Author Archives: kirk.kittell

Traces

Trailhead: Richard Campanella. Electric Avenue: New Orleans' own Champs-Elysees was once extraordinary -- and could be again. New Orleans Times-Picayune (2018-06-10). (Courtesy of Rob Walker's The Art of Noticing newsletter, #61: Hunting for Feelings)

Go ahead and read that article and come back. I'll wait right here.

...

OK. A secret pastime of mine is paying attention to places where old bridges, roads, and railroad tracks show their haunted remains in the current scenery. It's almost an obsession to look at satellite images and see where railroad tracks used to be—that diagonal line of trees cutting across otherwise square cornfields, swooping into a small town, the 45-degree diagonal bending at the last moment as it intersects the town and matches up to the street grid.

In real life, there was the gully across the street from where I grew up in St. David where the railroad used to branch off the main line and go to the coal mines.

And there's the place in Lewistown where the railroad branched off the main line and crossed Main Street near the high school, and connected to some other line that must have gone into downtown and on toward Cuba—anyway, wherever the ends went, the middle used to cut across the edge of our yard. And at camp there were the remnants of old County Line Road, between Knox and Fulton Counties, now partially underwater since the dam for Lake Roberts was installed in the 1970s. (Bonus points if you ever found the remnants of the house on the east side, near Horseshoe Bend.) And the hulking grain elevators that you can see, a dozen at a time across the glacier-scraped middle of Illinois, giving away the shape of old rail networks that no longer exist. And there are the old mining roads and trails that I explored in Panamint.

Panamint City, Surprise Canyon Road ("Road")

I could wear you out with examples of old roads and bridge pylons and on and on. But it's not just the remnants themselves, but the remnants of design decisions that sprung up around them. In that New Orleans article, it mentions how the old canal and railroad still exist, not in their original forms (they're long gone), but in the shape of the neighborhoods around them, in the long empty stretch to the river where they used to lie, in the names of places that survive.

Here's another example: Tanner Howard. Native American routes: the ancient trails hidden in Chicago’s grid system. The Guardian (2019-01-17).

And in Manhattan, Broadway, which meanders against the grain of the rest of the island's grid, was once the Wickquasgeck Trail, where it was once a sensible route across swampy land.

Some traces weren't on the land, and their remains are getting smaller and smaller, forever and ever, amen.

So many of the reasons that things were built have since buried or lost or burnt or rebuilt or unbuilt, but their influence remains. I wonder about that from two sides. (1) Do the old roads tell us something that we're missing? We can knock down any hill or fill in any swamp now—we have the tools and we have the talent, etc. It's not quite Chesterton's Fence, since the fences are long gone, just the bend in the road where the fence used to be. (2) What are we—what am I—building today that will shape the layout of the future? Are we being good ancestors? (See also: The Long Now Foundation.)

I don't know if I'm the only one with this habit of finding the traces of old things in the current. It's not like I chose the habit, it chose me. There are people like Sarah Parcak whose literal job is searching for traces of old things from space—so maybe I chose the wrong career path.

The Captain's Newsletter, 2021-W02

The Captain's Newsletter, 2021-W02 - Out of control

This week in the newsletter we explore 1980s children's TV, explore drawing, explore the wilderness, explore shipping version 1.0, explore corn tortillas, explore unstructured time, and explore our technique. Everything is exploration if you look at it hard enough.

Wander with us: /captain.

Many other links don't make the newsletter: notes.kirkkittell.com.

Early garden planning 2021

This year it's time to put in a proper garden at the house.

We've already prepared the west side, installing a little sidewalk around the garage with some place to plant flowers and maybe some vegetables. The backyard, though, is where the real work will happen.

The project to flatten the backyard—installing a retaining wall behind the deck and some steps down from the garage back door— is getting... well, it is less unfinished than it was a few weeks ago. The wall is in good shape, but the steps need more time. And there is still a huge pile of dirt ("dirt"... more like clay) from the excavation piled up in the yard. That all needs to be pulled sideways to being leveling the lower side of the sloped yard, and some of the high side of the yard still needs to be dug out to bring it to level. Hopefully that will all be finished in a few weeks, before spring arrives

Let's consider finishing the hardscaping as Project 0—finishing the shape and size of the garden.

Speaking of the pile of dirt/clay: that needs to be fixed to grow anything well, even grass. It's awful. We planted a few potatoes last year, and the only one that grew only made it to about 2 in x 3 in (5 cm x 7 cm). That's it. That's as far as it could push the dirt around it to grow. Some of the other plants grew with ridiculously small root systems. That's it. That's as far as they could push the dirt.

So that's Project 1: fix the dirt. Probably that means raised beds for growing, at least in the short term. Long term, something should be done to build a good layer of dirt on top of the clay.

Project 2 is the most interesting for me: plant interesting seeds. I'm looking for old varieties—heirloom seeds and Missouri natives, plants that are the very definition of the place. I'm not against the modern hybrids, it's just that I can buy those at any grocery store, so they're not as interesting. (And they don't taste as good.)

Project 3: optimize placement. How do I keep fruit and flowers going in multiple seasons? How do I keep tall things from blocking small things? How do I mix plants to keep them from attracting pests? How do I get bees to come and help pollinate things?

Project 4: introduce automated monitoring and controlling. It's not necessary, it's just interesting. Why not teach the garden to decide when it needs water—and then water itself. How can I take data about which areas of the backyard get sun at which times on which days? Where does the rain fall, and where does it get blocked by the trees overhead? Which spots get hotter and cooler, more and less humid. How can you sense the health of a plant—size, color, chemical properties in the soil—and have it call for help? Can I power everything with solar panels? Can I store rainwater and use it instead of watering everything from the tap?

Left to my own devices, I would probably turn the entire backyard into some weird jungle garden. Fortunately I live with someone who has taste (and a degree in biology), so we might be able to turn it into something good.


Some resources I've found so far to answer a few of these questions:

Post-NLP class notes

This morning I took a 4-hour course through O'Reilly about natural language processing with Bruno Gonçalves: Natural Language Processing (NLP) for Everyone. (ramshackle notes)

(Side note: I've tried several O'Reilly events this year, for various business and software topics, and they've all been good. We get access free through my company, and it's safe to say that O'Reilly access is my favorite company perk.)

NLP is one of the things that I've been wanting to dig into for years, so I signed up for this one. (In short: NLP is machine learning applied to comparing, categorizing, and creating human language text.) It's just a casual superpower that I'd like to know more about and make some tools for my own use.

My main interest in it is language translation. When I'm trying to find something to read in Chinese, whether for gathering words for zhwotd.com or to read for fun or information, I have a hard time discerning what articles are actually good and which are not, which authors are good, etc. I'm not good enough at the language to tell the difference. Much of the time I spend with new (to me) Chinese text is simply trying to break down the article into the smallest parts that I can understand—often individual words or characters—and clumsily building up from there. If I could have some friends give me examples of good ("good") things that they've read, then I could use those as a body of good examples against which I could compare other articles to read. It's not as good as making the decision myself based on understanding, but who knows when I'll have the skill to do that.

Another idea I've had in the back of my mind is being able to create a service where I could find recipes that match whatever food I have on hand at home. It seems like I should be able to crawl some group of websites with recipes, build a library of recipes, and be able to input a list of ingredients and find the best matches. ("Building", not "sharing", the library of recipes—just use it for the analysis, and pass the user on to the real thing on the real site, not steal the content.)

One final idea, related to work: finding information at work is a huge headache. On one hand, we have an internal library and an internal search engine. The library works best if you can search on title or author or keyword, and I don't know what the search engine is doing, but it's not very useful for me. That's the formal information. The informal information is the most relevant for day-to-day work—emails, meeting notes (people should do this more), files on the server, information in databases, Jira, Confluence, on and on and on. This sort of information finds its way into hidden corners and folders, effectively lost forever, and there simply isn't time to open it all and make sense of it if you do find it. But what if you could scrape that information, categorize it, and make it relevant to use? That would be a superpower—to be able to find anything and everything that a project created, not just the things that are collectively remembered. (I would like to hold up Evernote's context feature as an example, which showed six notes most related to the current open note at the bottom, but they've removed that feature in their newest versions... bring it back, bring it back...)

There's an advanced version of the class coming up on 27 January that I've signed up for: NLP with Deep Learning for Everyone.

Exploration, meandering, boredom

Trailhead: Kathy Hirsh-Pasek. Play breeds better thinkers. Science 371:6525 (2021-01-08).

I've not read the book that the review refers to (Susan Engel, The Intellectual Lives of Children), but the review itself brought some thoughts to mind. Also, I don't have any kids, so I'm not even thinking of ways to optimize or improve their development.

Yet explorations take time—the time to meander and discover, the unscheduled time to be bored. As Engel writes, “when children are allowed to dive into a topic thoroughly, they... connect isolated facts in order to generate new ideas.” They learn grit and they learn to have agency over their own learning. [...] As adults, we often overlook the fact that learning is happening during periods of unstructured play, or we dismiss these intervals as unproductive.

This is also true for adults. But there is a different kind of tension. At home there's the tension of "stop messing around" or "you should know how this works by now". At work there's the tension of "follow the process" or "stop messing around".  That treats problems as already solved, and solved problems as being solved correctly, and problems solved correctly as being solved in the best way. [sweeps arm about the horizon] Look around you and tell me that you believe this is true.

Some of the current mess—pick whichever mess suits you—is the result of poor performance or poor planning, but plenty of problems suffer from not having new ideas. Best practices and lessons learned should be consulted and used, but not exclusively. They have blind spots. Frontiers aren't passed with certificates. Breakthroughs aren't broken by following the process. "Messing around", letting your mind wander, getting bored or stuck and trying to get out of it or not—that's where the magic happens.


The review refers to two books that have been on my to-read list for ages. Maybe it's time:

Underpromise and overdeliver, or not

I'm transferring jobs at the end of the month, from a systems engineering to a project engineering role, so I've been doing another read-through of The First 90 Days (notes) by Michael Watkins, to get ready for the switch.

In Chapter 4, about negotiating what success is supposed to mean with your new boss, there is this nugget of advice: underpromise and overdeliver. I don't know about that. I can think of situations where that's a good approach, but none of them with a boss that I respect.

If I was dealing with a customer, underpromise/overdeliver makes sense. There are real consequences—not just to you, but your project or company or to the customer—to picking an early date, or the expected date without margin, as a target and then missing it. The date you pick for deliveries is part of a real negotiation, contracts and agreements and all. You're not manipulating anyone by picking the expected date, or a date later than that for margin. (Things only break when there is no margin available to fix them.) You're negotiating, and you're getting agreement from the people receiving the thing you ship. And if you can pull off an early date and delight your customer? Congrats.

But internally, instead of externally? Intentionally selling someone on your own team a date that you know is wrong, just so you can score a big win, doesn't feel right. It's better to be honest and explain the margin up front. Maybe this kind of business book is targeted to career climbers who don't care about that. I think that starting a relationship with a foundation of lies—which is what it is when you know better and say something else—isn't the way to go.

A future post, perhaps, because it's something I do occasionally: get better at your predictions by writing them down up front, and then grading them later. Consider improvement instead of manipulation.


A few other, similar voices (you can go read Tom Peters if you want to hear that overpromise/underdeliver is good):

Next stop: Baja California

Previous stop: Cambodia

Now that we're back to work—mentally, if not physically, and not all that mentally yet—our trips-without-going-anywhere are less frequent, perhaps once per month. Our next stop is Baja California. We've been down to San José del Cabo twice before. (And we'd like to actually go back, so wear your mask, etc.)

For Christmas I got Chen a copy of The Baja California Cookbook by David Castro Hussong and Jay Porter. Granted, it seems to be about the northern state of Baja California near to Tijuana, not Cabo and Baja California del Sur where we've been, but it's good enough for now. An idea comes to mind: maybe we can drive the length of the peninsula some day, stitch that north part to the south part with experience. Who knows.

Taking a quick cruise through the book, I've found the thing I'm most interested in: corn. In December we were making some food with thick, soft cornmeal wrappers—sort of like spherical dumplings—but the wrappers were not easy to work with. The corn meal dough never really cohered. They wouldn't really break when we steamed them, but they would crack, or a weak spot would become a hole. I couldn't understand how corn could be made into tortillas or other kinds of bread that I associated with Mexican food. I just hate not being able to figure out something basic like that.

Halfway through the book is a page: "On masa". It describes a process called nixtamalization, which prepares the corn to be ground and, apparently, to be made into a proper dough. For me, that's the missing link. And bonus points for the word deriving from the original Nahuatl (nixtamalli) instead of Spanish.

Another thing that caught my eye was something about "sourcing good maize". I'd never thought of that before. Basically all the corn we eat now is some kind of sweet corn. What kind of corn—maize, sorry, but I don't know what the difference is—are they talking about. What kind of corn would be "local" to whichever place we were trying to model our food? Where does one get different types of corn seeds to plant (in small doses), and would it even work here? Are there types of corn that would have been native to our current area that we might be able to work with instead? I don't have anything against the types of corn we have now, but it's interesting to think about everyday things in a different way—about what the options are, what the options were, how things became the way they did.


A few other captured links:

Make more decisions

Reversible and irreversible decisions—depending on where you work, one or the other doesn't exist. Reversible decisions are forbidden because it assumes the possibility of being wrong, or people assume that nothing is irreversible.

Matt Mullenwegg talked about this in a recent podcast episode of The Knowledge Project (Matt Mullenwegg: Collaboration Is Key; notes):

[73:38, Shane Parrish] What are patterns of people that make really good decisions? What do you see in these people and how do they think about things in a way that is transferable to other people?

[73:48, Matt Mullenwegg] You know, one of the best advice I got really, which was from—early at Automattic I actually hired a CEO, I consider him like a co-founder, Tony Schneider, he's like my business soulmate—and one of the things he taught me early on was: make reversible decisions quickly and irreversible ones deliberately. And I still return to that on a weekly basis. If it's a reversible decision, we'll probably learn a lot more by doing it. I find it so funny, in software especially, let's just build the first version, and build it to throw away maybe. But let's get that prototype out there. We could debate it for weeks or months, or do a million mockups. I have this old essay, "1.0 is the Loneliest Number". The oxygen of usage is required for any idea to survive, and so you want to get to that first version as fast as possible, and that learning is really, really valuable to the speed of iteration. So I like smaller reversible that happen frequently quickly, and without being attached to them a lot.

(And later he references Farnam Street's post about decision journals, which is out of scope here, but worth a read.)

I've found that smart people who are willing to be publicly wrong with decisions are few and far between. It's uncomfortable to be wrong and publicly wrong. And it's uncomfortable to violate consistency, even in the service of making better decisions. But it's the right way to go. Sufficiently complex decisions are often intractable—you're lucky if you can figure out what all of the variables are, let alone their values, let alone how they interact with each other. So you've got to do something to get from zero to a solution.

Experiment... why do people often think that word means "let's just try something and see what happens", or "hold my beer I'm going to try and jump over it"? Thought and preparation goes into experimenting, or it's useless. If you work in physical space, experimenting is often expensive in time and money and the opportunity cost of having your staff and facilities do something else. (Another post for another day.)

In my experience, at work, most information systems and team processes aren't set up well for reversing decisions. Sure, we have The Process that (supposedly) defines how we are allowed to design things, and we have Configuration Management which defines how we can change things. ("Things", in these cases are often requirement specifications, test procedures, software, hardware drawings, etc.) But The Process is often odious, and Configuration Management is the nun at the front of the class in a Catholic school. They're not built to try things quickly, explore the frontiers, and then back up and go in a different direction if needed.

That's only partially true. We could move faster and try things if we wanted to. What limits us is the way that we manage our information. When you really, really get down to it, what is a decision? It's a definition made by people at a certain time. A decision controls something. A decision can be encoded in nouns and verbs, i.e., variables, or classes and methods. If we thought of all the decisions that we captured in prose as being algorithms, or nodes in a larger graph, we could know what affected what, and try something, check the result, then decide to keep it or dump it. It's probably not easy to set up, but the problem seems easy enough to understand.

Even if we didn't make any changes to the way we operate, it seems like we should be able to submit experiment proposals to change control boards the same way we submit problem reports and change proposals—ask for explicit permission to try x on subset y for t time, report back with results, then commit to continuing the experiment or reverting it or accepting it as a change on the whole set of things.

(Apologies for the abstractions. That's what it's like to talk about work outside of work sometimes.)

Instead, we plow ahead with extensive planning and review, then take a systematic approach to planning things. That's good and often goes well enough—better than just winging it—but you're limited to what you know ahead of time, and many of the lessons you learn through applying the plan are chalked up to "lessons learned" for a future program, which may or may not be used ever. That paradigm is best for irreversible decisions.


More links:

The Captain's Newsletter, 2021-W01

The Captain's Newsletter, 2021-W01 - Mulligan

2021 was supposed to be... better? But I guess we had it coming. Betting too much on "there's always next year" is like [shakes Cubs fan magic 8 ball], hmm, don't want to get kicked there. This week I advise you not to commit felonies, not to micromanage (which will be a felony when I become King), not to share misattributed memes, not to ignore your team's emotions, and not to... OK you can commit felonies if they are interesting.

Join us: /captain.

Suck it up and take the L

For several months in the US we've been treated ("treated") to the inevitable conclusion of what happens when you don't teach your children how to lose with dignity. Growing up playing sports, you get to see countless examples of the good and the bad when it comes to winning and losing--in yourself, in your teammates, in your opponents, in the superathletes who compete on TV.

We're often over-sported here in the US, I think, and the concepts of winning and losing in zero sum games bleed too much into the rest of life where outcomes are more complex than a mark in the W or L column. But up to some threshold the lessons learned are good ones. Respect the game. Respect your opponent. Respect the officials. Respect the supporters. Prepare well. Execute well. Win with humility. Lose with dignity.

Everyone who steps into the arena will lose, eventually. Over time, nobody bats 1.000, nobody shoots 100%. How a person handles a loss is a test of, and an insight into, their character.

You know the type: at the end of the game it's always the ref's fault, the other team cheated, the field was bad, the ball was wrong, the weather was unkind, something got injured, etc. Each of those things happens frequently enough, but never always, rarely in combination. And when they do, the probability is unlikely that they occurred in a game in which the players did not commit their own errors themselves. And when they do, it's up to you how you respond to it.

In sports, in life, sometimes you have to suck it up and take the loss. Acknowledge the loss, congratulate the winner, thank the supporters, and prepare for the next match. If you're not tough enough to lose with dignity, you're not tough enough to win.


And away we go: