I've got a beautiful little graphic that emphasizes this,


How the World's Biggest Companies Design Machine Learning Applications | ML Monthly April 2021

how the biggest companies in the world


design machine learning powered applications.


This is a repost of this article.


But this graphic here is just exemplifying


the pieces of the puzzle.


Of course, these are not all of the pieces of the puzzle


around your ML code, these are just an example.


But that's the theme of this series or this post


of this edition of Machine Learning Monthly,


is how do you design all of these things


around your machine learning code?


And what I've done is, as we'll see in a second,


is collected resources from the biggest companies


in the world that are building machine learning


powered systems and put them in one place


so you can see how the best do it


and then apply that to your own projects.


So let's keep diving in.


And what I mean by infrastructure is all of the pieces


around your machine learning code.


But big caveat here, none of these,


these are guidelines throughout here,


none of these will replace the knowledge you gain


from experimenting yourself.


So read these as a guideline to give you a little,


a picture in the clouds of what you might like to build,


but none of them will do it for you.


Let's jump in.


The first one is Apple's Human Interface Guidelines


for Machine Learning.


We'll just dive into the resource.


I'll let you read the post if you want.


And, but, so why is this important?


Let's discuss.


And I'm sweating already because first of all,


I'm very excited to share these resources with you.


Second of all, Australia, it's supposed to be nearly winter,


but it is like the sun's beaming through my window


and it is ridiculously hot.


Anyway, no complaints.


Let's jump into this.


So why is this important from Apple?


Well, I haven't got my phone on me.


It's in another room, very important.


If you're doing something important,


keep your phone away from you so it's not distracting.


This is running on a MacBook, but they have,


I think it's somewhere over a billion devices


around the world.


And every single one of them runs machine learning,


whether it be on the system OS itself,


so the systems operating system, or on an application.


And so this developer guidelines is if you wanted to build


an Apple application with machine learning in it somewhere,


what should you think about


when you're building that application?


How could you get that on the app store,


get that into the hands of others?


Because ultimately that's what we want to do,


or that's what I want to do,


is get machine learning powered applications


into the hands of others.


So if you want to do the same,


this is some great things to think about.


So how could you design the user interface


and user experience, often referred to as UX,


of a machine learning app?


One of the most important questions here


that they go through is defining the role


of machine learning in your app.


And I found this very, very thought provoking.


So is it critical or complimentary?


That means, does your app,


is machine learning a critical requirement for the app?


Or does it enhance your app?


So if you imagine, AutoCorrect isn't critical


for a keyboard, but it may enhance how the keyboard works.


However, a service like Face ID requires machine learning,


so it uses your face to unlock your iPhone,


requires machine learning to work at all.


So therefore it is critical.


They also ask whether it's private or public,


like where does the data come from?


Is it proactive or reactive?


So does a proactive feature do it?


Does it work on itself?


Or does it only work when a user or a person puts in input?


And that's another thing I really liked


about Apple's guidelines,


is you'll see a lot of software refer to people as users.


I don't really like that terminology,


so I'm trying to fix that in my own wording,


because everyone's a person, right?


If you, it's very easy to get lost with numbers


on the screen and call them number of users that we have,


rather than, that's an actual person who's interacting


with your service or application or whatever you've built.


So that's what I'm trying to personally do.


So catch me out if I'm using the wrong language.


Visible or invisible, does it happen in front of a person


or behind the scenes?


Dynamic or static?


So I'll let you read through that.


As I said, I'm not gonna go through them in detail.


And then it also breaks it down to inputs and outputs.


And I really like this terminology,


because what does a machine learning model do?


It takes some kind of input,


finds patterns in that input,


and then produces an output that you've defined.


Now, Apple, it says,


if you want to build machine learning into your application,


use that, that ideology,


to design it into the application as well.


So what inputs does your app take?


What outputs does it give a user?


And you're going to notice a trend across


all of these guidelines.


And the inputs and outputs is a big one.


But the one I'm really a big fan of is mistakes.


So if we jump into this,


it's inevitable that your app will make mistakes.


Why is that?


Well, because machine learning algorithms are probabilistic.


That means that they are,


so probabilistic and deterministic,


probabilistic means that they output a probability


of something happening.


Deterministic means that it's certain,


the output is certain.


So if a machine learning model


is outputting probabilistic outputs,


it's inevitable that it will eventually get something wrong.


So how does your app handle


when your machine learning algorithm


makes a wrong prediction?


So this is very important to think about.


And then it goes through,


understand the significance of a mistake's consequences,


make it easy for people to correct frequent


or predictable mistakes.


I kind of hinted on this in my


deploying a machine learning model video


that I did a couple of weeks ago,


is if your application makes a wrong prediction,


how can you entice a person to help you


correct that prediction so your model improves over time,


in turn, eventually creating a data flywheel?


So really, really recommend reading through


Apple's human interface guidelines for machine learning.


I got a lot of value out of reading through this.


And it's certainly something I'm going to be using


going forward for creating my own projects.


And then I made a little colorful graphic,


which breaks down the role of machine learning in your app,


which just literally takes the roles here.


And rather than just being straight up texts,


makes it colorful and pretty, you know,


you've got to add a little bit more color to life.


All right, the next one is Google's People and AI Research,


which is the acronym is PAIR.


But if we jump into this,


this is another similar guidebook


to Apple's human interface guidelines,


whereas Apple's is more designed for


creating a machine learning application


for an Apple device.


The People and AI guidebook is more of a,


I would say a wider scale thing to think about from Google.


So if you imagine Google,


one of the biggest machine learning companies in the world,


you use their search engine,


I mean, I'm using Chrome right now,


which uses machine learning several different ways.


But if we wanted to get started,


they break it down into, no, thank you.


There's cookie, man, cookies are popping up everywhere.


I just wanna read a website.


They break it down into six chapters.


And what I really like about these chapters


is they come with worksheets at the end,


which means after you've read through a chapter,


so let's jump into a big thing you'll also see,


another trend is defining


what success is for your application.


So this is the user needs.


Again, I'm not a fan of that user term.


I prefer like, what does a person need?


What does a person on the other end of what you're building,


what do they need and define success?


So let's jump into this.


So even the best AI will fail


if it doesn't provide unique values to users.


So again, I would like to change that to people.


What's new when working with AI,


because the users, you can just get lost.


You forget that you're dealing with another human being.


And what's new when working with AI?


So I like this one as well.


Find the intersection of user strengths and AI strengths.


So if you think about what problems


is machine learning good for?


That's what this question challenges you to do.


Because machine learning is not always the right solution


to put into your application.


That's it, we'll see that later on.


That's one of Spotify's principles.


And then if you go through this,


again, I'm not gonna spend time going through this,


but this is, I found this was a great read through,


reading through all of these chapters.


The big overarching narrative


that I'd like you to take home from this video


is the overlaps.


So as I said, you'll find there's a lot of overlaps


between Apple's human interface guidelines,


as well as Google's pair, people and AI research.


See, they use people there.


Why not just keep that trend?


Anyway, but going back here is the key concept.


So you can answer the worksheets,


really help you to start thinking about


machine learning applications and products,


not just from a modeling standpoint,


but from the whole ecosystem,


putting together everything in this paradigm.


So let's jump back.


I kind of got distracted when I was telling you


the overarching narrative of this is the,


oh, there we go.


What do you do, errors and grace will fail you.


What do you do when your model is wrong?


What's the difference between an error and a failure?


A self-driving car stopping at a green light


could be an error,


but running a red light could be a failure.


You don't want your self-driving car to run a red light,


but if it started to stop at a green light,


that might be considered okay.


Of course, you don't want it to do that either,


but what's the significance between an error and a failure?


And you want to look for the overlaps in each of these,


because when there's overlaps between smart thinkers,


that's where the truth is.


Another great way to sort of learn something


is when two smart thinkers disagree with each other.


So as much as the overlaps are valuable,


look for the points where these guidelines


may disagree with each other.


So the next one is Microsoft's design guidelines


for human AI interaction.


Let's jump into this.


So Microsoft break it down into four main areas,


which is, let's get this graphic up.


This looks a bit better.


Can we see that?


Beautiful.


So the guidelines for human AI interaction.


So what do you do at the start?


Make clear what your system can do.


What expectations is the person using your system?


What are they going to get out of it?


Remember machine learning is,


it can seem like magic to someone


who's never used it before,


but if you're building the system,


you probably know where its flaws are,


if you're doing your experiments, right?


Make clear how well the system can do what it do.


So again, we're setting expectations.


We're building this entire narrative


around what a person is looking for,


what our application, what our project


can offer them.


Remember when I was working at Apple,


one of the big things we would talk about


is what are the benefits of someone purchasing


an Apple product rather than the features?


Because a lot of people don't necessarily care


how state of the art your model is.


They care what it does for them.


How does it improve their life?


That's what you want to think about.


The during the interaction.


So what that means is while a person is using your service,


what happens?


Do you have time services based on context?


Like for example, Google Maps might show you


food places around where you live or something like that.


Show contextually relevant information.


Again, this is all while someone is using your service.


When wrong, another overlap.


This is what we're saying.


Like all of these, again,


machine learning is probabilistic, not deterministic.


So it's inevitable that your model


will eventually make a wrong prediction.


So how do you make that the best experience


for someone using it?


I like these three here, these three cards.


Support efficient invocation.


So make it easy to invoke or request


the AI system services when needed.


So if you were talking to a voice assistant,


can you talk to them quickly?


Because speed is the name of the game in technology.


Support efficient dismissal.


Again, if you don't want to use the services anymore,


you want to deactivate the voice assistant,


you need to be able to tell them to stop quickly


and it'll just stop.


So for example, I don't want to set it off,


but I have a smart speaker out there.


If you say the word A-L-E-X-A,


if you pronounce that word, it will trigger.


But if I wanted it to stop,


I just say stop and it stops immediately.


And then again, if it becomes, if something's wrong,


if your application is wrong,


how does someone correct it to make it improve over time?


That's the final step.


So what does your system do over time?


Learn from, again, I'd like to change this,


learn from behavior.


Update and adapt cautiously, encourage granular feedback,


provide global controls, et cetera, et cetera.


Some great guidelines here,


and they also make it into a colorful graphic.


So I am a fan of that.


All right, to the next one.


Oh, here's a little trend that I drew with arrows.


You start with some sort of problem.


What problem?


Does your problem, does machine learning's strengths


overlap with your problem?


If not, you might need no ML.


So problem, create a solution,


set the expectations for what a person's expecting,


allow feedback for people to say,


hey, this is good and this is crap.


Have a mechanism for when it's wrong


and then improve over time.


And then you loop back to the problem.


I couldn't really draw that arrow with text,


but you kind of, you get the picture.


Next is Facebook's field guide to machine learning.


Now this is an amazing series of videos to think about


when you're building.


Now this is more focused on machine learning modeling.


So if we go back to this little graphic here,


machine learning modeling rather than


all of the steps around it.


So if we jump into this graphic,


again, it's defining a goal.


How do you start?


What data do you need to service that goal?


How do you process that data?


What model should you create?


See, I love here that they've got multiple models


because if you've gone through the TensorFlow course,


you'll know that a machine learning practitioner's motto is


experiment, experiment, experiment.


So try lots of things.


It's a scientific method.


It's combining engineering and science together.


And then of course, evaluate your model.


If we jump in, we've got six steps here.


I actually used this video series as the foundation.


You can go through these videos.


I'm not gonna go through them again.


As the foundation of my beginner friendly


machine learning and data science course.


So if you've gone through that,


you might recognize this graphic.


Well, here was the inspiration


from Facebook's field guide to machine learning.


Again, this Facebook's field guide to machine learning,


keep in mind that although the previous three resources


focus on many of these steps here,


the field guide to machine learning really only focuses on


once you have a data set and modeling that data


rather than data collection and deployment.


So yeah, if you want expanded versions of that,


you can go through the Zero to Mastery


Data Science and Machine Learning course,


or you can also read,


I have an expanded version on my blog.


So there's me with a Mohawk slash mullet,


and I put everything on a whiteboard to make it official


and then explained it with text,


what I learned from the videos.


Let's go back in here.


This is one of my favorites again,


Spotify's three principles for designing ML powered products.


Now there's a lot of information to take in here.


And again, I said at the start,


none of them will replace working


and running your own experiments,


but we're looking for overlaps here to keep in mind


when we are working on our own projects.


So let's jump into Spotify's three principles


for designing ML powered products.


Now Spotify have over 250 million customers around the world


that listen to streaming music.


Of course you're going to need machine learning somewhere,


but how do they think about doing it?


Let's jump in.


They have three principles,


identify friction and automate it away.


So where is a person in your service,


where are they running into sticking points?


So if you imagine the Spotify, you're looking for music,


that might be a sticking point.


So can machine learning help recommend different playlists


for someone to listen or discover new music?


Maybe it can, and I think you'll find it will


if you read through the full article.


Ask the right questions again.


What are we trying to do?


A person on the other end of your application


does not care how state of the art your model is.


They care what your service can do for them.


That's what you have to think about.


Benefits, not features.


And then finally, go manual before you go magic,


is do you need to start off with machine learning?


If you can use a simple rule-based system,


start with that, implement machine learning


if it improves that system.


So you can read through those.


I'm a big fan of, I used the Spotify application.


I was actually, while I was writing this article,


I was using, where is it?


What was I listening to?


And in my case, it looks like they must have heard


to their two principles,


because whilst building, whilst listening


or writing this article,


these tracks I'm listening to were absolute bangers.


So I was listening, they use machine learning


to create their Discover Weekly playlist.


What I was currently listening to


while writing this article,


I was listening to that this morning


while driving to breakfast.


It works.


So I'll let you read through that.


Principle two, ask the right questions.


If you don't know what you're building,


you could end up designing a product in the wrong direction.


Go manual before you go magical.


Lastly, we have From Big Data to Good Data by Andrew Ng.


Now this is another trend that I'm noticing


in the field of machine learning.


RoboFlow did a great summary of the main points.


So big shout out to RoboFlow.


I'm a big fan of their product too.


They build computer vision tools.


So go check them out if you're into computer vision.


But Andrew Ng did a talk recently


at Scales recent conference.


You can see it here.


You do have to sign up and put your email in.


It's free.


I've already done this,


but you can watch the whole talk there.


Some of my favorite points from the talk


were getting deployment is a starting point.


So I remember when I was


at my last machine learning engineering role,


we would build proof of concepts.


And we do a lot of the modeling points.


We get to deployment


and it'll kind of fizzle out after that point.


But that is what Andrew was asking is a starting point


because we all know the real test


of a machine learning model is not just on the test set.


It is once it's deployed to production,


getting actual people to interact with it.


The next, my favorite point was from big data to good data.


So let's be real.


We're not all building giant companies like Facebooks


and Googles and Spotify and millions of users.


So we don't have the big data resources


that they have access to.


We need to be smarter about that.


ML ops is most important task is ensuring


high quality data in all phases


of the ML project lifestyle.


So we're gonna be working with small data sets.


How can we automate the ML parts


and build the data parts around it


so that we're building this eventual data flywheel.


If you want more of that concept,


look up a talk by Josh Tobin, data flywheel.


We'll go to youtube.com.


You get a little insight into my recommendations here.


I'm into RuneScape, I'm into health.


Josh Tobin, data flywheel, highly recommend.


Oh, far out, I'm the first video on this.


All credit to Josh Tobin for the idea of the data flywheel.


Go check that out.


But essentially what you're trying to do


is just build a system that completely keeps collecting data.


The model improves by itself


and you're spending most of your time programming the data.


And when Andrew goes to be a consultant


on machine learning projects,


he tells them to freeze their code base,


freeze your modeling code base.


Get a good working model,


such as if you're on computer vision,


maybe EfficientNet-B4 is enough


for your image classification problem.


Freeze that model and then program your data.


So that's another thing I'd like to see come out from Kaggle.


Is Kaggle's like,


or maybe Kaggle or another data science competition,


is Kaggle usually, you have a data set


and you iterate on the model.


I'd like to see a Kaggle competition flipped


where you have a set model


and you have to iterate on the data set.


That would be really cool.


But go check out that talk.


I'm a big fan of that.


This point really speaks to,


if we come back up to the top,


the trend that I'm seeing in machine learning in general


is that machine learning is an infrastructure problem.


So once frameworks and pre-made models get better and better,


we're really just going to,


I think ML machine learning in the next few years


is going to be, it's just going to be like a,


this is going to be an API call.


We're seeing this with HuggingFace's models,


services and all that sort of stuff.


The model is going to be taken care of.


Your biggest task will be collecting the data


and feeding it to that model,


creating that data flywheel effect.


But let's finish up here.


Now, of course, I've thrown a lot of information at you


of how to think about building


your own machine learning projects.


And you thought I was going to leave you there high and dry


with all these principles, right?


Because principles, guidelines, shmard lines, it's all right.


I said, nothing is going to benefit you more


than actually working on these things.


So that's why we have a bonuses section.


The above are all guidelines,


how to think about building


your machine learning powered systems,


but they don't necessarily show you


or teach you how to go about doing so.


And so I've got some resources here,


which will go through the technical bits


around this little graphic.


So a great resource here.


I'm not going to dive through each of these,


but we have software engineering for ML,


which is this is a beautiful resource,


which really puts together, combines a lot of,


so when I started learning machine learning,


I missed out on a lot of software engineering skills.


I'm not going to dive into what those are


because this covers a lot of them.


So you could spend three months


reading through all of these engineering


or software engineering best practices for machine learning.


That's a great resource here.


The next one is the machine learning engineering book


by Andrei Berkov.


I have a copy of this,


usually within arm's reach.


Boom, I have a copy for this.


As you can see, hands-on machine learning,


deep learning for coders with fast AI and PyTorch.


Amazing book, available for free.


Read it online beforehand.


CS329S, machine learning system design.


So if you wanted all of the steps above


in course form from Stanford,


taught by the amazing Chip Heughan,


go and check out this.


Yours truly teaches the machine learning deployment section.


Deployment, no, deployment tutorials.


So you can go see all those,


but this is an outstanding course.


There's also full stack deep learning,


which I'm personally going through right now.


The 2021 version is out.


All of the videos are on YouTube.


You can see all of the notes here.


This is absolutely outstanding to learn.


Again, learn all of the steps around designing


and building a full-scale machine learning project.


Finally, the Made with MLOps curriculum by Goku Mohandes,


which is absolutely outstanding as well.


So this is more of a smaller,


individual lesson-based style.


I would say the full stack deep learning is longer style.


So they have 12 lectures or 13,


versus MLOps here has a lot more,


they're broken into smaller pieces.


So check all of these out.


You don't have to necessarily go through all of them.


I'd recommend at least one of these


to go along with reading through these.


So again, these will teach you how to think


about what goes into a machine learning system.


These courses then will get you hands-on,


and then your next step after that.


And my next step in fact,


is to build your own full-scale machine learning project,


but I'm not gonna talk about that for now.


That will be coming soon.


Far out, we have covered a lot.


If you wanna see the issue of this,


in your inbox next month,


make sure you sign up,


the link will be in the description.


But otherwise, that has been


Machine Learning Monthly for April, 2021.


Once again, if you have any submissions


that you'd like to see in a future newsletter,


or a future video like this,


you could see yourself on TV.


How cool would that be?


On YouTube, I mean, TV is dying, isn't it?


But send an email to danielatmrdeeburg.com


with the subject Machine Learning Monthly Submission,


and you may see it in a future episode.


Again, it could be anything


that you've worked on the machine learning world.


But this has been the design issue


of Machine Learning Monthly.


I hope you enjoyed it as much as I did researching it.


I've got a lot, a lot, a lot to think about


for my machine learning projects going forward.


But as always, keep machine learning,


keep creating, keep moving.


I will see you next time.


Peace.


Reading the first 42 pages of my first novel (Charlie Walks) out loud

Friends, welcome to the video. I'm very, very, very excited for this. This is, this has been a few years in the making.


And what you're about to see is I'm going to read the first 42 pages or so of my book, Charlie Walks.


You can see it there. The website is charliewalks.com. All the information you'll need to buy the book and to read some sample chapters as well will be there.


But this is, let's, let's, I figured it'd be fun to just read it out loud.


I mean, this is my first time writing a novel, a fiction book, and it's very, I'm very excited, as you can tell.


So let's not talk too much about it. There's the cover. I'll probably put another version of it here.


The website is charliewalks.com. All the stuff will be there. Let's read the first 42 pages.


We'll do it one and done style, which means no cuts. I'm just going to read it. If I make a mistake, I probably will.


We'll just, we'll just roll with it. And I think if you, once you read the book, if you do end up reading the book, you'll find that's the way Charlie would have liked it too.


So let's get started. Charlie Walks, a novel by Daniel Burke.


This is a work of fiction and is dedicated to Patrick and Elliot.


Chapter one. One. I've dived twice. We were told to write two facts about ourselves on post-it notes and stick them to our hands.


One of those team building exercises. The ones some might call awkward, but I love these situations.


When everyone feels like worms are in their stomach. Worms made me feel alive. What the hell, I thought.


I hadn't told anyone, but now seemed like a good time. I put the first one down and then the second, then got up and started to walk around.


I circled the room, reading and talking to others about what they wrote about themselves.


I've got two dogs. I practice kickboxing. I harvest honeybees. I'm a rock climber. No one else died twice yet.


The fighter girl circled back and started speaking. How can you die twice? She asked.


Her paper name tag spelled out her name. Sarah. The letters drawn in warm colors, which matched her dress.


I've got a heart condition, which takes advantage of me now and then, but the doctors don't know what it is.


Thank you for telling me that, she said. Sarcasm or honesty? I couldn't tell. I kept talking. Do you thank people who punch you in kickboxing?


Only after the fight, she said, then read my other note. So what do you write about? People. Mostly people.


What about people? I like hearing people's stories and remixing them with my own, I said.


Are you going to write about me? She smiled. You can be in my book if you want. You're writing a book?


We kept talking. She kept asking questions and I kept spinning answers. It was my turn when the announcement came over.


Okay, everyone. I hope you've learned something fun about your coworkers this morning. We're going to move to the next activity now.


We went on to the next thing. I didn't see Sarah for the rest of the day. After, I walked to the train and caught it home.


The whole time wondering what I'd say to her next. Ask her more about the gangsters from Greece, I thought. Yeah, that's a good idea. Real good.


Chapter two. Someone asked me why they were there once. The flamingos on my wall.


I stared at them and then down at my desk and thought, you know what? I can't work in an untidy room.


I don't know how everything got to where it did, but it did. I shoveled crap off the desk, reread some notes from yesterday.


A book doesn't have to be 60,000 words, Charlie. A reminder. Plenty of notes on how to write a book and not enough actual writing.


The demons crept in. I hadn't put enough time into the paper today. Writing was the release. Video games when I was younger.


As the law of conservation of energy states, addictions can't be removed, only replaced.


Most of it is sitting here waiting for the thoughts to come. And then they get dumped on the page. Whatever comes up, comes up.


If it didn't make sense, fine. It went down anyway. I'd fix it later. This was the third time I'd gone over these lines.


I hadn't seen them in a year. The first time weak. The second time cluttered. A different person each time.


Their thoughts trapped in time. Who wrote this? Me? Really? Whoa. Okay then.


Ten minutes passed and I'd managed to get out one word. A lie. The words were there. They always were.


My biggest fear was listening to them. They were always there. My biggest fear was listening to them.


The conversation starter. Talking to myself about what I did during the day. I'd start by recalling the day's happenings, then write them down.


I remembered Sarah and wondered what department she worked in. I hadn't seen her since the post-it notes activity.


But she'd been the leading actress in the movie in my head for the past few days.


Long hair. A little faded from the sun with a silver streak off to the right. Shorter than me, but only just.


Smile like a mix between the first and last rays of sun on the first day of summer. Eyes and teeth. Eyes and smile.


My two out of three favorite things to look at. She asked if I was going to write about her. Well, guess what, Sarah?


I smiled. I talked with her the least but remembered her the most. Some people have that about them.


The thoughts kept rambling and the word count had ticked over 750. Why 750? The perfect number, the three pages of typed copy.


A green button came up on the screen when you hit it. I loved that green button. But of course, the number never matters.


Did the thought get thought through? That's the right question.


If someone else was to read the words I just put down, they'd be barely legible. Hell, even when I reread them, I wondered.


All I knew is I'd go insane if I didn't let them out. I finished with a quip. People love to feel important.


And then it clicked. I remembered Sarah the most, the clearest out of everyone because she'd asked questions about what I was interested in.


I wrote it down again, 10 times, 10 different ways. People love to feel important. Everyone wants to feel important.


Ask questions about what the other person enjoys doing. People love to feel important. Everyone wants to feel important.


Ask questions about what the other person enjoys doing. And to top it off, what if you didn't need to feel important?


What would you do then? Imagine the energy you'd have. When conversing, all playing fields must be equal.


Pretend someone has a secret and it's your job to figure it out. Being interested makes you interesting.


That's how these things finished. Writing about the day all the way into scribbling down some kind of mantra.


Sarah gave me an idea, my muse for the day. I was probably in love already. Again.


I pushed away the keyboard and picked up a notebook, flipped through yesterday's notes and then to a blank page.


I wrote across the top. Everyone has a story to tell. There we go, I thought. That could be the book.


People like Sarah would be in it. I'd met plenty of people over the years, heard their stories, especially after dying twice.


Life gets reshuffled when you die. Charlie the curator, that's what I could be. I left the notepad on my desk.


The clock said late. I laid in bed, stared at the ceiling, noticed the patterns.


Thought about Sarah. Dangerous thoughts. Beauty inspires a man like nothing else. And it worked. A dog's sense of adventure bubbled inside me.


Because right before falling asleep, I had the outlandish idea that I could write my own story.


Chapter three. Water sprayed off the big letters every time the fountains came around, creating a small rainbow.


The rainbow looked good, but whoever designed the letters didn't think about the people walking into the building. The barrier helped, but mist still crept over.


I walked around it. A patch of grass sat out the front of the building. Each week the gardeners would trim the shape of a brain into it.


Inspiration for what we were trying to build or something. When the brain got too big, they'd come and give it a haircut.


I watched the fountains moving back and forth, remembered the guy talking about getting his helicopter licence. How scary it was.


When he's flying, it's a joy for his passengers, but he's on high alert. Like a lion stalking the jungle for prey.


No time to enjoy the scenery, only time to make sure he didn't crash and burn.


A human brain isn't good at focusing on more than one thing at a time, he said.


I didn't notice Sarah walking up behind me.


What are you doing? She asked.


When you're up in the air, you don't realise how close things are. You see the city from a different viewpoint.


Everything is smaller than you think. That place, which seems forever away in a car, is right there from the air.


You realise how much traffic sucks, man. Really sucks.


Charlie? She leaned closer.


I stopped looking at the fountain and turned to Sarah.


Oh hey, what's happening?


You were zoned out, dude. She laughed.


I told her about the helicopters. How this guy was talking about how hard they are to fly and how everything looks different up in the air.


That's cool. I like helicopters, she said.


I looked back at the fountains.


You'd think they'd turn down the pressure, so people didn't have to walk around the mist, I said.


I like pretending it's dangerous and I have to run away from it, she said, turning and running towards the entrance.


Then yelled out, Run Charlie!


The fountains started coming around. I picked up my bag and chased after her.


Sarah watched me walk in.


I'm getting breakfast. It's bagels this morning. You coming? She asked.


I'm not hungry. I'll get something later, I said.


Oh. I wanted to go, but I had work to do. I usually didn't eat until lunchtime anyway.


And refined carbohydrates were a one day a week thing. Not today.


Suit yourself. I'm getting two then.


We got in the elevator and pressed the buttons. The kitchen was on floor 34. Sarah got out.


Enjoy the double up. I put my hand up and waved.


Oh, I will, she said and walked out.


Floor 77 came up. Our building sat in the middle of the city.


Looking out the windows felt like flying over a forest. Except the trees were all made of concrete.


I sat down in front of my computer where I made my own world.


My computer's playing up on me here. Let's get that cover back up. That's a beautiful cover. Yeah, okay.


I sat down in front of my computer where I made my own world. Where my craft lived.


I typed in my username, the year I started, some letters of my first name and the initial of my last name.


I typed in my password, capital R, rainbow fox flower 77.


The security IT guy would hate that I'm writing this down.


It'll be changed by the time you read this anyway.


Three words. One capital, two numbers.


Easy to remember and as strong as some other unconventional combination.


You ever tried typing capital J, I, capital K, capital R, capital L, 443, exclamation mark, ampersand, K, F, N, S, M, E, at symbol, P, zero, multiple times?


They gave us time for working on our own projects. Mine needed plenty of resources so I tapped into the company's compute power.


Not that they knew.


I opened the XK1 folder. That was its code name.


No meaning at all. I told a friend if I was an alien, my name would be XK1.


It had no meaning then either. A better name would be NGEN or environment generator.


I wanted my little program to be able to create any scenario you wanted or didn't even know you wanted.


A computer generated world you'd be fully immersed in.


The stuff you see in the movies. Bugs crawled all over it.


But the prototype was promising. A full visual and feeling experience.


Hijacking the visual and motor cortex turned out to be easier than you'd think.


All from the comfort of an office chair. But the immune system?


Now that was a challenge. Immunity lives deep in the reptilian section of the brain.


Making someone feel cold is far more of a challenge than making them feel like they're about to jump out of an airplane.


No one else knew about it. I hid the extra compute power I was using under a scheme of aliases.


Something else this security IT guy wouldn't be a fan of.


Steve, floor 77 manager, walked past.


How's last month's data harvesting going Charles? He asked.


You harvest crops, not data, I said. Actually no I didn't, but I had that kind of wit.


We've got plenty to work with. I'll send you what I've found to the team later today, I said.


Keep at it Charles. This is why you've got a size three desk, Steve says as if he was making sure others could hear.


He walked off around the corner. Our desks came in different sizes.


If you did a good job or a good enough job for long enough, you got a bigger desk.


Of course no one actually said it that way, but that's how it worked.


They were numbered too. I looked at mine. Number 171.


Looking for Charlie? Floor 77. Desk number 171.


Oh, I'm having fun with this.


I'm just going to have a little sip of tea.


Wet the whistle.


And then we will keep going. By the way, the first seven chapters, what I'm reading through right now, are available to read for free.


So you can follow along on charliewalks.com.


Chapter four. Lunchtime.


I ate later in the day so I could test XK1 without being interrupted.


It didn't take long to load up. The building had plenty of spare computing power.


The way it worked was I plugged in and XK1 would read my brain, tie together my thoughts and create an environment.


Truth be told, I didn't really know how it worked to begin with.


A patchwork of things I'd read about and somehow the soup tasted good.


What would feel like hours in XK1 would only be a second or so of wall clock time.


Like a lingering blink.


The thing was, when it stopped, I never had a full recollection of what happened.


Like waking up from a good dream. Everything real, but not.


Yet, who's to say it wasn't?


Each time an environment finished, I'd write down what I remembered from it.


Skydiving, falling, on your own.


That was it. Three things as if I'd become a power trooper.


I didn't know why. Every time, the environment was different.


I had no idea what might happen when I went in.


Some might have considered the mysteriousness a bug.


Not me. I liked it that way.


I drew a line across the top of my notepad and wrote down what XK1 needed.


I'd built a black box bridge to the unknown, yet I still tried figuring out what next.


One, figure out how to prolong sessions in the environment.


Two, find out what actually happened in each environment.


Three, reduce the clutter of steps required on startup.


The question mark was intentional.


Still undecided whether I wanted to kill the surprise.


Maybe it could be a setting.


I stood up and closed my laptop.


Time for a walk.


A few times a day at 11am, 3pm, and perhaps another time, I'd do the circuit I always did.


A lap around the building, down the hill, especially after a session in XK1.


Any thought altering session took its toll on the brain.


The ritual became walk, work, walk, work, work, walk.


Like the push and pull of an accordion. Each required the other.


I'd get close to the water whenever I could.


I didn't need to be calm, but the water offered it anyway.


All the life forms under the sea, whilst we were up here.


Their own world, ours too. Organised chaos, I thought.


I kept walking, thinking, walking, thinking, mostly about nothing.


Sometimes I'd think of something provoking, thought provoking, halfway through the circuit.


And if it was worthwhile, it'd stick around until I got back to write it down.


All of my best ideas came from walking.


The last XK1 session came up. Skydiving, falling, on your own.


Was there a meaning there?


Despite my first rule, rule one, no explanations, I found it fun to attach one to things.


How? Through narrative.


What would Sarah think? I'd been thinking about her.


Every time I met a girl who said more than hello to me, I thought about her for days, sometimes longer.


Some from years ago, as if my next few actions would be subject to their judgement.


A clear sign I hadn't learned anything from my past lives.


I got back to work and stayed there for a few more hours.


Chapter five.


I liked to start writing as if I was writing a letter.


Partly because I lacked the ability to start from scratch.


And partly because my nephew, Paulie, had reached an age where he could read.


And quite well too.


Start with the date, the time, a little ramble about what's going on, a hello or good day and then get into it.


The personal touches. The rest arrived how it needed to.


And so, if you look at the format of the letters, this is just, it doesn't really show itself in visual.


I might put it up here.


Text that is part of the text is non-italicised but anything that Charlie writes is italicised.


So the letters, which you'll find later in the book, but this is the first letter.


So this is in italics.


Saturday, 11.53am.


January 19, 2019.


Dear Paulie,


Sitting at the local cafe this morning.


Jeez, I love this place.


The sun, the clouds.


I've only really started to take all this stuff in over the past couple of years.


Really started to pay attention to the beauty right in front of me.


You're already doing it, so nothing to worry about there.


Anyway, let me tell you about what happened earlier this morning.


I went in a plane.


There were 12 of us.


The plane could hold 16 but 12 felt like enough.


The propeller roared and we ripped along the runway.


And when I say runway, I mean a flat patch of grass cut down to the roots.


From far, smooth, up close, you felt every bump like a kick in the butt.


We really started to get some speed.


Going so fast, trees started to blur.


I peered out the window and saw the shadow of the plane starting to shift.


Then my stomach came up to meet my lungs.


Airborne.


We're in the air Paulie!


Past the tree tops, then the birds, then the clouds.


Usually after the stories my dad told me.


Any kind of height above eye level fills my body with a slight weariness.


But this was far too high for that to kick in.


The cars and trucks below were smaller than toys.


The pilots started speaking.


Five minutes until the drop zone!


The guy at the front nodded to the guy at the back.


Rick, the lead skied over, taps me on the shoulder.


Then shoved his glove covered hand with a thumb sticking up.


Then shoved his glove covered hand with a thumb sticking up in front of my face.


He lent into my ear.


Let's fly Charlie.


Rick spent more time in a plane than you and I have in a car.


Sweat rolled down the inside of my goggles.


You could feel the heat in the plane.


But this wasn't heat sweat, it was nerve sweat.


One time I told someone I thought jumping out of a working airplane seemed stupid.


Yet this jump would be my ninth.


Every other time someone else strapped themselves onto my back.


A tandem they called it.


Someone else who'd thankfully done the silly thing of jumping out of a working airplane far more than me.


Sixty seconds!


The pilot called out.


I turned to Rick.


How did you do it?


I asked.


He looked at me as if he didn't hear.


I spoke louder.


He yelled back.


Do what?


Your first solo?


I was drunk.


He laughed.


Really?


He nodded.


The first six times.


How about now?


He held his hands up towards his face.


Or his hand up towards his face.


Thumb and index finger spaced apart just enough so I could see his eye.


Signaling a little bit without saying it.


Terminal velocity for a human being is 190 km per hour.


Almost double the car on the highway.


Once you reach this speed you don't fall any faster.


Twelve seconds after I leave the plane door, I'll hit it then hold it for another forty or so.


I closed my eyes, clenched my hands and took a deep breath.


Thoughts rushed in.


Did I pack my chute right?


I checked it three times.


Was my altitude meter calibrated correctly?


They get tested every day.


Were my goggles fogging up too much?


Drip, drip, drip.


Did you count the number of sweat beads rolling off my forehead?


Once the door opened the wind would take care of it.


I opened my eyes.


Looked out the window and reminded myself of my training.


I'd done this before.


Plenty of people had done this before me.


Rick was drunk when he did it.


All I had to do was jump, check the horizon, ground, altimeter.


Horizon, ground, altimeter.


An altimeter is the thing that measures how high you are.


Once I hit seven thousand feet, stare at the needle, watch it hit six thousand, pull, check the chute, cut the chute if necessary, if not, guide it in.


Easy money.


Fifteen seconds, the pilot said, the final warning.


The jump light would come on soon.


You're on your own this time Charlie, Rick said.


We'll be right behind you, Rick tapped my shoulder three times.


Taps of reassurance.


Thoughts again.


Why do we force ourselves to do such things?


I smirked.


Showtime.


I'd get nervous in the build up, but when it came time to perform, I always put it on.


Rick moved towards the door.


Let's roll, he shouted toward the group.


His right hand grabbed the door handle, his left pointing to each of us.


That's Sammy first, then to me, second, then Pat, Charlotte, Chris.


Right in the middle.


The soloists got sandwiched in case something went wrong.


Rick ripped up the door handle, slid the door open, air rolled in, and the plane shuddered.


Rick ripped up the middle, Rick eyed the space between the pilot.


The jump light came on, and he waved towards the door.


Go, go, go!


Sammy stepped forward, then out, gone.


A full sized person shrunk to raisin spec in two seconds.


Let me tell you Paulie, gravity works quickly.


I turned, Rick eyed his watch carefully.


At this speed, we need seven seconds between jumpers.


He raised his left arm, my eyes followed.


Time to do the silly thing, I told myself.


Time to leave a working airplane.


I counted down in my head.


Seven, six, five, four, three.


Rick's arm swung down, he looked me in the eyes, formed his lifts in a circle, and let out a big go!


I rolled out, left leg first.


The wing caught it, and the rest of my body followed.


My stomach met my chest again.


I saw the plane, smaller and smaller, another reminder.


Gravity works quickly.


All that potential built up, waiting to show its face.


Wait, I shouldn't be able to see the plane.


Upside down, like a turtle on its back in an ice skating ring, slipping and sliding.


Every attempt, I'd make it rolling over, I'd lose control and slide around more.


Rick's words echoed in my head.


You're on your own, Charlie.


Reality kicked in.


190 kilometers through the sky on my own.


Twice.


We practiced this, laying on our stomachs, whilst raising our arms and legs towards the sky until we couldn't.


I tried.


Gravity had a different idea.


It seemed much easier on the ground, much easier with someone else on your back calling the shots.


Despite hurtling at nine tenths of terminal velocity, I considered my options.


Try to right myself and risk being too close to the ground when I pull my chute, or pull my chute and hope it yanked me into position.


Rick's words again.


You're on your own.


Bud.


Something hit me from behind.


Hard.


What the...


I shouted, there's an F word there, but it's bleeped out in the letter, so...


Paulie, I bleeped this out.


Careful with that word around your mother.


Rick hit me mid-air.


Hold on, Charlie.


He said through the swamp, swamp of air around us.


Rick balanced us out.


Shove his hand under mine, around my back and pulled.


The pilot chute went up.


The mini parachute before the big one.


Rick let go.


Purple and white exploded from my back and sucked air in.


My body rotted itself as Rick fell below.


I watched his chute come out, then checked my wrists.


100 metres above the danger zone, safe by standard skydiving measures.


Time to land.


I followed Rick's circles.


A big left pull, a big right pull, left pull, right pull.


Thought, hopefully he's not actually drunk.


On the final turn, I pulled too hard to the right.


I missed the target by six or seven body lengths.


My knees hit the ground, then my hands, then my face.


I stayed there.


Rick kneeled beside me, put his hand on my back.


Sorry, Charlie.


I looked up, let out a small laugh.


You did well up there, Rick said.


If you didn't stop the roll, I couldn't have helped you out.


You were about to right yourself, I could tell, but by then I'd already committed to coming in.


I had to, he said.


Maybe I should have gone to the Phoenix first, I grinned.


Rick's favourite bar.


We started laughing.


Rick helped me up.


In a few weeks, I'm going for my second first solo.


I'll pull my own chute this time.


You could come meet me at the landing zone if you want.


The letter could have ended there, but I always like to put a little summary at the end in case the message or moral of the narrative hadn't come through.


XK1 gave me these stories to riff about and send through to Paulie.


When I wrote this letter, I'd never been skydiving, so this is back to non-italics here.


I'd never been skydiving, but somehow the details spilled out of me.


Things I couldn't have imagined.


I'd met a drunk called Rick whilst driving Uber to pay for my studies.


That really happened.


He told me he's experienced skydiving, doing nine tandem jumps before his first solo, drinking heavily the first night and not remembering getting on the plane and doing the same thing for the next five or so.


My letters to Paulie, including this one, were often a love child of mixed realities.


Between the blurry experience XK1 offered and the stories I'd stolen from people like Rick.


Now we're back to italics.


Before I finish, let me add something I think you should know, Paulie.


Jumping out of a plane is about as on your own as you can get, but you don't have to leave a working aeroplane wearing an oversized backpack to appreciate that lesson.


Despite what anyone tells you about relationships, and I will be the first to let you to tell you how important they are.


Life is single player.


When you look at someone in the eyes, when you look yourself in the eyes, when you're lying in bed at night, when you're listening to the words come out of your mouth, you're the only voice in your head.


Your memories, challenges, joys, problems, pains, pleasures, feelings, thoughts, all yours.


And no one else is going to care as much about them as you.


Every time I forget this, every time I think someone is going to take on my challenges for me, complete my tasks, be as excited as my interests as I am.


Join me on every adventure I seek, I'm reminded.


Stop playing hide and seek with yourself, Charlie. You're it. You're it, Charlie. And so are you, Paulie. You're it.


One of the top three best feelings is self-reliance. When you know you can depend on your own skill and tact to deal with whatever gets thrown your way.


Even though I was scared, falling through the sky like a helpless bird who hadn't learned to fly yet, I was calm.


Being a little scared is a good thing.


You're a whole different person when you've got a good dose of fear flowing through your veins.


In fact, that's often when you're at your best. At least it is if you've practiced self-reliance.


Fear makes you feel alive. It turns your instincts on, makes you realize what you were built for.


If I didn't do things which scared me on a daily basis, I'd feel dead inside.


I've still got a ways to go, but I'm getting better. And the more self-reliant I become, the better it feels.


But I know we humans are social creatures. Full self-reliance doesn't exist.


If you didn't interact with others, how would you know who you were? For you to be someone, you need others.


It's more of a way of thinking, saying to yourself, oh yeah, I do have the fortitude. I do, I do, I do.


To endure whatever comes my way, instead of being consumed by fear, I can use it. Use it as nature's test of my abilities.


Instead of avoiding fear, seek it. Become immune to anything which questions whether you're worthy or not.


Because you are. Love you always. Talk soon. Charlie.


I put the pen down, folded the paper into thirds, put it in an envelope, licked the seal, wrote out the address, stamped it,


sat it on the edge of my desk, right underneath the flamingos.


And we got a little sippy sip.


This is fun. Very fun. The birds are outside, not sure if you can hear them. You might be able to hear a little bit of ambience. Cars driving past.


Chapter 6. Not much happened over the next three weeks. A project out of the office downtown.


The building had these colourless pillars out front. The inside matched one notch better or worse than the vibe you get from walking into a funeral home.


Each day I walked up and signed in and they'd hand me the tag. Sometimes there were no tags, so I waited while they wrote out a slip.


Keep the slip on you at all times, the security guard said. Once I had my tag, the security guard would call upstairs and ask for someone to come down.


Morning, I'd say. Morning. How are you? Good and you? Excellent, thanks. Then we'd go up in the lift together.


Chapter 7. Another day downtown. Sarah decided to move overseas. Germany. I'd read writers go to France. The two are close. Where do writers who are technology nerds go?


Back to the problem. I was stuck. I liked where I worked, but I liked working on my own project more. Stay at a large company with all the benefits and comforts of a large company that can offer?


Or leave and start my own? Two selfish choices. Of course I wanted the best for me. Doesn't everyone?


I turned it into a story. Two roads. One into town, well explored, known. The other, out. Newfound land or complete ruin.


And door number three? Well, I can't reveal all of my tricks yet. My issue? Patience. All the songs talk about wanting something, longing for it.


Then when they get it, the songs revert back to the journey. In my head, I was a writer in a company, a founder of a company. Charlie the writer, Charlie the company of one.


Did I just say that? Yes, really? Yes? That sounds good, doesn't it? Real good.


Did other people think these things? Of course they did. Except tragically, many of them never leave the warm-up phase.


The lady with the badge came down and said hello, and we walked over to the elevators. The doors closed in, and my fun thought experiment went silent.


Chapter eight. Usually I'd keep up with the things I had to do, then work on my own thing. Somehow, busy sunk its teeth in. Yes, busy with a capital B.


More and more things got added to the list. Every two hours, another email. Every ten minutes, another message. These were conservative estimates.


Ding, ding, ding. The distraction cannons loaded with instructions to kill any form of concentration. If it focuses, kill it, gentlemen.


I thought I was good at staying on it. You're slipping, Charlie. One thing to the next. Walks unclogged my spirit. I've already said I deemed them a necessary human activity.


If not, they helped me think of what to do next. How to climb over the wall, or most important, of nothing.


I'd get round the bend, up an eleven degree incline, then turn the corner. The trees always had rubbish under them, so I picked up a piece, or a few pieces if the situation demanded, and carried them to the trash.


Picking up trash had the dual benefit of making me feel good, while leaving things looking nicer.


Clean head, clean environment. Win-win. A real gangster knows the streets are his, as much as anyone's.


I knew I'd been outside when I came back in. The air conditioner earned its worth. I pulled my chair out and sat down. My shirt sandwiched itself between the chair and the thin film of sweat covering my back.


I looked at the list beside me. Before I walk, I write down what's next. Reply to Henry, fix the code on LMS, a project we had, name abbreviated for not yet understood reasons, one hour on XK1.


So that was chapter eight. We're past the samples that are available on charliewalkers.com. So this is, this is, I mean, if you read the samples, this is new territory. So strap in, people.


Chapter nine. XK1 started being pushed to the end of the day. I'd stay back, work on it. There were still things from the previous day, they had to be ticked off first. Terry messaged me.


You forgot, you forget to check in yesterday for the Kroger project? We're tracking the hours on this one. On it, I replied.


Tracking was a pain, but it had to be done. That's how business works in the big leagues. Surely you've read section 4.2. An employee must track the time they spend on all tier two and above clients.


Reading it made me nauseous. I was a show up and feel the spirit and let it happen kind of guy. A list on paper was the extent of my planning.


Maybe that explains why XK1, XK1 started to lag behind. A person is only capable of a certain number of things per day. I knew it though. You're doing too many things, Charlie.


My writing was slipping. My projects were slipping. Everything's slipping. I'd made this mess. Four chapters ago, self-reliance. Now this. I don't think I emphasized the words, ways to go, enough.


Chapter 10. No one was at the office early. I got there to work on XK1. Something had to go. The morning words got parked. I needed material anyway. We're friends now, right?


I decided on a less codename style way to refer to XK1. Sengen. Short for scenario generation. Say it a few times, roll it off the tongue. You'll like it.


Marketing a product with a name like XK1 would be like pushing a minivan uphill. We don't want that. We want the opposite. A skier heading down on a black run. Anyway, that's what it's called now.


Sengen was working better than ever. The interface better than anything on the market. From the outside, it looked like a broken home, but on the inside, it looked like the photos. You connected, hit start, and you were in.


Sengen creates a personalized scenario based on what it picks up from your limbic system. More specifically, the part of your brain which has the most traffic. That's as much as I knew anyway.


I hadn't told the system what to gather. It learned it on its own. As we've discussed, the motor and visual cortexes are easier to manipulate than you'd think.


But no way could I have thought up such a thing. I was a doctor of machine learning, so I taught the machine how to learn, and it did. I wasn't blind though. I knew this could turn out to be a roadblock. Anyone else would probably want to know where it all came from.


I didn't mind. I liked the surprise. Another top three feeling in life. Everything was already there. All Sengen did was lift the shadows.


What have I done, I wondered. I've created a hallucinogen. An electric powered hallucinogen. My great creation to show the world. Have a few alcoholic beverages or smoke the grass you got from your friend, Chop.


And you'll get the same effect. Like that time in Japan, sitting in a hostel lobby with the American telling me about his medically approved stash.


Here, have some of this, he says. Sure, okay. I had some and my brain turned inside out. This guy is trying to scam me, I thought. Get me high and then take all my stuff? Sleep? That's a negative. We're waiting this one out.


Despite the hellish night I had, I woke up to November snow in Tokyo for the first time in 60 years. And immediately thought, I need to replicate this feeling.


Everything looks new. Everything I thought about had changed. The veil lifted. What might became what is. The dubs flapped away.


The history books will show what a great inventor I was with the photos of the hostel and the bed I slept in. Yes, that's where it all started. Right there. Can you believe it?


But they'll miss, they always do, the part where I gave up on writing to make a technology driven version of being drunk.


People started coming in. Steve hurried through, reminding people, if you're on tier two, don't forget to start your timers. The reminder worked. I closed Sengen and started mine.


Oh, lucky number 11. How you liking it so far?


That's the pacing of the first few chapters, by the way, is that you can get that was just 10 chapters and we did that in how long? Half an hour. So that's how I wanted it to be. I wanted to just keep rolling with it.


Speaking of keep rolling with it, let's keep rolling with it. One and done, baby. Chapter 11. Floor 77 gave you the eyes of an eagle.


When I wasn't out walking and needed to think, I'd stare out the window. You could see right out to the mountains, a background to the city and below concrete all the way.


Who decided where the city ends? Who decided how high this building should be? Floor 77 was seriously high.


You knew it when you went right to the edge and looked over and felt your stomach hit your throat.


It wasn't even the top. The artificial lighting didn't help either.


Excuse me, just had to burp a little. The artificial lighting didn't help either. A real hospital aesthetic. Inside offered 500 lumens.


A sunny day outside edges towards 100,000. 200 times more. Think 40 candles versus 8000 plus vitamin D.


Fake lights, fake temperature sitting in a box. Some gold like character might look at us in the same way that we look at mice in a lab.


There wasn't much noise. Quiet enough to hear your own thoughts. But is that good or bad?


When I walked in, a few faces glanced up and then back down at what they were working on. Most stayed down.


What were you expecting, Charlie? A welcoming committee? A cheer squad? Let's be real. People have their lives and you have yours.


A few months passed and I got used to it. Used to being up on floor 77. Used to the light, used to the height, used to the quiet, used to the safety.


Spend long enough anywhere and you get used to it. Another night staying back. For work or CENGEN. CENGEN.


But it pained me. Another bug so I retreated to the window and stared out at the lights.


And decided to spend a good deal of time thinking of nothing. Until I remembered my game.


I'd make up stories about the buildings surrounding ours. There was the one over there with the blue looking windows and the curved glass pretty close by.


Word around was our company owned it. A space for the other division. The height of it allowed you to see in.


Their building looked like ours. I wondered if they had a Steve. Were their lights 500 lumens? Did they have a Sarah? A me?


I could see a cleaner walking around. The cleaner went back and forth, in and out, of each of the office spaces wearing a blue hat.


And headphones in. Music to drown out the vacuum perhaps. I began adding my own parts to it. His name was Bluey, after the hat.


Seventeen years he'd been in one building, cleaning to the classics every night. After listening for so long, he bought a second hand piano and tried to play the tunes he loved.


But stopped when it got hard. The creative virus died before symptoms started showing. He tried again then stopped. Decided cleaning was his thing.


He'd show up, put his headphones in, do what had to be done. Every month the check came through. Not much but enough. Enough for food, rent, school fees, books.


Having a party, the butcher would ask? No, just feeding the family. Four kids eat more food than you can imagine. Bluey took every second Friday off to teach his kids how to cook.


The company allowed him since he'd been there so long. They listened to classical music while they cooked. Cooking to the classics every second Friday.


Roast chicken this week, all the vegetables, carrots, potatoes, onions. Our company used robot cleaning machines. The building was littered with them.


Most of the cleaners had been let go. Thank you for your service. See you later. There was one who still came around to floor 77 though.


I'd spoken to him a few times. Surely not for long. Maybe the cleaning machines hadn't made it to Bluey's building. The other ones on the market were crap.


Ours were good. I'd written some of the computer vision code. Teaching a computer to suck dust and avoid furniture was easy.


Bluey thrust himself in the vacuum out of sight and my story ended just as an idea arrived. I turned from the window and walked back to SendGen.


Chapter 12, and this one's all in italics as well because it's a letter to Paulie.


Wednesday, 11.35am, April 10, 2019, Christchurch, New Zealand. Dear Paulie, we've been on the road. Met Richard today.


He took us aboard his ship. A little blue one with wooden boards for the floor and a roof over the top and sheets on the side to stop the wind.


Thank God for these sheets, I thought, because the wind howled up like a pack of hungry wolves and waves were coming like savages.


Kind of the opposite to what's going on now. Before we hopped aboard, we rolled up in the van, got out, started taking photos.


The lens needed to clean, so I cleaned it and started taking more. Richard saw me and called out. I didn't know his name was Richard then.


Does this still work, he asked. There's something on the lens. I'm testing it out, I said. Okay, I'll keep smiling then.


We walked over. The boat nested itself on the back of a trailer at the end of a rock pier.


Four coffee cups stood on the starboard. That's the right side of the boat, railing with a filter above each.


A filter is what you use to let the water flow into the cup, but not the coffee grounds.


Do it right and you get the coffee, but not the grounds, my favourite kind of bean water.


I turned to Merlin. You want something? I asked. Sure.


I turned to Richard and ordered. We'll take two coffees please. They were Stroopwafels too. Dutch cookies with honey, butter, cinnamon.


All the things you need to create magic in biscuit form. And two waffles please, I said.


I didn't know they were called, I didn't know they called them Stroopwafels until after.


Merlin's turn came up, so he handed over a 20. I turned to Merlin and he turned then back to Richard.


Oh and he turned to me and then back to Richard.


Merlin's turn came up, so he handed over a 20. One and done, remember.


How do you know each other, Richard asks. I turned to Merlin, he turned to me, then I turned back, then to Richard. The internet.


We talk about different things online, I said. What do you talk about, Richard asks.


I turned to Merlin, he turned to me, then back to Richard. Books. Mostly books. What books?


I told him, then went on. Books, life, writing, girls. More about life than more about girls.


Most of the things young men talk about. Most of what we talk about, Paulie. Minus the girls.


But we'll get there. We kept talking for a while, I introduced myself. I'm Charlie.


Richard told me his name. I pointed to Merlin, said, this is Merlin. We all shook hands.


The lady of the ship started speaking, said her name, Monique. Charlie, I replied.


We shook hands. Richard stepped forward. Do you want to come aboard? He asked. Sure.


Merlin and I put our coffees to the side and climbed over. The little blue ship had space for a waffle oven, coffee supplies and the four of us.


I picked up my coffee, sipped it, enjoyed it, bit into the stroopwafel, took another sip and repeated the process.


You like writing, hey? Richard said. Yeah. It helps me get my thoughts together.


I get lost in thought but found in words, I said. Like a snobbish writer, poet type. That's amazing, hey?


Richard threw a hey onto the end of each sentence as if it was meant to be there. I liked it.


It's a creative outlet. Everyone should have some kind of art, I said. Richard spoke strongly.


Yeah, mine is coffee. Coffee and sometimes rock carving. Richard pointed to a pillar on the port, left side.


A nail stuck out with a piece of ribbon hanging from it. The ribbon pierced through the top of a stone heart.


I carved that, he said. I looked at the carving and then back at Richard.


When did you come to Greymouth? A small town on the west coast of New Zealand, I asked.


28 years ago, he said. And what made you choose here? Ah, let me see.


Young I was, around your age, and I wanted to leave Holland and explore, hey?


So I did and I went to a few places. America, a little in Australia, all around New Zealand.


And then I ran out of money, so I got a job here and I really liked it. Since then I've never left. Been here ever since.


What job did you get, I asked. Deer hunting. I shifted my head. Deer hunting, I asked.


Yeah, out of a computer, out of a, out of a computer, yeah, out of a helicopter with a rifle, hey?


He said. Richard put his hands into a gun-holding position.


New Zealand had this feral deer problem, hey? Oh yeah, really bad.


They'd get into the farmlands and disturb the other herds, so we went round hunting them.


First on foot, then out of a helicopter, then when they were really out of control, everywhere, hey?


I grew up on a farm, so I had experience with a rifle, he said.


What did you do after deer hunting, I asked. Oh, some fishing, some farm work. Now I am here with my sweetheart.


Richard smiled and looked at Monique. She smiled and chuckled.


How did you two meet? Here in Greymouth, I asked.


Oh, you were like this. We met at primary school actually, back in Holland.


Then three years ago Monique was travelling through New Zealand and we met again.


Right here in Greymouth, he said. Monique started speaking. Yes, I was visiting on holiday.


I had looked it up the night before. Greymouth had 13,000 people and Merlin and I had been around the town the day before.


You could walk end to end in 20 minutes, 10 minutes if you're not taking notice of the scenery.


I looked at Monique and Richard and Merlin. Wow.


All the way from primary school and now together in Greymouth, I said.


We met again whilst there was holiday. Then I went back home, collected my things and came back to stay for good, Monique said.


Oh yeah, great hey, Richard said. Then we started this. I wasn't into coffee until Monique showed me.


We kept talking, sunk into a second coffee and dropped the coins we had into the cup to partner it with another Stroopwafel, a requirement.


I told Richard about my writing. How writing letters to you helped me think.


How I'd figured out the secret was to keep doing hard things. Pleasure seeking didn't work out for me. Pain was more interesting.


It became pleasure, the purest kind. If you did it right, items aren't as important as people and nothing more than health and relationships.


Simple lessons. Everyone wants to be loved and to love, to feel important.


Making things, making art, give better highs than any drug.


Money stands in the shadow of the best currency in the world, the effect you have on others.


Have a mission or don't. Improving at something gives one a purpose and if you lack purpose, at least be playful. It'll come.


Self-love, self-reliance and surprise are the top three feelings in the world. Life goes on, shit happens.


It's elegant to endure and enjoy at the same time.


Sitting on that boat, I'd become a real philosopher. Someone who practices philosophy, the love of wisdom.


Charlie the philosopher, Paulie the philosopher. We're all philosophers. I take that back.


Not everyone is a philosopher. Some people don't think at all. What a shame.


Richard spoke. It took me a long time to learn those things. None by your age, he said.


Richard looked at Merlin. How about you? How are things in your world? He asked.


They're good, Merlin replied. Richard nodded toward me. You're learning from this guy? Merlin nodded.


Yeah, that's good, hey? What about work? Do you work? Richard asked.


I'm a cleaner at the stadiums. I get rid of the bird before the games, Merlin said, which reminded me.


Some of my best conversations have been with janitors. You write too, Richard asked.


Yeah, I have a website. I write there sometimes. You too, hey? Richard said. Merlin smiles.


Richard keeps being friendly. You know what you want to do next, yeah? He asked.


Not really. That's okay, hey? Look at me. Travelling around the world. No clue.


Then I stop here, hunt deer, meet my sweetheart. Now I am serving stroopwafels. I never thought this ever. Never.


Richard and Monique laugh. A happy laugh. Merlin and I join in.


Part of the laugh is how we're all in a boat in the screaming wind, sipping coffee and biting discs of sugar, talking about life.


Let me tell you, Paulie, laughing is an international language, a way of communicating to each other that everyone understands.


Or doesn't. Not knowing is often far more funnier than knowing.


If you want to make friends with someone, laugh with them. Richard looks at Merlin.


I want to give you something, hey? He says. He tiptoes across the boat, towards the pillar, picks up the stone heart off the nail.


Every so often I meet someone special, he says. I tell you, I do some carving now and then. This one, this one, it's a soft stone, you know.


A stone which is easier to carve. I carve it and then wait for someone special and I give it to them.


He reaches towards Merlin. I want to give this to you, hey? Merlin reaches out, lifts the stone out of Richard's hand.


Thank you. Yeah, I think you deserve it. You are here, young, on your journey to figure it out.


Richard looks at me. You're a bit further along, but you help each other, hey?


He's younger than you, so you teach him what you've learned and he reminds you what it's like.


I smile. We're all sitting around, I look to Merlin, Monique, Richard, my empty coffee cup.


We better get back on the road. Thank you for the coffee. The... wait, how do you say it?


Shrop waffle... strup... strup... stru... strup... don't worry. Thank you for the coffee, the waffles, the conversation.


I say strup waffles wrong again for the third time, but they get it. Thank you too, Richard says.


This has been amazing, hey? This is why we do this, to meet and talk with special people like you.


Merlin and I smile. Our smiles say thank you and the feelings are mutual.


Come to think of it, Paulie, I can't think of a single moment on the boat I wasn't smiling.


You know what happens when you're in the company of good people? The energy spreads like a beneficial virus.


Merlin and I hop off the boat, turn around, look back in, Richard sticks his hand out, hands us his card.


If you're ever in town, come see us, hey? Of course. We shake hands, say a few more goodbyes, smile.


In the car I look at the card and then to Merlin. How good was that, I ask.


Real good, he says. I look at the card and read it out loud.


What's meant to be will always find its way. Again, slower.


What's meant to be will always find its way. I show Merlin. We laugh.


We drive off and got back on the road towards the next place.


We're going to a place with rocks shaped like pancakes.


And apparently there's a guy there who runs a glow worm tour.


Any operator who runs a glow worm tour is a character I'd like to meet.


Anyway, dinner soon. I trust you know the takeaway from this one. Richard did it for me.


Trust nature and remember what's meant to be will always find its way. And if not, ask for it.


Love you always. Talk soon. Charlie.


P.S. I'll show you Richard's card one day. I'm going to hang it in my room.


Who knows? Maybe we'll even buy a ticket and go visit.


Now we're back to that was all italics because it was a letter to Pauley.


Up to chapter 13. How's the book going, Dave asks. Terrible.


I've said yes to too many things, I told him. You've got to finish it. It's important, he said.


My arch nemesis and best friend. Actually, friend wasn't strong enough.


Brother. The sibling rivalry meant it pained me to admit. To give him the one up, but he was right.


It was important. Important to finish or better yet, at least follow through with things that are important to you.


Other things got in the way. A collection of good fake becauses.


The kind you use so the other person will understand. The good reason and the real reason.


Saying yes to too many things was the good reason, but the real reason was perfection.


Perfection sunk its teeth in waiting for me to keep going so it could tear off a little flesh.


This book had to be the best book in the world. Everyone had to love it. That's how it needed to be.


Nonsense, Charlie. You know what you lack? Ignorance and arrogance. You need both.


I was gaining them. Gaining them as the words flow. As Dave reminded me, it was important.


Ignorance? Ignoring the possibility. No, the reality. Not everyone would love it.


Once that kicks in, it would be bliss, bliss, bliss. When you realize you're the only one in your way, everything becomes a dance.


Arrogance meant putting your soul out there on display. All of it. Right there in the window.


I'd become a traitor. My deal? Authenticity for affection. Affection feels good.


The love of another. I'd conform for it. Do the things. A puppet connected to a string.


Tied to the fingers of whatever the source of control was at the time. Girls, peers, bosses.


Dancing, moving, operating, whatever. Never lose the love, Charlie. Never.


Who can deny? It feels good when someone else loves you. Feeling loved gives one energy.


Oh, but there it was. Always there. The prod in my side. The knot in my stomach. The hairball in my throat. Always there.


Have you felt it? Perhaps you've discovered what it is. What? Authenticity.


Tapping at the window. The truth. Screaming to come through. Poking, prodding. No wonder it's trapped.


You feel it come up, but you push it down. No, no, no. Back down. You stay there. Quiet.


We've got love to earn. Affection takes over. The approval of others. Love. All those sweet feelings.


Now you're stuck. Affection builds up. Those sweet feelings build up.


Ho, ho. I like this. You say. And guess what? It's now a requirement.


The addiction makes itself at home and it needs to be fed. Fed four or five times a day.


Hungrier than a newborn Labrador pup. All the love in the world isn't enough.


Every time you get close to satisfied, authenticity steps in. Look at this. Look at me.


Poking and prodding. Saying, look, look, look. Remember me.


Strange thoughts before work on a crisp pre-winter morning.


You never know when they're going to show up, but you can practice. You have to show up first.


Step on stage. You've got a performance to do, young one. The Muse. Oh, the Muse.


Such a beautiful woman. And she will dance with you. Oh, yes, she will.


But only, yes, only, only if you're on the floor first.


Dave knew me well. Like all my all good arch nemesis is.


Well enough to know my bullshit. Well enough to know what was important to me.


Don't be fooled. I knew myself well enough too, but I kept using the good reason. Why?


Because the good reason is the easy reason. Others understood the good reason.


They used it too. No explanation required. Remember rule one.


No explanations. Tell me again. Who doesn't love affection?


I'm patient. I can wait. Got an answer. Do you? Well, I'll fill you in.


It means nothing when authenticity shows up. Truth bearing your soul has a power like no other.


I felt it. I'm feeling it. Submerged in the it-ness.


Energy distilled, baby. All this time. The other things.


The string of yeses getting in the way. I knew what I had to do. I, Charlie, me, knew what had to be done.


It pushed and prodded me all day.


Maybe you're the same. My real reason.


Write the best book in the world. My book. It's important.


Chapter 14.


A meeting. As usual, I'd forgotten about it. Timed events were outside my circle of competence.


My style was roll in, do the tricks, think about Sengen, think about writing, always about writing, go for a few walks, leave.


But there were business matters which needed attending to.


And someone decided that for any project, a series of experiments where everyone gathered in an airtight room for an hour or more was helpful.


We went in, started talking about the project. We had it for the client. Everything going well.


Coming in on time, on budget. Two miracles.


All the typical business metrics look good. Real good.


The problem? Communication. Always.


Despite sitting in a room for hours at a time with each other, sometimes multiple times per week.


You think we'd learn?


One person thought we were doing one thing. Another thought another. I thought something else. And we all thought we were right.


Okay, okay. Now we've figured this out. Is everything going as smooth as it seems? Who knows? Come on, let's figure it out.


I started speaking.


What's the due date? I asked with a little haste. I'd hate deadlines more if they didn't work.


Amber spoke.


I'm not sure. Pat hasn't given us anything. Something to do with contract issues.


Ah, the document problem.


I'd come to realise much of modern work needs to be documented before it can even take place.


One might think documenting the thing is more important than the actual thing.


Well, I'm going to keep going with what I've been doing, I said.


What does the client need it to look like at the end?


The security IT guy spoke. He threw out a lot of $10 words, many of which I didn't understand.


A doctor of machine learning, a practitioner in the process of teaching computers how to learn,


but I still found myself confused by the jargon filling the air.


Wasn't there a simpler way? Yes. After spending a second or so making sense of what he said, I spoke.


So you mean they need to be able to access a demo?


He thought about it for a moment, looked at a wall, turned back.


Basically, yeah. I kept it simple. I had to. I was good at what I did, but anything beyond my responsibilities,


like sitting in poorly ventilated rooms at scheduled times, I drew the line.


After yesterday, all I could think about was writing the most important book in the world and its sole creation.


Be readable.


Sorry, after yesterday, all I could think about was writing the most important book in the world and its sole criterion.


No one wants to read crap, see crap, hear crap. That thought started spilling into everything.


Charlie, Amber asked, sidetracked.


Yes, I replied.


Are you going to keep going with what you're doing? She asked.


Yes.


The meeting ended. That's how most went. How are you going? Good. Any roadblocks? No.


Are you right to keep going? Yes.


Sometimes a moose would make itself comfortable on the road in front of you.


Not a real moose, of course. The moose is a metaphor for a roadblock. A problem, yes, but nothing that couldn't be solved with a little time.


Meetings were a roadblock, but they had to happen. That's how business works.


Don't you know? Doing something? No, wait. We must talk about it first.


The endless calendar events, too. All of them. How things ever actually got done perplexed me.


The calendars were clogged. Someone thought it was... I just found a typo. Beautiful.


Someone thought... Oh no, we don't need that.


Someone thought it a good idea. Everyone should have access to everyone else's time.


Oh, I saw you had a small piece of white space between 1.36pm and 3.17pm, so I've slotted in a progress catch-up.


But yes, that's how business works. I was part of it. Part of an overscheduled experiment. I had to be.


That sweet chick which showed up every second Friday depended on it.


But that didn't stop some of the practices making me ill. White space. A little time to rest one's noodle after a prolonged period of thought.


No, sir. We must make the most of every second, but the $10 words, they weren't needed.


Believe me, when your idea is simple or better explained simply, more people understand it.


More people want to see it happen. Including me.


I went back to my desk, sat down, looked at the time. 10.07am.


A whole hour in already, I thought. Read my notepad, saw the first thing on the list and started.


Chapter 15. I went around the corner, picked up a piece of trash, felt good about it.


Kept walking and went back to watching the movie playing in my head.


An ideal set-up. A hero, a challenge. Hero solves the challenge, comes up against another, no one thinks he can do it.


And then he does it.


Another movie started playing, one where I didn't figure things out.


Sengen went to ruin, my writing never took off and all those letters to Paulie meant Jack.


Who was I to be sending out these stories like I knew what was happening?


Thinking like this forced a little laugh out of me.


And soon after I realised I didn't like that movie so I changed it.


I'm writing the script anyway.


Cut. Charlie. The director. The writer. All of the main characters at once.


I was rational about it though. Another laugh. Rational. What a word. Too formal. Real is better.


I was real about it, you know. Didn't need thought either.


When you think you can predict the future too much, people might start to think you're crazy.


Me? Crazy? No, no, no. I was real. I'm not crazy.


Christ. I found it. My movie had to be changed. A fatal error indeed.


Charlie, here's what you have to do. Take more chances. Allow for more challenges to arrive.


They make the story better anyway.


Imagine the hero being born. Everything going his way and then him dying.


That's no hero. That's one of the rich, spoiled kids you see crying when they come forth.


You remember fifth grade, don't you?


Get too used to winning and it makes you weak. Capiche?


Yes, win and keep winning. Oh please do. But take a hit once in a while.


I rewrote the movie as I walked. The solution? Do more things that might not work.


It didn't make sense but it did. I saw a girl at the cafe. We locked eyes.


Then hers moved away and so did mine. She was cute. She looked like Sarah but Sarah was in Germany.


How would I explain it to the girl? How would I explain my solution?


I smiled and thought of how. Excuse me beautiful.


You see, just now I've thought of the solution to all of this.


Yes, you wouldn't believe it. Just on this walk.


Around the bend up there and it hit me. Can you believe it?


The solution to all of this is to do more things which might not work.


The wind doesn't really help this changing the page.


Surprise myself more often. Oh yes, profound isn't it?


But that's how. But that's it. I've got no time to explain it now.


I've got to work to do. You'll have to think about it for a while.


Perhaps we might discuss it over dinner sometime.


I know a place down the road. I think you'd like it.


St. Jane wasn't yet singing the tune I wanted it to because I'd stuck to the things I knew.


My writing? Smack the reader in the face. Gently of course.


I knew how to fix it. How? More risk Charles. Come on. Venture out.


Thrust yourself into the unknown. Embrace the darkness as if it were a warm blanket on a cold night.


And if it doesn't work? Well, if it doesn't work, at least you know what doesn't work.


Chapter 16. Last name? Company? The woman asks. I read her name tag.


Nikki. I told her my information. She typed it in and hit a button.


The label came out. She peeled it off and handed it to me.


Thank you, I said. A pocket hung off the left side of my shirt, so I put the label on the right side.


Ornaments hung around the lobby. How could one describe them?


We were visiting a science building, so I guess you could say the ornaments were old science tools.


You could tell by the colour. Old colour. You know, the brownish green, some of them decades old.


Music played too. The sound of trickling water without the water over and over.


Whenever I got there before Rob, I'd sit and listen to the sounds and look at the tools.


Sounds, tools, sounds, tools. I'd forget if I was listening or looking.


That's how you can tell good art. When you've got no idea what it's supposed to be, but it gets you.


It got me. Rob appeared. Hey man, he said.


Morning brother. I turned to the wall and looked back at Rob.


Have you heard this music? I asked. Rob looked around the lobby.


It gets me. I don't know what it is, he said. It got Rob too.


We got on the lift and I swiped the tag security gave us. The building had three towers.


We were in one of them. Two or three weeks in, we started to remember the maze we had to go through to get where we needed.


Up the lift, out the doors, through the fire door. The big thick hinged double-plated door in case the experiments went bad.


We can shut off this whole section, they said. Through another fire door, down the hallway, past another lift, but not in it.


Past Sandy's office. Morning Sandy. Then our desk. We're third on the right.


Deep in the digestive system of a building filled with some of the world's top researchers.


And now Rob and I, we're here to help. We set up for the day then left.


Back to the lift, we walked past the one we didn't go in.


A ritual took form. Get in, set up, go to the lift, go up to the cafe. Rob got breakfast, I got coffee, then we sat outside.


The only floor with an outdoor area. I got my notepad out and we planned the day.


Planning the day gave us a chance to figure out what the hell we had to do. No exact map. A compass.


People walked past. Name tags with pictures hanging from the hip. A way to keep track of who was who.


They looked official. I wondered what they thought of us. Would they catch us? Us and our printed labels.


We're done for Rob. They've got us. The show is over. Let's get out of here. Every time.


Every time we weren't at HQ. Am I really supposed to be here? There's a psychological term for this feeling.


Imposter syndrome. Feeling like you're someone you aren't. Somewhere you shouldn't be. Yuck.


I felt it, but then I realised I was smart enough to push past it. So I did. How?


Get better at whatever it is you're doing. Confidence comes with skill. Build skill and the imposter syndrome will fade away.


Also, avoid comparing yourself to your peers. Engineer to engineer. Writer to writer.


Be more concerned with the people you're trying to serve. Their only interest is you solving their problem.


They do not care how advanced your solution is. The reader's only interest is being dissolved into the story.


They do not care how. Back inside. The elevator doors opened and we went in. I scanned my tag and Rob pushed the button.


Rob looked around. They must be doing construction around here. There's sheets all over the lifts, he said.


I looked around. I think you're right. The doors opened and we went out past Sandy's office. She was standing in the hallway.


How's the new place? I asked. Sandy turned around. It's great. I've got two dogs now.


Felix and Coco, she said with the excitement of a bird at sunrise. She pointed to the wall.


Half a dozen photos of dogs pinned to a board. Felix is the black one. Coco is the brown one, she said.


Sandy told me she took care of houses. When the owners weren't there, she moved in, took care of the pets, kept the place clean.


She hopped from house to house. Every time she moved to a new place, she took photos of the pets and put them on her wall.


A welcome innovation, I thought. Give this dungeon some colour. Her energy entered you via osmosis.


Like one of the contagions they kept upstairs. I loved hearing the stories. It attracted me to her.


It had happened again. Every woman who could tell a story was some kind of fire in her breath.


I couldn't tell whether it was the woman or the story. Maybe both. Maybe neither.


Sandy finished telling me about Felix and Coco. Two walks a day, she said. One in the morning, one in the evening.


Just like me. Not too far though. Coco's hips weren't what they used to be. I wouldn't mind that.


The more walks the better. I went back to my desk. Rob's fingers stopped tapping.


How's Sandy? He asked. Good. She's taking care of two dogs.


I heard, he said. No secrets down here, is there? Multiply the acoustics in this dungeon with Sandy's enthusiasm and you get the equivalent of an underground town crier.


We smiled and laughed a little. Then got into it. We weren't underground. More like six or seven floors above ground.


But the lack of natural life induced cave-like feelings. Another meeting with the clients later in the afternoon.


They'd be expecting something. Results, results, results. Oh, and the pictures. Can't forget the pictures.


Rob told me about the rubber duck. A powerful problem-solving tool. When Rob was stuck on something, he talked to me about it.


Then I'd do the same. Talking out our problems as if we were talking to rubber ducks.


The yellow ones you find in bathtubs whose actual purpose evades me.


One named Charlie and one named Rob. Lost in thought, found in words. We were trying to teach a computer to read.


There were records. Records made by doctors talking to patients. A familiar challenge.


It was hard enough for me to take notes about my own thoughts, let alone teach a computer to read the notes of someone else about someone else.


We'd work then talk. Work then talk. Conversation kept us sane. Maybe that was our problem too. Not enough madness.


One day Rob turned to me and said, hey man, I've been thinking. Paused and kept going.


I've been thinking about it and you're legit. My ears said, what? Rob continued.


Yeah, when you first started here, I thought you were putting it on. What do you mean? I asked.


You were so excited, saying hello to everyone. How are you going around being all energetic and all curious?


I laughed. Really? I asked. Yeah. And I thought it was all an act, but after working with you for a while, I thought to myself, wow, he's legit.


I smiled. Realised I'd received a pinnacle of Rob compliments. Laughed. Thank you, Rob.


Yeah, man. You're legit. We hadn't spent long enough in the dungeon to be numb to it yet. There were plenty of other workers there.


You could tell they'd been there long enough for it to sink in. How? The eyes and the waist. One second of eye contact and you'd see it.


Each on the verge of snapping and setting the whole floor on fire. Or maybe that was me.


Lucky there were fire doors aplenty. Their waists bursting at the seams. One so much, he looked like a snake who decided to test its jaw dexterity by consuming an adolescent hippopotamus in one hit.


Compensating for the lack of fresh air and natural light with an excess of calories. One lady had six, yes six, I counted them, bottles of soda on her desk.


Lined up in break in case of emergency fashion. Except the emergency was every 90 minutes. Lunch? Rob asked. I agreed.


I scanned the tag, Rob pushed the button and the doors closed. We went back up to the cafe where we made the plans.


I had my own food, meat and vegetables, but checked out the offerings. They looked good, smelled good, real good. Cursed I was. Studying food will do that to you.


The place was littered with refined carbohydrates and fried blobs. All the things on my avoid at all cost list.


How could this be, I thought? We were in a world renowned health research facility and all the food options were basically hog feed.


If you had no regard for the hog's arterial walls.


The same stuff they'd feed the testing animals on floor 14. While Rob ordered, something crazy occurred to me. Perhaps we were the testing animals.


In order to have some chance of photosynthesizing, I sat outside. The computers we were teaching to read didn't need sun or air, but we did.


A good engineer knows what they need. Sunlight, air. A great engineer knows what they don't need. Fried blobs, refined carbohydrates.


We finished lunch and went back down. I remembered the meeting. Not long until the meeting. Results, results, results. We talked about it over lunch.


Rob agreed I could do the talking. It made sense. He recognized my ability to a rate at length.


And that was fine because he was better at the things I wasn't good at, like programming the interface to scan the doctor's reports and make them digital.


We balanced each other out. I put together notes for the meeting, drew some pictures, made some graph graphs.


Our work was good, but none of it would matter if we couldn't tell a story about it.


I obsessed about the questions they might ask. I told Rob, Rubber Duck Rob, when I thought of a new one.