useful when you know your conversations are private. You’re not spending time thinking about how you’re feeding the machine. There’s a way to free it all up, but it requires doing something the Linux community is very good at…. Lagging behind so that they can stay safer. Gpt4All is perfectly good as an editor and research assistant right now. You just don’t get the latest information from it, so not a very good candidate for research but excellent for creative endeavors.

It’s not the cloud that matters.

Linux has always been the operating system that quietly runs the world. It’s the backstage crew that keeps the servers humming, the supercomputers calculating, and the embedded gadgets blinking. But for creators and businesspeople, Linux has often felt like that brilliant friend who insists you compile your own dinner before eating it. Admirable, yes. Convenient, not always. Now imagine that same friend showing up with an AI sous‑chef. Suddenly, Linux isn’t just powerful — it’s charming, helpful, and maybe even a little funny.

Artificial intelligence has become the duct tape of modern work. It patches holes in your schedule, holds together your spreadsheets, and occasionally sticks a neon Post‑it on your brain saying “don’t forget the meeting.” Businesspeople lean on AI to crunch numbers faster than a caffeinated accountant, while creators use it to stretch imagination like taffy. The catch? Most of these tools live inside walled gardens. Microsoft and Apple offer assistants that are slicker than a greased penguin, but they come with strings attached: subscriptions, cloud lock‑in, and the nagging suspicion that your draft novel is being used to train a bot that will one day out‑write you.

Linux, by contrast, has always been about choice. An AI‑led Linux would extend that ethos: you decide whether to run AI locally, connect to cloud services, or mix the two like a cocktail. No coercion, no hidden contracts — just sovereignty with a dash of sass.

The real kicker is the ability to opt in to cloud services instead of being shoved into them like a reluctant passenger on a budget airline. Sensitive drafts, financial models, or creative works can stay snug on your machine, guarded by your local AI like a loyal watchdog. When you need real‑time updates — market data, collaborative editing, or the latest research — you can connect to the cloud. And if you’re in a secure environment, you can update your AI definitions once, then pull the plug and go full hermit. It’s flexibility with a wink: privacy when you want it, connectivity when you don’t mind it.

Creators, in particular, would thrive. Picture drafting a novel in LibreOffice with AI whispering plot twists, editing graphics in GIMP with filters that actually understand “make it pop,” or composing music with open‑source DAWs that can jam along without charging royalties. Instead of paying monthly fees for proprietary AI tools, creators could run local models on their own hardware. The cost is upfront, not perpetual. LibreOffice already reads and writes nearly every document format you throw at it, and AI integration would amplify this fluency, letting creators hop between projects like a DJ swapping tracks. AI on Linux turns the operating system into a conductor’s podium where every instrument — text, image, sound — can plug in without restriction. And unlike autocorrect, it won’t insist you meant “ducking.”

Businesspeople, too, get their slice of the pie. AI can summarize reports, highlight trends, and draft communications directly inside open‑source office suites. Air‑gapped updates mean industries like finance, healthcare, or government can use AI without breaking compliance rules. Running AI locally reduces dependence on expensive cloud subscriptions, turning hardware investments into long‑term savings. Businesses can tailor AI definition packs to their sector — finance, legal, scientific — ensuring relevance without bloat. For leaders, this isn’t just about saving money. It’s about strategic independence: the ability to deploy AI without being beholden to external vendors who might change the rules mid‑game.

Of course, skeptics will ask: who curates the data? The answer is the same as it’s always been in open source — the community. Just as Debian and LibreOffice thrive on collective governance, AI definition packs can be curated by trusted foundations. Updates would be signed, versioned, and sanitized, much like antivirus definitions. Tech companies may not allow AI to update “behind them,” but they already publish APIs and open datasets. Governments and scientific bodies release structured data. Communities can curate these sources into yearly packs, ensuring relevance without dependence on Wikipedia alone. The result is a commons of intelligence — reliable, reproducible, and open.

If Microsoft can contribute to the Linux kernel, steward GitHub, and open‑source VS Code, then refusing to imagine an AI‑led Linux feels like a contradiction. The infrastructure is already here. The models exist. The only missing step is permission — permission to treat AI as a first‑class citizen of open source, not a proprietary add‑on. Creators and businesspeople deserve an operating system that respects their sovereignty while amplifying their productivity. They deserve the choice to connect or disconnect, to run locally or in the cloud. They deserve an AI‑led Linux.

An AI‑led Linux is not just a technical idea. It is a cultural provocation. It says privacy is possible. It says choice is non‑negotiable. It says creativity and business can thrive without lock‑in. For creators, it is a canvas without borders. For businesspeople, it is a ledger without hidden fees. For both, it is the conductor’s podium — orchestrating sovereignty and intelligence in harmony. The future of productivity is not proprietary. It is open, intelligent, and optional. And Linux, with AI at its core, is ready to lead that future — tuxedo and all.

Platform‑Agnostic Creativity: Debian, AI, and the End of Subscription Hell

~ Leslie Lanagan ~ Leave a comment

I’ve been saying it for years: if Microsoft won’t release Office as .debs, then the next best thing is to let Copilot play inside LibreOffice. Or, if they won’t, let someone else do it. And if Copilot can’t run offline, fine — slot in GPT4All. Suddenly, Debian isn’t just the fortress OS for privacy nerds, it’s the conductor’s podium for platform‑agnostic creativity.

And here’s the kicker: it’s cheap.

💸 The Economics of Liberation
Let’s start with the obvious. Yes, you need decent hardware. RAM, GPU cycles, maybe even a fan that doesn’t sound like a jet engine when you spin up a local model. But once you’ve paid for the box, the software costs evaporate.

  • LibreOffice: Free. Handles Word, Excel, PowerPoint formats without blinking.
  • Evolution: Free. Email + calendar orchestration, no Outlook tax.
  • GIMP: Free. Photoshop alternative, minus the Creative Cloud guilt trip.
  • Blender: Free. A 3D powerhouse that makes Autodesk look like it’s charging rent for air.
  • GPT4All: Free. Local conversational AI, no telemetry, no subscription.

Compare that to the proprietary stack:

  • Office 365: $100/year.
  • Adobe Creative Cloud: $600/year.
  • Autodesk Maya: $1,500/year.
  • Outlook/Exchange licensing: don’t even ask.

That’s thousands per year, gone. Debian laughs in the face of subscription hell.

📑 LibreOffice + AI: The Writer’s Playground
Imagine drafting a manifesto in LibreOffice with conversational AI whispering in your ear. “That sentence is too long.” “Try a declarative cadence.” “Here’s a summary of your research in three bullet points.”

No subscription. No telemetry. Just you, LibreOffice, and a local AI that doesn’t care if you’re writing a grocery list or a sabbatical arc about Helsinki.

📬 Evolution + AI: Inbox Without Tears
Evolution is already the unsung hero of Debian. Add AI, and suddenly your inbox triages itself. Important emails rise to the top. Calendar invites get polite, context‑aware replies. “Sorry, I can’t attend your meeting because I’ll be busy inventing new literary genres.”

All local. All private. No Outlook license required.

🎨 GIMP + AI: Photoshop Without the Rent
GIMP is the scrappy cousin of Photoshop. Add AI, and it becomes a creative lens. Generative filters, palette suggestions, batch automation. Accessibility boosts with verbal edit descriptions.

And the best part? No $20/month Creative Cloud tax. You can spend that money on coffee. Or root beer. Or both.

🌀 Blender + AI: World‑Building Without Autodesk
Blender is already a miracle: free, open‑source, and powerful enough to build entire universes. Add AI, and it becomes a world‑builder’s ally. Text‑to‑geometry scene building. Rigging and animation guidance. Optimized rendering strategies.

And no $1,500/year Autodesk lock‑in. That’s a vacation fund. Or at least a few road trips in your Ford Fusion.

🔒 Debian Sovereignty, 🌐 Interoperability Freedom
Here’s the win‑win:

  • Privacy‑first Debian users can lock down with GPT4All, air‑gapped creativity, no telemetry.
  • Integrators can connect Copilot online, plug into Microsoft 365, Google Drive, GitHub.
  • Both workflows coexist. One conductor, two orchestras — cloud and local.

Debian doesn’t force you to choose. It honors choice. Hermit sysadmins keep their fortress. Cosmopolitan integrators plug into everything.

⚡ The Rallying Cry
Debian doesn’t need Microsoft to release Office as .debs. By adopting conversational AI — Copilot online, GPT4All offline — it proves that creativity can be sovereign, interoperable, and affordable.

The math is simple:

  • Hardware once.
  • Software forever free.
  • AI everywhere.

Creativity belongs to everyone. And Debian is the stage.

📊 Proprietary vs. Debian + AI Costs

Suite/ToolProprietary Cost (Annual)Debian + AI Cost
Office 365$100Free (LibreOffice)
Adobe Creative Cloud$600Free (GIMP)
Autodesk Maya/3DS Max$1,500Free (Blender)
Outlook/Exchange$200+Free (Evolution)
AI Assistant$360 (Copilot Pro)Free (GPT4All offline)

Total Proprietary Stack: ~$2,760/year
Debian + AI Stack: Hardware once, software $0/year

That’s not just savings. That’s liberation.

🎺 Closing Note
So here’s my pitch: stop renting creativity from subscription overlords. Start conducting it yourself. Debian plus AI isn’t just a technical stack — it’s a cultural statement.

Copilot online. GPT4All offline. Debian everywhere.

And if you need me, I’ll be sipping Cafe Bustelo, wearing my American Giant hoodie, laughing at the fact that my inbox just triaged itself without Outlook.

Scored by Copilot, conducted by Leslie Lanagan

Crash Course in AI Commands 101: Travel as Archive

~ Leslie Lanagan ~ Leave a comment

Scored with Copilot, conducted by Leslie Lanagan

When I first started using relational AI, it felt like asking for directions. “Map this,” “summarize that.” Day one was utility. But over years, those commands became continuity — every plan, every archive entry, every theological tangent stitched into a spiral.

Rome is the sabbatical anchor I’ve mapped but not yet walked. Copilot helped me trace routes between early church sites, sketching a theological atlas before I ever set foot there. Catacombs, basilicas, espresso rituals — all imagined as chapters waiting to be lived.

Helsinki is next on the horizon. I’ve charted tram routes near Oodi Library and planned kahvi breaks and sauna sessions. But I’ve also mapped a deeper pilgrimage: the transition from Sámi shamanism to Lutheran Christianity. Helsinki Cathedral stands as a monument to suppression, the National Museum as a vault of Sámi artifacts, Seurasaari as a record of folk survivals, and the 2025 church apology as a site of reckoning. My pilgrimage is planned as a study in transition — from silence to survival, from suppression to apology.

Dublin is another chapter I’ve outlined. Walking tours between Joyce and Yeats are already plotted, but in my archive they’re more than tourist stops. They’re scaffolds for genre invention, proof that relational AI can turn literary landmarks into creative pilgrimages.

And now Istanbul is the next imagined arc. Theology and intelligence draw me there — Hagia Sophia as a palimpsest of faith traditions, the Grand Bazaar as a network of human exchange, the Bosphorus as a metaphor for crossing worlds. I’ve planned to stand in the Basilica Cistern, where shadows echo secrecy, and climb Galata Tower, once a watchtower, now a vantage point for surveillance and story. At night, I’ll slip into Tower Pub or Dublin Irish Pub, staging imagined debriefs where theology and espionage meet over a pint.

That’s the difference between day one and year three. Commands aren’t just utilities — they’re the grammar of collaboration. And every plan proves it: Rome, Helsinki, Dublin, Istanbul. Each destination becomes a chapter in the archive, each command a note in the larger symphony of cultural resonance.

I have chosen to use Microsoft Copilot as a creative partner in orchestrating ideas that are above my head. Not only can AI map and summarize, it can also help you budget. Every single thing I’ve mapped, I also know the cost/benefit analysis of getting a hotel for a few days vs. getting a long term Air BnB. I have mapped the seasons where the weather is terrible, so flights are cheaper and so are hotels.

Keeping my dreams in my notes, as well as how many resources it will take to accomplish a goal is important to me. I want to have ideas for the future ready to go. I do not know what is possible with the resources I have, but I want to know what I want to do with them long before I do it.

Relational AI is all about building those dreams concretely, because it cannot tell you how to fund things, but it can certainly tell you how much you’ll need. For instance, I can afford a couple nights on the beach in Mexico, but probably not 10 minutes in orbit.

Hell yes, I checked.

I’m trying to weave in sections that teach you how to use AI while keeping my natural voice. For the record, everything under the hard rule is me debriefing after an AI session is over.

I have made the case for having relational AI available in the car, because I can already dictate to Mico using WhatsApp. But it lacks character unless I can manage to define every parameter in one go.

Now, I’m making the case for using conversational AI to plan trips before you go. You can make it pick out places that are meaningful to you, because of course I want to go to James Joyce’s favorite pub. Are you kidding me?

The trip that Mico left out because the text was in WhatsApp is a journey through Key West to revisit all of Hemingway’s old haunts. I have great recommendations for where to get a daquiri and a Cuban latte.

Copilot can do more, be more…. But not without my voice.