I’ve been thinking a lot about Solarpunk.

Not in an obsessive puzzle-to-solve way, but rather as a recurring theme that pops up in reference to conversations, news developments, and everyday activities. It’s a sort of background hum that has been growing a bit over the last few years, and noticeably stronger in the last several months and weeks. Like a piece of music that you can’t get out of your head, but that you also feel like whose melody fits into this soundtrack moment perfectly.

What is Solarpunk

Solarpunk, for the uninitiated, is a sort of aesthetic vision of the future. It emphasizes a co-existence of technology with nature that is more sustainable and integrated more holistically. It’s an “aesthetic” because it’s more a vibe than a concrete philosophy or guidebook on how to make sweeping political changes. But it sits at a higher level of abstraction, and helps us to imagine a world of clean energy (i.e., solar), sustainable cities, bending technology to explicitly serve social good as opposed to a that being a hopeful side effect, and working as various communities to partner with our lived world rather than dominating or fighting with it.

There are very good elaborations on SolarPunk here and here. Media that comes to mind would that align with it would be Black Panther, Avatar, anything Miyazaki on the film end, and a nod in Butler’s Parable of the Sower or Ursula Le Guin’s The Dispossessed.

Rejecting Cynicism

One reason I think it’s been helpful as of late is the “punk” nature of it too (related: cyberpunk, steampunk). It’s not a dystopian vision of the future, nor a post-apocalyptic collapse. As punk as punk is, it rejects cynicism and nihilism — it’s a “radical” departure from our current systems that aren’t working for really anyone.

But I also see it in smaller ways — in my day-to-day life, where I’m deciding between buying something new, or mending it myself, using my 3D printer to design and build a replacement, or using on-hand local-first computing and gadgetry to do something small, sustainable, and repairable.

Overall, it’s a “campaign in poetry, govern in prose” kind of aesthetic that I think a lot folks need right now. What kind of vision for the present-made-future do we want to strive towards?

Whether it’s politics, AI, climate change, energy, social media, or dozens of other challenging areas — these are simply too vast, too interconnected, and individually too dispiriting in many ways to tackle with a single philosophy or message.

Forward

I’ll have more to say about this and how it crops up around us (e.g., right to repair movement, local-first computing) — it’s one of the key themes of me restarting the Good Tinker newsletter and has in some ways been an undergirding of my approach to “tech for the social good” before I’d found the term.

It’s 2025, it’s good to be back on here, and I look forward to engaging with all of you.

Hiya friends,

Apologies for the slow updates — it’s been a busy time at the GoodTinker household!

Just wanted to give you all a heads-up that I’m taking a slight pause on the weekly-ness nature of the newsletter.

Nothing at all to worry about, just trying to manage some immovable time demands of primary and side projects.

And with that, I have some big and exciting announcements coming…I just can’t announce them yet!

As always, get in touch on twitter or email. You’re all amazing, and keep tinkering.

-Gabriel

I'm sorry to report that I'm leaning into TikToks (😬).

My most recent foray is on Desire Lines — the shortcuts created through active use rather than suggested design. These are also called desire paths, herd paths, or social trails. Oh, remember that I've been cataloging these over at my EverydayConcepts.io site!

The concept of desire lines is one of those where once you start to see it, you'll notice it everywhere.

I'm trying to be more abstract with my drawing, but it's essentially a picture of a sidewalk with a kink in it, where you have a brown path — a worn area created by people taking a shortcut instead.

Desire lines are not inherently "wrong" or harmful. They're helpful in figuring out patterns of use, preferences, shortcuts, all of it!

This concept's excellent because it's not limited to dirt pathways but is present in many aspects of life, society, and our lived experiences.

Sometimes usability testers will create heat maps these maps to understand the "shortcut" that our eyes (and subsequently our attention) take across a screen.

There's even a fun little Subreddit, DesirePath, with plenty of excellent examples — and lots from surprising contexts!

Desire lines don't always help us establish the best way to go from point A to point B. Sometimes those shortcuts have real costs associated with them, and sometimes those costs can be more than just getting your shoes dirty. Everything from the shortcuts we take in food (delivery over preparation) to habits (the shortest route to working out 3x per week is just not to do it!) What's fastest might not be what's best.

I love the concept of desire lines in daily life because it shows us the world as it is and not how it's ideally designed. It's a reminder that we can rarely design systems entirely from the start and that preferences, efficiencies, and, yes, even laziness, will often guide their use.

Where do you find desire lines in your everyday life?

What Else I'm Reading

• A dissenting view on the origins of the US's Right wing | Aeon Essays — This article is about the lost Cowboy Progressives. As someone who grew up in Kansas and remembers a streak of a democratic populism before it was subsumed by social conservatism and the right.

• Agile and the Long Crisis of Software — One of the better place settings for Agile (software development) out there. The trends highlighted here are pernicious in DC, where folks are still catching up to "making their teams Agile" in the first place.

• The Oral History of 'PCU', the Culture Wars Cult Classic — I think about this film more than I realized.

• TikTok's Algorithm Spews Out Viral Villains - The Atlantic — Yeah, this is going to be a growing trend. It's like that Twitter line, "Each day on Twitter there is one main character. The goal is to never be it."

• Snapchat has a new lens to help you learn the American Sign Language alphabet - The Verge — These are my favorite advances in technology.

Thanks for reading,
Gabriel

Last week I mentioned the world being on fire, and one thing I reflect on to help assuage the burn; how we can repair it. Apparently, the UN agrees with me (about the whole 'on fire' thing, sadly.)

It's helpful to think of what we do in a broader philosophical and moral endeavor to maintain and repair the world around us as we go. A reader (thanks Charlotte!) wrote to remind me of 'tikkun olam' (literally: 'repair of the world'). It's a Hebrew term often interpreted as an aspiration to act constructively.

From Systems to Screws

The lofty aspirations and guiding principles of repair are fantastic and something I carry with me into a lot of my work.

But 'repair' isn't just for the lofty; it's also for the mundane. It's in the policies, practices, and products of our daily lives. And unfortunately, 'repair' isn't just a question of know-how, resourcefulness, and time, and it's bound together with ownership and allowance. In other words...

It's about capitalism, isn't it

Yeah, it's capitalism.

Corporations have an incentive to make things harder or impossible to repair — they'd prefer you buy their newest product (or the same product, multiple times). They do this by using non-repairable components, forcing license agreements, restrictive intellectual property, planned obsolescence, and more.

For example, when you buy a John Deere tractor, you're required to sign an agreement that all the software, data, and communications belong in perpetuity to the company. This, combined with the complexity of John Deere's equipment, has led to pushback from farmers and to the rise of pirated diagnostic and repair tools.

This status quo hurts us in a lot of ways. It prevents obvious repair instances, but it also really hampers in other ways, by limiting sustainable solutions, homemade solutions and "hacks," innovation by inventors and builders who build on initial infrastructure, and more. One of my favorite examples is the Hush-A-Phone Supreme Court case that ruled that AT&T had to allow individuals to use the device on their network. This led to a secondary market for all sorts of attachments and paved the road for an eventual breakup of Bell altogether. Oh, and another excellent example of this is the Internet. Go figure.

Right to Repair

There's a growing movement, Right to Repair, that seeks to provide legal and policy backing for repair and limit restrictive policies (think iFixit as an example organization leading the charge.)

Last year, the White House issued an executive order providing a directive on just this topic, and the FTC further backed it. And it's not just the federal government; there are initiatives in 25 states around Right to Repair. Europe has been leading on Right to Repair laws (the French have even started instituting a repairability index).

This seems like one of those "let's build the world we want to live in" sort of moments. While we might not all be farmers looking to upgrade the sensors on our combines, there might be a lot of downstream consequences to those of us with Raspberry Pis and a robot.

What Else I’m Reading

• The Rockefeller University » The human genome is, at long last, complete — This is one of those “the last 20% took 80% of the time” items, and it’s really exciting to see how this will cascade to better understandings about our genetics.

• No Amazon? No problem: How a remote island community built its own online shopping service - Rest of World — As someone who, living in DC, 100% takes all of this for granted.

• Shopify’s Evolution – Stratechery by Ben Thompson — There is no better person out there thinking about platforms, networks, systems, and economies. His podcasts are a must-listen if you’re into understanding this ecosystem.

The world is on fire in so many ways these days, and it doesn’t always seem to be moving in the right direction.

If you’re like me, you can find yourself experiencing seizing moments of dread, desperation, and exhaustion to think about our direction. I’ve always found it helpful when I have those moments to think of all the people, projects, and intentions that people place in repairing the world around us.

A repaired world isn’t the utopian vision of science fiction that is all clean surfaces, spotless jumpsuits, and seamless technologies. It’s the opposite — it’s lived surfaces, worn environments, and kludgy technologies that have been made to work through sheer will, frustration, resourcefulness, and even love.

Repair in the Most Likely Places

When I was in graduate school at Michigan, I had the good fortune of working with a fantastic advisor Steve Jackson, and an equally fantastic fellow student in Alex Pompe. We won a grant to spend the summer returning to where we had lived as Peace Corps Volunteers (Madagascar and Namibia) to study the impact of technology on various communities. This was in 2010, and the mobile phone revolution was still in full swing in both of these countries, albeit in slightly different ways.

It was open-ended research, in a way — we were looking for what stood out and followed the trail. One of the things both of us found in our interviews was just this theme of making do with the tools you have at hand. This might sound obvious — of course; you’re going to use what’s around you, particularly in the Global South. But it was more than that. It was an overt choice that people were making for simple systems over feature-rich but complex ones. It’s Nokia phones over smartphones, old French Renault and 2CV cars over more efficient modern models — repairability over predicted obsolescence.

Repair Worlds

I wrote a short blog post about this in 2012 — but the academic paper we wrote holds up — Repair worlds: Maintenance, repair, and ICT for development in rural Namibia. The term ‘repair worlds’ is an homage to Howard Becker’s Art Worlds (1982), where Becker describes how art is created by multiple people and not just individuals, and particularly a more sociological approach to ascribing value to art.

The gist of this paper is that systems often prioritize the new, novel, packaged, and ‘upstream’ products. But the lived reality of these prioritizations often ends in rusting tractors and broken mechanisms with no local know-how to fix them, much less abilities and allowances to do so.

When given a choice, people (and not systems) make decisions that reflect a rational actor in a world where things malfunction, break, require upgrades, and are constantly being appropriated and re-appropriated. Considering ‘Repair Worlds’ forces us to step back and think about ‘downstream’ use - sustainability, investment, and user-centered design.

By placing our projects while looking both upstream and downstream, even simple interventions can have a tremendous impact.

A fantastic documentary came out in 2014, Ady Gasy, that focuses on this particular phenomenon of repair and resilience in Madagascar — I can’t recommend it enough.

The maintenance and repair of our tools is something that still cuts across a lot of the work that I do — whether it’s building digital platforms, 3D printing a new gadget, or tinkering away on some old piece of hardware (that’s how the newsletter got its name!).

Next week, I’ll follow up a little with some trends in the repair space, and why it’s so important to pay attention to, and why we ignore the issue of repair at the peril of our species—no big deal.

What Else I’m Reading

• The Tech That Comes Next by Amy Sample Ward & Afua Bruce | Purpose-Built Platforms — Lots of good stuff here that is on-brand for the newsletter right now.

• What Constrains Tech In sub-Saharan Africa — Someone sent me this essay, and I’m diving into it, but some of you might like it.

• Chalamet Coughs, Dune Wins — Data science at its best.

• Elite Ukrainian Drone Pilots Are Reportedly Making All the Difference — Huh.

Thanks for reading!
Gabriel

Hi folks — Playing around with the format of the newsletter a bit — long-form every two weeks, slightly shorter every week, etc. And also playing around with more research-y posts versus ones that have a little more personal connection to them.

I have to say that I’ve really enjoyed launching and writing this, and I love the feedback you’re providing (keep it coming!). With everything happening in the world, it’s helpful to continue to try and put something positive into the world — so thank you!

Topics on the hopper include repairability, tech4good, and systems thinking overall. If there are specific topics or ideas that you want me to cover, please let me know!

It’s the middle of March, which is just enough time for our New Year’s resolutions to have worn off, for 3rd winter to arrive, and for whatever goals we have for ourselves to be stress-tested to their breaking point.

My brain grinds against something that doesn’t quite work with me until I find an alternative and try the next one (or next 20).

Lately in my life, that has been the whole idea of goals, and why I’ve slowly been replacing them with systems.

As you know from my Notion post and my general type-A-ness, I’m kind of a sucker when it comes to organization and planning.

But I’m not disciplined enough to work within frameworks that are no longer helpful for me — it’s a blessing and a curse. I wish I could have started Bullet Journaling lo these many years ago in middle school and just kept it up (alas).

The goal of goals

Goals are objectives — they are the light at the end of the tunnel, the dais of achievement, and the medal around your neck on something that you’d like to have that you currently don’t. But the thing about goals (most of them, anyway) is that they are hard.

Goals are hard to deconstruct, they are hard to motivate towards, they are hard to achieve, and they’re kind of hard to talk about.

That doesn’t stop us from putting them out there, though.

We are very good at holding ourselves to goals all over the place — career, health, relationships, milestones, habits — these things are easy to write down when we take a moment, but much more challenging to follow through on (much less accomplish.)

The same is true of lofty goals and high-level objectives — it’s just not enough to say, “I want to write a book in 2022,” and then the product magically arrives.

Letting go of goals

Over the last several months, I’ve been reflecting on my goals in the context of several other seismic life updates (jobs, careers, relationships, etc.)

And one thing I’ve noticed is that — goals haven’t worked for me the last few years. I think I’ve slowly been forgetting about them, as I (a little bit without thinking about it) just ended up replacing them without systems instead.

It wasn’t a purely immaculate conception on my part — there is this Zen Habits post and how the best goal is no goal. Another place I found for inspiration was James Clears Atomic Habits, where he takes a pretty strong stance towards systems rather than goals.

In the end, having goals hadn’t been helping me achieve those goals in the first place. If anything, they added to my anxiety about not achieving those goals. Who needs that?

Building up systems

Systems are about habits, processes, and feedback. They’re the carve-outs in calendars and scheduling that you have to make for something. Systems are also adaptable — you can change things more quickly in a system (committing to exercise every day, rather than the stricter run 5k every day.

The great thing about systems is that they don’t judge you for accomplishments or even progress necessarily. You can commit to something as part of a system that says, “I am a person that goes to the gym three times per week,” rather than a nebulous goal of “getting stronger.”

For me, this has been a game-changer because it removes my discipline from the equation, as well as any expectation about performance at the moment. Showing up is more important than peak performance, in my systems mindset.

And actually, there’s an exciting caveat about performance. You might be tempted to think that simply guarding the slot on your calendar and performing poorly is not going to get you to your (now non-existent goal). But that’s not what I’ve found — that, when I show up and put my butt in the chair, a different part of my brain and motivation take over, and I do end up working hard and making that progress. It’s just getting into the chair that was a challenge before.

Systems get your butt in the chair, and output comes later.

In my experience, this mindset of systems over goals has helped me launch ProprThings, to start this newsletter, to keep me engaged with friendships, to keep me oriented in these turbulent times.

And look — when you look backward, you find that you are achieving those goals, even if they’re not your focus anymore. The things you produce or achieve are a by-product of your systems, not the culmination of uninterrupted discipline towards an objective. Deliverables are the derivative of good systems, and incremental progress is a feature, not a bug of the system.

What else I’m reading

• Hearts and minds — Very beautiful data visualization of immigration in Europe.

• Maxar - Russian convoy outside Kyiv - 3D clip - Maxar — Another way the activities in 2022 Ukraine are visualized like no other conflict.

• Why BBC Revived Shortwave Radio Dispatches in Ukraine - The New York Times — Sometimes the old technologies are the best technologies.

• Ukraine Vice Minister Says SpaceX Starlink Is “Saving Lives” — I think this is before Elon offered hand-to-hand combat.

Thanks for reading,
Gabriel

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

I've changed industries a couple of times and have had the good fortune to be a part of several teams looking to build their data science and AI capabilities.

I've seen a few challenges in different organizations as they start at varying phases of their data science journey, so this edition might be a little more geared towards the data nerds and product folks on the list than most people. Still, I think it's also generalizable enough for most folks thinking about technology intersections.

Why Data Science

Before getting started down the road of data science, modernizing technology stacks, and integrating the latest cloud architectures with your team's data — it's essential to take that giant step backward and ask — WHY?

In other words — how will data science improve your product, your team, your impact? How will it change your approach, and how do you as a team manage your processes? What are you hoping to get out of it? How are you approaching your investments in terms of time, personnel, resources, and more?

OK, once you've started giving yourself a heart attack with those easy ones — I usually sketch out three broad areas of thinking.

Culture — Align within your organization

You shouldn't be chasing data science because it's new and shiny — even if it is. Too many organizations start from the fantasy of solution orientation and are quickly disappointed when it's challenging to match that enthusiasm from the needs-assessment side. Your teams don't want data science if they are already tapped out on their bandwidth and energy, wouldn't see the benefits to their tasks or project output, and aren't involved in the journey.

You have to line up the context of where your organization is at — the expertise, the experience, the priorities, and the personnel, and have them all facing in more or less the same direction to take on data science.

This can be done through sponsored trainings, fellowships, internal cohorts, even internal hackathons, and half-day workshops are good ways to get the right people to the table and try some of these things on for size. This way, you're not only building skills, but you're also building the networks, and through that, you're building the internal culture that tethers your teams to new ways of thinking and problem-solving around data science.

One way to do this is through data science competitions like those run by Kaggle (and there are more than just Kaggle).

Timelines — Use time scales, don't fight them

One of the biggest challenges is the disconnect between the overwhelming pace of change we see in this space and the longer time horizons of organizations.

Everyone always feels like they are starting from behind.

But you're not!

"Start where you are, use what you have, do what you can." — Arthur Ashe

Not everything has to be a neural network built with a supercomputer.

Going from a paper-based survey collection process to an Excel spreadsheet can be an absolute game-changer. We can build on existing solutions and translate that practice where and when appropriate.

On the flip side, we also don't want to spend all of our time trying to formulate the one-big-platform-to-rule-them-all. When we do this, we start to enter Everything Pig territory, and that's a no-no.

Instead, we want to think about building in small, incremental, but ultimately valuable phases. This drawing from Henrik Kniberg that I came across a few years ago is perfect. I think the reality of the top-down approaches that spend years on a path without building functional iterations along the way are much less cheery than the top row in this drawing — they often get canceled before it even comes to this.

My favorite recent example was an app project that I led where we built a smartphone app to detect mosquito eggs. It started out simply — just in recognizing small black dots from a photo. Eventually, it grew to encompass different types of images, user controls for various conditions, multi-language support, training, and more. But we didn't do it all at once.

Scoping — Technology is hidden, and should be

When I hear a team start by saying, "We really need to data science this..." — I know that we've already started too late.

Technology is often just a means to an end.

When you read the reports of organizations and governments, you find that you don't need to invoke technology to talk at all about impact. What I mean is that when you're reading about healthcare initiatives, access to clean water, improved education, etc., what you see is the focus is on improved access to resources, greater financial freedom, or higher test scores. You don't necessarily hear about health records systems, supply chain databases, or learning management software.

When I hear someone say the scope of work doesn't have anything about technology — my first thought is usually one of relief, as it means the project isn't hobbled by being forced to go down a particular technological path. This way, we are free to build the product or service to most effectively meet the needs of the team.

Thoughts

By starting small, with the right team, and building upon small but essential wins, you can begin to see some very encouraging progress.

And so, even though it won't be easy, I'm optimistic about our opportunity to be that force for good, design and develop cooperative systems, and be part of an organization that helps make a positive impact outside the scope of technology — using data science and beyond!

What Else I’m Reading

• The Great Switch: distributed work first – James Governor's Monkchips — Good lessons about thinking through distributed work.

• The Smart Nonprofit: Staying Human-Centered in An Automated World by | Staying Human-Centered in an Automated World — Lots of similar thinking from this article (and excerpted book).

• Shopify’s Evolution – Stratechery by Ben Thompson — I love Ben Thompson’s thinking on most topics, and really provides the best ways of thinking about this sector.

• Elon Musk Says SpaceX Starlink Satellite Internet Is Active in Ukraine — Comparing to my previous example.

• Bionic eyes: Obsolete tech leaves patients in the dark - BBC News — Well this is nice and dystopian.

• Why Africa will be the world's fastest growing video game market — Quartz Africa — Bet you didn’t necessarily see this one coming.

Thanks for reading,
Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

It’s a sign that a lot is going on in the world when a story about 40 satellites being destroyed by a geomagnetic storm isn’t front-page news for days.

But here we are. Cool 2022.

The satellite story may have hit your radar a little bit — it’s the project of the always-on-your-radar Elon Musk, the man trying to be a multi-planet species in SpaceX.

While SpaceX gets much of the attention right now, I have a (not-so) hot take that I think Starlink will have a more significant disruptive impact here on Earth before we start building colonies on Mars.

The rocket launch industry is a billion-dollar industry, and what Starlink is capable of is a trillion-dollar industry. It will join the ranks of energy, travel, IT, healthcare, government, and defense.

Some context on the company: Starlink is the satellite-based Internet network developed by the private space company SpaceX (both helmed by Elon Musk.) Since 2012, Starlink has been building the infrastructure and technology to launch a global network of satellites that will provide Internet access to ground-based locations from space. They started launching satellites in 2018 and began selling “user terminals” (small, consumer-focused antenna dishes) in 2020 (unboxing and teardown video, if you’re curious.)

Pretty cool, right?

Satellites are the New Black

You know — once you start launching people in space, building electric vehicles, and start boring companies, why not just tack on a world-changing telecommunications platform to your side hustles? But it’s more than just a fun vanity project — there’s a real market here and some exciting angles that might up-end one way that we think about the edges of the Internet.

Satellite connectivity is nothing new. Iridium satellites have been around since the 1990s, and the DirecTV subscription service still has 16 million subscribers.

But satellite-for-Internet has always been a more formidable challenge — equal parts physics and economics.

The Physics

Companies like Viasat have been providing satellite Internet for the last 20 years. But the systems have traditionally used geospatially-locked satellites (very far away, which means increases in latency, or lag) and can get expensive. On top of that, they’ve typically required fixed satellite dish systems to operate. So it isn’t cheap, it’s challenging to set up, and the service isn’t that great. So basically, it’s like health insurance.

But there’s a market for them — rural or off-grid locations, ships, airlines, and even RVs. The other demand is for business and Internet service providers in other countries, where for whatever reason, landline broadband doesn’t exist, is prohibitively expensive, or is unreliable — more on that later.

All said, all Starlink has to do is to provide a service that is simultaneously cheaper, more reliable, and simpler. The bar has been set. Let’s look at the details.

For ‘traditional’ satellite Internet, you might be looking at $30 - $160 per month for speeds that average out to 18 Mbps. For context, US-based broadband averages out to 115 Mbps.

In recent surveys, Starlink clocked in at 97 Mbps.

But download speeds aren’t the only thing (upload speeds matter too, but not quite as much). Latency has been the real killer on satellite connections.

Wait — A quick digression on satellites

This issue of satellite latency surprises most people — as you imagine that satellites and connections operate at something called the “speed of light” (they do). But it turns out that geospatial satellites are far away (36,000 kilometers — or about 3,600 times the height of a plane flying at 35,000 feet), and when you have to bounce signals back and forth to them — it takes precious hundreds of milliseconds.

This is a total aside to say that the network of undersea cables that most of the modern telecommunications platform runs on is fascinating.

This is why the Low Earth Orbit (LEO) satellites are essential to Starlink’s plans. They are much closer to Earth (just 550 km — so that’s only 55 plane-heights) — and so instead of being “stationary” from our perspective on the surface of the Earth, these tiny satellites are zipping around. They require lots of them to make a network work and smart terminals on the ground that can quickly transfer from one to the other as they pass by its view — like locking your eyes onto specific trees when you’re daydreaming from a car (not driving.)

In five years, a Starlink satellite will perform 30,000 orbits. In each of these 90-minute orbits, the satellite will spend most of its time over the uninhabited ocean and perhaps only 100 seconds over a densely populated city.

For the first time, internet availability will depend not on how close a particular country or city comes to a strategic fiber route but on whether it can view the sky. — Casey Handmer

That’s why Starlink is planning for a lot of them. As of this writing, there are 4,408 Starlink satellites in orbit — and Starlink is preparing for an additional tens of thousands of satellites.

What’s even more incredible is how the satellite network not only communicates with the ground but with other satellites.

Back to latency: traditional satellites offer a high latency, or lag, of 500–800ms. It seems small, but if you’ve ever facetimed with someone over a lag, you’ll know the difference.

Modern broadband averages 14ms of latency, whereas Starlink clocks in at 45ms of latency. That’s within spitting distance of fixed-line broadband.

The Economics

Starlink owns the vertical. It’s a rocket ship going upwards, so it really does look like a vertically-integrated market, as Starlink cornered the market on cheap space launches.

But it’s still relatively expensive to put satellites into space, operate a global platform, and provide valuable, helpful Internet service.

I’d recommend Casey Handmer’s blog post on the economics of launch costs, the longevity of satellites, reusable rockets, and marginal costs that scale. This post got me thinking about Starlink in this way in the first place.

But the numbers are enormous — and could be positively astronomical ::smirk::. Currently, about 90,000 people are testing the service (Starlink claims there are 500,000 pre-orders), each paying $99 a month (plus a $499 fee for the satellite dish). The market cap of potential customers in this space numbers in the many millions, either as direct customers or paying into an ISP using Starlink as the back-end.

Our Dotted Future

It’s not all sunshine and rainbows. There are significant challenges and resistance that Starlink faces in other areas.

As satellites dot the sky, the sky can become slightly...speckled.

The sky is a big place, and the naked eye isn’t going to be impacted — but there’s a growing response of concern from the astronomy community.

The ‘megaconstellations’ of these satellites are causing problems for astronomers. And some are fairly...vocal. And the satellites can risk running into each other.

Also, they might kill astronauts.

But also, the on-the-ground experience isn’t perfect. They can heat up, and my favorite — they attract cold cats.

Competition

Interestingly, Starlink’s star seems to be rising as competitor efforts have sunset. Alphabet (Google) shut down its Internet-by-ballon project in 2021, and Meta (Facebook) shut down their Internet-via-drone project in 2018.

OneWeb, a London-based satellite company, has had an exciting couple of years — entering and exiting bankruptcy as it pushes to launch its satellites for global Internet connectivity.

Amazon is going after SpaceX (not just Bezos v. Musk — well, it is, but not only that) as it is testing their Project Kuiper, which is working with startup ABL Space Systems to launch 3,236 satellites “that will provide fast, affordable broadband to unserved and underserved communities around the world.”

Facebook has even come back into the Internet connectivity game, with new investments in undersea cables (which Google is doing too) and progress on its wireless Terragraph service.

Why We Need More Internet

When you zoom out from the top-level stories about satellite launches, download speeds, latency accommodations, and providing Internet access that’s comparable to broadband for rural populations in the US — you start to see a whole new type of market that emerges.

Even if satellite connectivity isn’t the best or the cheapest connection to the Internet for many — it can be a valuable backup, a competitive pressure on one-option environments (including my apartment in Washington, DC, it would seem), and a lifeline to critical services in emergencies and disasters.

But it’s usually not hurricanes alone that are knocking out access. In 2020 alone, 29 countries restricted access to the web at least 155 times, according to a report from Access Now.

There are still many people who can’t access the Internet — it’s unavailable, unreliable, too costly, too inaccessible, not allowed, not encouraged, or some combination of these. Making the Internet more accessible and available to more people has been a mantra of global development policymakers, economists, telecoms and tech companies, non-profit and foundation groups. It might be one of the few things that all of these groups have resoundingly agreed.

If you want to be genuinely impressed by the importance of the Internet in peoples’ lives, then look into the lengths that people will go to when it’s restricted. Look no further than Toosheh in Iran, the KNPB in Indonesia, or Cuba’s Sneakernet.

This could be great news to provide a powerful voice to so many communities and movements worldwide. And though it’s early days, what’s most interesting about Starlink so far is that it seems to be maybe inching towards progress.

What else I’m reading

• Form fit: Device wraps around hot surfaces, turns wasted heat to electricity | Penn State University — If only this existed for the computer I built in college, it would have powered the entire campus.

• The Rabbit Hole Beneath the Crypto Couple Is Endless — I will never not read these stories.

• How Texas is becoming a bitcoin mining hub | TechCrunch — Speaking of crypto.

• If You’re So Smart, Why Aren’t You Happy? I will also never not read these stories.

• An 8-year-old slid his handwritten book onto a library shelf. It now has a years-long waitlist. - The Washington Post — This is a lovely, lovely story. Full stop.

Thanks for reading, Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

Hi friends!

I know, a delay! Don't worry, getting my sea legs on the new gig. More to come on that at some point! For those wondering, I'm really liking the team at CARE and there is a LOT of good work going on and to be on all things data and technology!

But also, thinking I might move my publish date to Tuesdays so that I don't ultimately succumb to the Sunday Scaries.

On to the good stuff...

When looking at AI news, I've started finding it useful to distinguish between jobs and tasks.

Wait — don't leave!

I basically assume that if you write "AI" in any piece of content on the Internet today, you're either going to have everyone flock to it or everyone's eyes glaze over.

Or ideally — both?

There's been a lot of e-ink spilled about the trials and tribulations of this era of birthing our AI. Are we on the right track for Artificial General Intelligence (Skynet)? Are we in another "AI Winter"? Is GPT-3 even good, or just mostly pseudo-linguistic garbage? So many questions!

Even the term 'AI' being bandied about so carelessly is a little obnoxious. Are we really ushering in the next era of intelligent evolution with recommender engines based on Enron emails and pictures identified as cats? It does seem that from a hype perspective, we've definitely crested onto 'AI' really just insinuating everything that...we just don't have a great way for doing it yet. Magic! Pixie Dust! AI! And we do kind of know who to blame — over-zealous slide decks from tech bros:

Difference between machine learning and AI: If it is written in Python, it's probably machine learning. If it is written in PowerPoint, it's probably AI.

AI is a buzzword, but it's still real.

But let's not throw the byte out with the bit-water here, either.

There's enough real firepower behind advanced modeling, recommender systems, classification, categorization, and more that the front edge of unsupervised learning, reinforced learning, and real-world applications do start to feel a little like magic. Here are a few:

• Koda's Robot Dog Uses Artificial Intelligence To Sense Human Emotion - UNILAD

• AI hearing aids: How artificial intelligence can help hearing loss

• Cancer can be precisely diagnosed using a urine test with artificial intelligence

Egads! And actually, these are all from JANUARY 2021! (Note: one place to track what AI can do, DeepIndex. Great for building those pitch decks for the board members.)

It's all over the map, though!

Yeah, that's the challenging bit about tracking what's going on in the AI world — it's everywhere right now. And it's only going to get worse (better? worse? better/worse! yeah — better/worse.)

To steal and wildly misuse an old adage, when it comes to AI — never was so much developed by so many to...so many. There are just so many folks carving out areas where algorithms can play a role in transforming their business.

One way of carving it up — jobs vs. tasks

This is not going to be that comprehensive AI post.

But the intent of this newsletter is to tease out what's happening across the digital / tech landscape — what lenses make sense to peer at this area, whether it's about social impact, or sustainability, or even just rote aesthetics. We aren't above stabbing in the dark a little, to try and find some ways of understanding the parts of the elephant that we are currently closest to.

That's all to say; I'm seeing one way of looking at AI is through the lens of what is going to affect jobs, versus what is going to affect job tasks.

Jobs that people have, and tasks that people perform — these are not the same beast.

McKinsey did a study in 2019 comparing human skills to computational skills, making the point that demand for technological, social and emotional, and higher cognitive skills will grow, while needs for many manual labor skills and even simple cognitive ones will decline.

There's a potential future here where we have an opportunity to design and develop systems that draw on the best of the abilities of a human workforce, partnered and supplemented with AI assistance. Cooperative systems will be more efficient, more effective, more transparent, less biased, and more resilient.

And really, this isn't a controversial or groundbreaking statement. We've known for nearly 40 years that teams made up of humans and machines form stronger alliances. It's almost cliché at this point to say that any...good enterprise is coupled with good data. 😎

The Great Resignation meets Bullshit Jobs

I also picked up the book Bullshit Jobs last year — right as we were heading into the era of the Great Resignation (which, maybe this doesn't actually exist?). This is a fantastic read from a thinker who we sadly lost just as he was hitting his stride. Maybe I'm biased because of my Washington D.C. residence and history of working in/around magnets for bullshit jobs (but seriously it's a good book). But a lot of areas that fall under Graeber's rubrik for a bullshit job (box tickers, taskmasters, duct tapers) are ripe for automation and AI-sponsored pattern recognizers. The days are only numbered for many of these roles.

The timing and possibilities around automation are interesting as we are having a conversation (read: negotiating for better offers) about the world of work, what we find most important after 2+ years living through a pandemic, and how we relate to this little organic sphere hurtling through space getting hotter and hotter.

Reasons for optimism

Jobs are changing. We are changing. COVID made us change even faster. It's not all bad. We are seeing is the algorithmification of job tasks, which can be good! It's good until it becomes the distilled recipe for a job, which is bad.

And yet — we have reasons to be optimistic about this future, if we bend it correctly to what we want.

Computers are really good at some tasks. And humans are really good at some tasks. These tasks, are not necessarily overlapping, and in fact, they often complement one another.

In 1930, John Maynard Keynes predicted that, by century's end, technology would have advanced sufficiently we would have achieved a 15-hour workweek.

It seems long overdue — but better late than never.

And you know, when my little AI friend can take over writing this fledging newsletter (tell your friends!), I won't even let you know. You might see a hint of it somewhere. Dedicated readers will notice a subtle change in style, but like Michael Caine's Alfred at the end of the Dark Knight trilogy, you'll see me in Italy, and hopefully give him a little head nod of recognition — we finally did it.

What else I'm reading

• The Great Siberian Thaw | The New Yorker — Sigh. We're all screwed.

• We Need to Let Go of the Bell Curve — Comparing "normal" distributions to Pareto distributions. I'm still wrapping my head around this one.

• Scott Galloway on the False Promise of Web3 | Marker — Really smart overview of all the hype surrounding web3.

• These Turtles Fly South for Winter | Hakai Magazine — Cover photo alone did it for me.

Thanks for reading, Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

Hi friends,

I hope your new year has been treating you all well! I’m writing from Washington, DC, where I’m crossing my fingers this week that the city’s COVID-19 new cases are plateauing — and to a much lesser extent than the weather will stabilize a little too.

This past week, I started a new job as the technology director at CARE. It’s an incredible opportunity and a fantastic global team working on some of the most pressing humanitarian and development challenges around the world.

Don’t worry, I’m continuing this newsletter, though I might push it to every 2-weeks. Stay tuned!

So let’s get to it —

New Year, New Productivity Approach

I was fortunate in having a little downtime to review and reflect on my own goals, systems, and personal growth.

Having solved it all, I now have an air-tight, fully enlightened, and 100% efficient approach to productivity tools, and I’d like to share them with you. 🙃

LOL.

But over the years, I have tried so many different approaches, software tools, systems, etc. Some of these have worked well and continue to be in my toolbox, others failed miserably and have been abandoned, and many others have been somewhere between valuable and insufficient. But even the ones that fail help lead me closer to a better understanding of what works for me.

That said, it has been helpful to review my systems and share them with you all in case they’re helpful and enlist your insights and feedback on what you’ve found has worked for you.

I should also note that these are primarily for my own systems — not necessarily those I use for interacting with teams and clients — which would be another post altogether! 😊

Now, on to my current setup...

Project Management / Notes / Knowledge Base

I’ve been a Notion evangelist for a couple of years now. It’s hard to describe the platform simply because it does so much, but essentially it provides note-taking, project management, and knowledge management functionality. Notion has a nice intro to their platform, and this one from a power user is an excellent intro.

I use Notion to track my consulting work, writing projects, goal planning, and 100 other things. For anything that used to be a quick note or one-off spreadsheet, I now use a Notion page or table (database.) So everything from checklists for travel to books I want to read to my own journaling practice. I use both the desktop and iOS apps (and you can do this entirely from the browser).

If you’re new to personal information management, this might be overwhelming. I get it. I went through a long journey that started with text files, to Notational Velocity, to Evernote, to Microsoft OneNote (which I still use for professional work).

I’m considering doing a deeper dive on this, as I’m seeing the popularity of folks like Thomas Frank and Marie Poulin — so let me know if you’d like to see a deeper dive and glance at my own templates.

Oh — and I’ll put a plugin for watching platforms like Roam and Obsidian. Interesting, but they don’t fit with my mental model (folks cite the value of Roam as not needing a mental model, and you can start writing, but the value of these platforms for me is that they do have friction that forces me to organize my thoughts).

Todo

I use Todoist to track tasks — and I am quite happy with it. I actually did try to do my tasks and todos in Notion as well — in all sorts of configurations, but at the end of the day, it just lacked a few key features (recurring tasks, smart dates).

Todoist helps me track daily and weekly tasks, priorities, groceries, things I’m waiting on from others, etc. There’s a little bit of overlap with what I’m doing in Notion when it comes to specific projects, but I try to split it logically — Notion manages my projects, whereas Todoist reminds me of project todos.

The other nice thing about having a dedicated task application is that it has mature integrations with related tools like Gmail, Alexa, Siri, etc.

Others

Email. I don’t have a ton of super unique insights in these areas. I’m pretty boring, and I use Gmail primarily for email. I have been a big proponent of Inbox Zero for probably around 20 years (!) for myself in both personal and work. I recognize this isn’t for everyone and depends a lot on things outside one’s control — so I’m not a zealot on it, but I do think it solves a ton of downstream challenges for folks.

Calendar. I use Google Calendar to track events and scheduling. Honorable mention to Calendly to set up meetings and discussions without dozens of emails confirming calendars and links.

RSS Feeds. I’m a massive proponent of RSS feed readers — I track over 200 feeds with Feedly, and it is my secret weapon in consuming information quickly and reducing overall screentime.

Reading. I use Instapaper to bookmark things I’d like to read later (and also remove ads and site-specific formatting). It’s great.

Mind Maps and Flowcharts. Oh! I almost forgot, I use Whimsical for a lot of mind-mapping-type activities, ideas, and workshops — particularly in the context of digital meetings. It’s a lot more user-friendly than Mural.co or Miro.

A Note on the Productivity Rat Race

It’s important to recognize when you’re one of those folks that will always be optimistic about the next system that will revolutionize your system, solve your problems, and bring prosperous harmony to your life. These folks are content to spend 12 hours integrating a new method for something that would otherwise take 1 hour.

Hi, I am one of those folks.

The bad news: there is no such platform on the horizon that will act like the one-ring to rule them all.

The good news: you shouldn’t discard your interest in new systems as frivolous procrastination, either. The best approach is to thread the needle between the extremes of only continually adopting new systems and never adopting new systems. At the same time, it can be constructive to force yourself to move to new platforms. It provides an opportunity to review, critique, evolve, and better understand your processes and priorities.

In other words, don’t beat yourself up.

Abraham Lincoln said, ****“If I only had an hour to chop down a tree, I would spend the first 45 minutes sharpening my ax.” (he probably didn’t say this)

Just remember that at the end of the day, you still need to cut down the tree.

What Else I’m Reading

• Forced by shortages to sell chipless ink cartridges, Canon tells customers how to bypass DRM warnings | Boing Boing — Amazing.

• Drone carrying a defibrillator saves its first heart attack patient in Sweden - The Verge — This is really cool. In this example (Sweden), they were able to deliver the defribillator in three minutes.

• Wearing face masks erases "beauty bias," study finds | Salon.com — I knew it.

• Bugs are evolving to eat plastic | Canada's National Observer: News & Analysis — This is simultaneously tragic and optimistic.

• These Lemurs Have Got Rhythm. Scientists Have Got Questions | WIRED — Indris are quite a special type of lemur, and their songs can be pretty incredible.

Thanks for reading, Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

What I Read This Year

I not-so-secretly really like end-of-year reviews. They are easy to digest, don't ask much of me, and allow me to add some items to my list that I might have missed through the year. I'll do the same thing here!

Rather than focus on all areas of movies, television, books, articles, etc., it made more sense for me to provide a few bite-sized pieces — perfect for holiday break consumption.

Also, when I looked back on my movies and television, it wasn't anything terribly insightful (I liked Succession, Dune, Formula 1: Drive to Survive, Squid Game, White Lotus, and The Great Pottery Throw Down, if you're curious).

Note: I, like you, am a subscriber to many but not all publications below. I find archive.md a helpful resource to get around the odd paywall or two.

• Autocracy Is Winning - The Atlantic — Start off with something that will have you pulling your hair out. But Anne Applebaum is such a fantastic writer — she pulls the threads together in a coherent way that makes sense of the reality in which we find ourselves and points to some ways to disrupt the system.

• The Deep and Twisted Roots of the American Yam - The Ringer — Easy and historical — why is what you call a yam different than what other parts of the world call a yam — read to find out! (it's not an easy read in that it's got a lot of uncomfortable history, but hey).

• Creating a Better Leaf | The New Yorker — Elizabeth Kolbert is terrific and brings to life the science and hope (and realities) behind photosynthesis, solar power, and energy futures.

• What It's Like Inside the Cargill Meatpacking Plant in Dodge City - The Atlantic — I've read a lot about meatpacking industries over the years, having grown up in Kansas (and one of my anthropology professors focused exclusively on them). This piece takes you inside, and you get a sense of the people, incentives, mechanization, challenges, and reality.

• You Are Not Late. Can you imagine how awesome it would… | by Kevin Kelly | The Message | Medium — A short piece from Kevin Kelly, and just one of my favorite polymath nerds out there. Plus, Kelly wrote 10,000 True Fans, which is a little the inspiration for this newsletter.

• How Shein beat Amazon at its own game — and reinvented fast fashion - Rest of World — I recently included this one, but it's a great insight into both fast fashion and Amazon competitions.

• What David Graeber, 'Dawn of Everything' Author, Left Behind — I was just starting to get into David Graeber, having finished Debt: The First 5,000 Years and Bullshit Jobs. This is a great piece, and we lost him way too soon.

• Lab-grown meat is supposed to be inevitable. The science tells a different story — "it's a fractal no. You see the big no, but every big no is made up of a hundred little nos." — long-piece that I found particularly informative on lab-based meats.

• TikTok and the Sorting Hat — Remains of the Day — Great background on the company and algorithm of TikTok. It pairs nicely with what came later in the year from the New York Times, How TikTok Reads Your Mind.

• A Project of One's Own — As a self-inflicted collector of side-projects, this really resonated with me — from Paul Graham.

• One Man's Amazing Journey to the Center of the Bowling Ball | WIRED — I'm guessing that you, like me, had no idea what was happening in the middle of that bowling ball.

• Losing the War - by Lee Sandlin — This is an older piece, but I only discovered it this year and was blown away by all aspects of it — the narrative, the writing, and the rhymes with our current era and what we will remember and not from these most "unprecedented times."

• How a polymath transformed our understanding of information | Aeon Essays — I began learning about Claude Shannon in graduate school (for Information, no less). It's perplexing that his name isn't at the household level, given his contribution to...all of society.

• The Collapse of Puerto Rico's Iconic Telescope | The New Yorker — Yeah, ok, it's a little depressing. Particularly when I think about it in the context of one of my favorite movies, Contact.

• The Erosion of Deep Literacy | National Affairs — I mean, I only skimmed this, but I felt like I should put it here.

• 52 things I learned in 2021 by Tom Whitwell from Fluxx | Fluxx Studio Notes — There are some great little nuggets in there.

What Else I’m Reading

• Wearing face masks erases "beauty bias," study finds | Salon.com — I knew it.

• Bugs are evolving to eat plastic | Canada's National Observer: News & Analysis — Encouraging?

• These Lemurs Have Got Rhythm. Scientists Have Got Questions | WIRED — I also knew it.

Thanks for reading,
Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

Why aren't we better at modeling Earth?

This has been on my mind recently — and not just because of COVID, although that's certainly a big piece of it. But with things like climate change and politics flooding us with predictions and probabilities and forecasting — you'd think we would be a lot better at it by now.

Shouldn't it be the case that as we see improvements in technologies, sensors, and computing power — we would be seeing significant advances in modeling itself?

A couple of recent stories sparked this for me.

Simulating Model UN

First, the UN is backing a new simulation tool, the Policy Priority Inference, that uses a combination of agent-based modeling to compare outcomes across spending priorities. In theory, this will make it easier for governments to prioritize various scenarios. (If you're a super nerd on this, there's an excellent white paper and link to their GitHub repo). It looks like this particular approach is to essentially plug-in as much government data as possible, including traditional measures of development indicators, but also things like policy goals, trends, rule of law, etc. In this way, the model hopes to simulate a more realistic situation where official government data would not always be trustworthy. The model can then track progress in a more objective and identifiable way.

Predicting with Satellites

Second, a fascinating tool from a team at Stanford looking just at satellite data to estimate patterns of growth, poverty, and development over time. The model they developed was trained by looking at satellite imagery for 200,000 villages, compared with collected data about those communities for at least ten years. The imagery would show things like buildings, roads, agriculture, etc. The result is a type of pattern recognition that could at least get you a ballpark estimate for an area for which you have no data (or no recent data, as communities grow and shrink). We can do similar analyses for ocean pollution as well.

Learning from Video Games

And third, I've started exploring a game, Civilization 6, which has built-in modeling for climate change that you as a player have to consider as you enter the modern age.

Yes, reading about agent-based modeling scenario planning tools and playing video games are essentially the same.

Actually, this is a little bit true. Suppose you reach back to the origins of Sim City, the video game that defined the genre of simulations. In that case, you'll find the creator in 1984, Will Wright, actually borrowing heavily from a 1969 book entitled Urban Dynamics by Jay Wright Forrester. Forrester had created a sort of blueprint for modeling equations for the growth and decline of cities — which were controversial even at the time for leaning a little too heavily on hands-off approaches to business and innovation.

Modeling for Granted

None of these areas have it all mapped out — from government policy data and trends to satellite sensor data to sophisticated game mechanics and modeling. And that was very clear as we struggled to understand the evolution and expanse of COVID-19 over the last two years.

It's just — tough! And it's no surprise that not a single model or forecasting approach has become a household tool (though full disclaimer that there are many models out there that are being used by health authorities even if they aren't household names!)

There's so much data we would need to have, and even the data we do have is typically not of a quality necessary to provide a meaningful seed for modeling.

Interestingly, one area that has seen steady improvements has been weather forecasting. The weather includes an enormous amount of data. There are sensors worldwide collecting raw data, and there are time-series data that have been continually collected, sometimes stretching back over more than a hundred years. And there are many organizations, agencies, and people with vested interests in working models, forecasts, and accurate predictions.

It's a remarkable system.

GPT-3 as a Model

When I think of the volume of data that we'd need to see meaningful improvements in more meaningful Earth simulations, I think of what the team behind GPT-3 used to get their language model to its current state. GPT-3 is a natural language processing model built using 175 billion language parameters (and around $12M for a single training run that is great, but not perfect, at generating believable human speech.

What GPT-3 has done has got to be probably the minimum level necessary for believable Earth simulations involving so many entangled, overlapping, co-dependent variables of human and environmental interactions.

Just Getting Warmed Up

All of this is on my mind a bit anyhow, as I've been tinkering with an impressive COVID modeler that uses network analysis to simulate how policy planners can think about planning at tiny scales of human interactions. In this case, looking at the classroom level (think how elementary school students stay in one class all day with the same peers versus high school students who mix in different classrooms throughout the day). And even then, it's at a small scale, but the math gets very complicated very fast!

I recently learned of a new effort from EU scientists to create a digital "Earth 2" to do what we've been talking about here.

Let's hope they learn the fitting lessons from Sim City in the first place.

What I've Been Reading

• How Shein beat Amazon at its own game — and reinvented fast fashion - Rest of World — As someone who knows nothing about fast fashion (or fashion), I thought this article does an excellent job of framing Amazon, manufacturing, supply chains, etc. in an accessible way.

• Autocracy Is Winning - The Atlantic — Sigh. Yeah, I mean, yeah.

• How the FBI Discovered a Real-Life Indiana Jones in, of All Places, Rural Indiana | Vanity Fair — Wow. This story is pretty incredible — and that one that I just have to assume could not possibly happen were things 40 years later, much less today?

• On "Succession," Jeremy Strong Doesn't Get the Joke | The New Yorker — I mean, c'mon. This is still incredible.

Thanks for reading,
Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you've enjoyed this edition, please consider forwarding it to a friend. If you're reading it for the first time, consider subscribing (it's free!).

One of the benefits of having a broadly-focused newsletter is that it allows me the occasional unabashed logrolling of my other projects. Thankfully this week the overlap is warranted, as it covers many areas related to design, technology, and tinkering (for good!)

Let me back up and provide a little context for those who haven’t had the pleasure of hearing from me personally grouse in the last few weeks about magnets, supply chains, and filament colors.

A “Propr” Beginning

In 2017, I initially launched a Kickstarter project to develop one fun little item, the ProprHandle. This device was an accessory for tablets, e-readers, and phones that made them easier to hold and prop up, particularly for long stretches of reading (and so they wouldn’t hit you in the face when you held them in bed, which was the real reason).

It was a fun project, done on the side while I was still working in the innovation office for the Peace Corps in DC. It made sense to continue to offer the accessory beyond the Kickstarter while at the same time fulfilling a few random requests from friends and increasingly strangers to design and develop custom parts all in the same “genre” of the ProprHandle, i.e., well-designed, thoughtful, useful items.

ProprThings was born.

You can read more about the history here.

New and Improved

The pandemic allowed me the time and opportunity to flesh out some design ideas and projects, and I was able to get four more products to the finish line for consumer sales.

If you’re curious, the products consist of: a magnetic soap holder, a pocket stand to prop up your phone, a minimalist keyring device, and a set of table wedges designed to look like old school matchbooks.

If you’re at all interested in keeping up with our releases, I highly encourage you to check out ProprThings, even sign-up to receive updates, and follow along on Instagram.

I’m currently developing a follow-up to the ProprHandle that is retractable and uses magnets rather than suction to attach to the device. Plus, it’s just a lot cooler.

The Bigger Picture of 3D Printing

Out of all the emerging tech to be skeptical and cynical about (and there’s no shortage of them, with blockchain, crypto, NFTs, 5G, AI, surveillance, etc.), 3D printing has been quietly chugging along with punctuated updates about new technologies, materials, businesses, and applications:

• A startup, Carbon, uses “continuous liquid interface production” to develop stunning materials for medical technologies.

• Another example is the use of 3D-printing technologies to build out home sections entirely.

• A team used x-ray imaging and 3d printing to identify an earlier version of a Picasso painting, hidden underneath a revised version.

For me, what makes the technology landscape so interesting is that it’s just become much more massive and mainstream at the same time. Libraries and high schools have 3D printers all over the place, and you don’t need to look very hard on Etsy or Thingiverse to see a healthy ecosystem of 3D printing, design, and hobbyists. There are popular YouTubers and TikTokers getting millions of views for fairly in-the-weeds topics around aspects of heated print beds and techniques for recycling filament.

It’s cool, seriously.

What Else I’m Reading

• UN Calls Elon Musk’s Bluff, Providing Detailed Plan to Prevent World Hunger — This exchange is both playful and terrifying. It demonstrates the emerging gulf in how people frame the solutions to the world’s most pressing challenges.

• Fifty percent of Facebook Messenger’s total voice traffic comes from Cambodia. Here’s why - Rest of World — Another needed example of how certain technologies have become adopted and adapted in different ways worldwide, which have been implications (both good and bad) down the road.

• Smithsonian Bug Expert By Day; Eccentric Tunnel Digger By Night — Architect of the Capital — You wouldn’t be able to get away with this kind of thing today, and we are worse off for it.

• Person Furious That Someone Right Click Saved Their Precious NFT — 👩‍🍳 :: chef’s kiss ::

Thanks for reading,

Gabriel

—

GoodTinker is a weekly email from Gabriel Krieshok about technology, design, and social impact. If you’ve enjoyed this edition, please consider forwarding it to a friend. If you’re reading it for the first time, consider subscribing (it’s free!).

Get Back

Over the weekend, I binged all 8 hours of Get Back, the Peter Jackson Documentary on the Beatles. I really enjoyed it. It was hypnotic to watch the sessions of rehearsal and dialogues from a by-gone era. In particular, it gave someone like me (Elder Millennial), for whom the Beatles were always a little more mythical than tangible, a real sense of the personalities, dynamics, and talents.

One thing that struck me (other than the fact that I think McCartney and I have the same hair and beard shape) was the quality of the video, the pictures, and the audio. It wasn’t like watching a documentary from the early 70s — it seemed in many ways like a modern production and made the watching of it all the more accessible.

Restoration Helps Storytelling

I shouldn’t have been surprised — Jackson has become the go-to person these days for film restoration techniques ever since They Shall Not Grow Old, the 2018 World War I documentary that used 100-year old film. To use that film, they had to use every modern digital trick in the book. Techniques included rotoscoping, adding missing frames, updating the timing, filtering out grains, scratches, and colorization.

Jackson used many of the same techniques here, plus a couple of new ones, including using machine learning on the audio tracks to isolate and amplify vocals, guitars, etc.

Of course, no “upgrade” of this sort is going to be perfect, as some point out, and there are times when you know you’re seeing something that has been smoothed or softened or even slightly altered.

It’s a tradeoff we make to access the signal from the noise. As an audience member, it certainly has the intended effect.

Beyond Restoration

The documentary got me thinking about that slippery slope of restoration in general and black-box technologies like machine learning and AI in particular. As these tools are used more and more (and get better and better), the lines are blurring between historical representation, interpolation, and interpretation.

One of my favorite examples of AI-in-film-restoration comes from the YouTube channel of Denis Shiryaev, a product director of Neural.love, where they restore (very) old films, such as New York in 1911 or Apollo 16 on the moon in 1972.

What’s interesting as well is not only the technological advances themselves, but the perception of technology that may or (may not) be behind the scenes.

In fact, in Shiryaev’s compilation video, he is very explicit that these videos are not historically accurate, and are only meant to serve as interpretations.

We are moving beyond restorations, as we aren’t just cleaning up dust specs here or fixing a broken splice there. The techniques fill in missing data from extrapolated datasets of millions of faces, millions of hours of related film and coloration data.

Deepfakes, Obviously

You can’t talk about these blurring lines without talking about deepfake, the technology behind digitally replacing faces with the likeness of someone else. If you haven’t been paying attention, the technology has become very good (Tom Cruise, Barack Obama, The Shining with Jim Carrey).

Earlier this year, the documentary Roadrunner, about the late Anthony Bourdain, sparked some controversy by using a “deepfake voice” of Bourdain to read his private journals.

What’s interesting about the rise of these examples is that for now, they still generate headlines and are stories in and of themselves. But a lot of people are (rightfully so) worried about the implications of a deepfake world, where we can’t readily identify authenticity, generated or altered content, or underlying intent. While it might be a challenge to create a deepfake of Barack Obama and pass it off as legitimate, that won’t necessarily be true for your average person and the cascading implications.

Taken to its logical conclusion, it seems like all media will correspondingly become a digital wasteland of trust, where, like with the rest of the Internet, we’ll be able likewise to believe and disbelieve anything that we see.

And my hopes aren’t too high on blockchain figuring this out.

Perceptions of Technology

In a completely unrelated venue in recent weeks, we saw the impact of perceptions around video AI technology in the trial of Kyle Rittenhouse, when the lawyers for the defense argued that it was using pinch-to-zoom on a video displayed on an iPad manipulated the footage. The full quote is telling:

“iPads, which are made by Apple, have artificial intelligence in them that allow things to be viewed through three-dimensions and logarithms[...] It uses artificial intelligence, or their logarithms, to create what they believe is happening. So this isn’t actually enhanced video, this is Apple’s iPad programming creating what it thinks is there, not what necessarily is there”

Yes, it’s particularly inane, and it’s unclear if this was a legitimate concern. But it’s not as if this belief that underlying algorithms are manipulating images is somehow unbelievable.

This concern (given weight by the judge, by the way) is a bit of a waterline for seeing how far we’ve come when it comes to not knowing and not trusting the underlying technologies (which we shouldn’t by default).

I don’t have a pithy conclusion to this — it’s both a fascinating technological landscape (check out Two Minute Papers Youtube Channel for incredible examples), as well as an inevitable minefield of ethically dubious opportunities.

All of this started with me wanting to say that I enjoyed the Beatles documentary. And that’s true — it was excellent.

But it also makes me feel like if we zoom in on what’s left after we open Pandora’s Box, that by using AI image enhancement, we’ll see that what we thought all along was going to be “hope” that was left, was in fact just “nope.”

I have a fun side project where I draw simple sketches around concepts from various fields that can be applied to everyday life. It's called, unsurprisingly, Everyday Concepts. I have a database of literally 1000's of concepts I've collected over the years from software development, economics, data science, design, etc.

The term that's been on my mind this week is "Bikeshedding," which is honestly one of my favorites because it's one of those that when you learn about what it is, you start identifying it in every interaction and discussion for the next three months. It's one of those once-it's-named-it's-recognizable sort of things (and also Baader-Meinhoff?)

Bikeshedding (or Parkinson’s Law of Triviality) is the tendency to give disproportionate weight to trivial issues of a larger or more complex project. In other words, it's prioritizing something easy to grasp or is debatable.

The term comes from a fictional 1957 illustrative anecdote by C. Northcote Parkinson about a committee discussing a nuclear power plant plan. In this hypothetical meeting, the committee spends most of their time arguing over the color to paint the bike shed in the back, because that was the part of the plan that everybody could understand.

If you're like me, you're probably thinking back to a dozen recent discussions or office controversies that were exactly this. It's so much easier (and way more fun!) to dig your heels in on something of no consequence than it is to prioritize the priorities.

I don't know that there's an obvious way to avoid this either — most people aren't going to be aware that they're doing it.

I would argue that we're mostly not aware when we do this to ourselves!

It's always easier to focus on the trivial. It serves as both an opportunity to avoid more challenging, complex issues while at the same time feeding the need to feel productive through dialogue and confrontation. It's as true for work teams as it is for personal projects, procrastination techniques, and relationships.

What I'm Reading

• Person Furious That Someone Right Click Saved Their Precious NFT — You really love to see it.

• Exclusive Interview with Billionaire Charlie Munger on Controversial UCSB Dorm | 2021-11-01 | Architectural Record — This story has everything available for a late-stage capitalism musical.

• Brain Implant Translates Paralyzed Man's Thoughts Into Text With 94% Accuracy — The future of computer interaction.

• An update to dislikes on YouTube — This is an exciting development, as they're only getting rid of the numbers, not of the dislike button itself. I know I use this as a helpful signal to see the "ratio'ing" of a YouTube video, so I'm unsure how psyched I am to see this.

• Portugal bans bosses texting staff after-hours - BBC News — Amen.

Cheers,
Gabriel

Cards on the table — I'm an Elder Millennial. This means that I've had no problems adapting to technology's advances, the Internet, and a life lived very online. It also means that I'm at the age where the youth are an increasingly mysterious group. The music, the fashions, the fads — it's slowly beginning to escape my awareness and understanding.

That's how I first understood TikTok. It's just the latest iteration of something I didn't quite understand or felt compelled to engage with. It's a kids dancing and lip-syncing app, right?

While that certainly was a significant component of its early rise, I'm here to tell you that it's grown, evolved, and become something you (yes, you) should be aware of, if not following, enjoying, and creating yourself.

It's not a kid's dance app anymore. Well...ok, it's still that...but it's that plus these other things now too.

The history of Tiktok is fascinating, and its rise has been pretty meteoric, so you'd be forgiven for being surprised to hear that as of September of 2021, the app globally has over one billion active users. What's more, over half of all TikTok users are above the age of 30. See — Millennials Unite!

I don't want to gloss over the bigger picture here. The growth, the algorithm, the competitors (Netflix and Instagram), the returns to creators, the societal challenges wrought by social media, and TikTok specifically deserve careful attention.

I find it helpful when talking to the TikTok-Uninitiated to show them the breadth and depth of some of the areas they could find on the platform.

So here's a sampling — Full disclaimers that the algorithm is tossing me up precisely what I want to see, so your mileage may vary.

Amateur Comedy

This is one of the most refreshing areas to get to see. There's a whole cadre of weird, quirky, charismatic, original comedy on the platform that blows Vine videos out of the water.

These days, the most viral are the Bones / No Bones daily updates from @JonGraz that let us viewers know if the 13-year-old pug has bones that day (interested in standing up) or no bones (definitely not interested in standing up).

One-person skits (with clever editing) are the real treasure in this category. @drglaucomflecken (a real-life ophthalmologist) has incredible one-person videos conveying the world of medicine and its stereotypical doctor specialties. @nomdecoom has excellent skits about Marco Polo discovering noodles in China or what it would have been like for a Babylonian Priest Inventing Astrology. @cearajane nails the workplace divide between Boomers and Millennials (this one is my favorite), while @corporatenatalie has become the master of all workplace interactions, particularly the new remote/conference life. In a similar vein, @corporayshid walks through every awkward (and non-awkward?) interaction possible, and @mnames_jeff does an incredible IT guy persona.

There's also random and weird stuff that you just wouldn't see on other platforms. More examples: a graphic design instructor lightly mocking student submissions (part 2 just as good), scoring the relative difficulty of Riker from Star Trek's distinct seating habits, this woman randomly turning into objects over time.

There's a gold mine of just new raw talent in general. Canadian @kallmekris has nearly 40M followers, and @deadeyebrakeman and @benmarshallstyle are finding an audience for their obvious talents.

Music

This is where the platform shines. Probably the most viral videos of late have been the Sea Shanties (the one that got me hooked), which uses the dueting feature of TikTok to stitch and splice together chains of videos to add something to the original video. Taken further, these videos feature some pretty incredible ensembles, usually starting from a... somewhat awkward seed video, such as a cat making a funny noise, another cat making a funny noise, or a dryer making a funny noise.

There are some mini-masterpieces, from an evocative voice, to Star Wars renditions (french horn in a field, woman's voice under a bridge). Combining with comedy, there is the incredibly viral Internet Drama from @lubalin, and this Law and Order: SVU theme production re-enactment. Finally, just the fun and bite-sized — this woman singing scales and this Korean group doing a handful of Windows theme startups acapella style.

Pets (But Really Mostly Cats)

Look, this might just be my algorithmic skewing, but there are many adorable cats and cat behaviors on here. Cats running (fast), cats modeling, a cat dancing like Beyoncé, a cat in slo-mo attacking a box, a cat in a towel burrito as punishment, a cat using a nerf gun, cats running up a custom pole (this inspired me to make my own one of these), a cat teaching another cat how to spin attack (with dialogue), a cat catching you looking at the neighbor's cat, and a cat listening to our problems (another one with actor Rhys Darby's cat who is less than impressed).

Oh, and here's a dog hearing his favorite words.

Relaxing, Art, and Repair

This might be my favorite current genre — anything from @relaxify or @toolstour, which shows off calming, hypnotic tools and processes (and epoxy crafts for some reason?). I've also been finding myself on the repair side of TikTok, with @watchrepairers, @ladbrestoration, and @anyflug.

There is some fantastic art being demonstrated on the platform, like this clay teapot by hand from @teapotcraftsman. I was blown away by @chrisbreier's color-matching clips (color-matching a CD). But broader pieces about art as well, like @artedguru talking about painting, and @davideasterbook discussing bonsai trees.

Oh, and there is a growing genre of videos that span the gap between DIY and crafts and explainers — such as testing pan cleaning myths and 3D Printing.

Explainers

This is where TikTok can shine — there is so much good informative content being produced. An excellent recent demonstration is this video demonstrating how COVID vaccines work, but also more generally anything from science educator @hankgreen1, and compelling stories from @tomlumperson (this one about swinging bats...err...bats in swings is one of my all-time favorites and shows the platform's strengths.)

And Facts about Opossums. You didn't even know you wanted to know about opossums, but you know you do now.

There are also some outstanding commentary accounts, like @louisatalksbuildings (anything 432 Park Avenue is gold, as is this video on spite architecture). There are many helpful niche areas out there — design interaction tips from @designertom, freelance tips from @jamiebrindle, and commentary from Simon Sinek (of TED video fame).

Don't worry; there's funny/cute stuff too: pigeon cameras, random rich New York apartments, and how to make pasta sauce while the water boils (Cooking TikTok is a whole category.)

Wholesome

Finally, this is I think one of the most exciting areas of TikTok and the one I was least expecting. There is just some randomly wholesome and feel-good material on there. Yes, some of it is gamed by the algorithm, and yes, some have the heavily-produced-heart-string-pull of platforms like The Dodo — but still.

Take, for example, this video of a trucker and his cat Bobbie just enjoying the morning. There's something just so genuine about the whole clip that seems so random and short and genre-less that you couldn't imagine another platform where it would find a home.

Another example is from @yourkoreandad, a heart-warming account of a POV-style account where he does activities with you, the viewer in mind as his child of various ages. It's a bit weird at first, but after seeing this reaction video where he talks about why he thinks his account is so popular, I understood a little better how powerful this might be.

Similarly, combining all these categories is, I think, what initially brought me to TikTok, the Coming of Age clip from @americanbaron, one of my favorite new voices.

Oh, and there are also people playing with stranger's feet shadows, and it's cute.

I'm telling you, there's some good stuff there.

I would love to hear from you about what accounts you find interesting, engaging, funny, and wholesome!

It Started with Text Games

When I was a kid, I remember booting up the family computer in the office to play "Vampire's Castle," a 1984 text-based game where you had to solve the challenges by typing in commands to the interface (you can still play it here). Much of the experience was trial-and-error, as you tried different words "LOOK," "INSPECT," "GO WEST" and would be lucky if 1 in 10 did anything. It was frustrating, and I still remember getting caught up not knowing what a parapet was. The game's vocabulary was pretty limited — and it turns out it was only about words that it "knew" as commands. I remember thinking at the time that it would be so much better if it could just understand what I wrote in actual sentences.

It turns out, I just had to wait a few years for data science to mature. Computing has come a long way in a short amount of time these last few decades.

Gatekeeping Data Science

I find the "science" part of "data science" can be a bit of an unfortunate gatekeeping term. It keeps people out by making it sound like it's only done in cleanrooms or academic chalkboards.

But data science has become the de facto way to look at the intersections of people, information, data, and technology.

And a lot of people with vastly different skills are needed to work in this space.

Data science already has a considerable effect on people's lives (see: advertising, supply chains) and will have an even more significant impact moving forward (see: healthcare, climate change).

It's going to be part of the conversation. But that doesn't necessarily mean it's always going to be a welcome part of the conversation. Examples in just the last week of influence-gone-bad: Facebook's Face Recognition and Zillow's stock crash of 30% (where the CEO put much of the blame on the data science team).

The Social Impact Part

It's our opportunity (and responsibility, some would say) to use these advances in a way that provides overall benefits to society. And it's a race to the finish line.

It's a race to see how quickly we can adopt these technological advances into something beneficial before time runs out. And by time running out — it's not just a global apocalypse spawned from advancement (though, that's there too), but a race against time to provide help to those who have the most to benefit from it. For example, can we develop life-saving vaccines (with computing power assistance) to prevent hundreds of thousands of deaths? Can we use computers to help us design climate modeling to help us survive the next century? Can we use algorithms to help us design economic systems to pull people out of extreme poverty?

In other words, can we use computers to save lives and improve the human condition?

Or, at the very least, can we use computers and algorithms and data science to positive effect before we use it only to build an authoritarian global surveillance state and possibly destroy society in the process?

Unfortunately, you might say that these two ends are somewhat unrelated or at least possible at the same time. This take is probably correct — we are going to see a lot of negative social impact examples with a few outstanding good ones.

But I'm also not convinced that they are entirely mutually exclusive. The power of scale of data science, machine learning, and AI seems to imply that the next decade will be critical in pointing this science in the right direction before it becomes too unwieldy to backtrack.

A Theme of Social Impact and Data Science

In the coming months, one of the themes I intend to cover will be around data science and social impact in more specifics — both good and not-so-good examples, how we ought to think about evaluating them, etc. Let me know if there's a particular area of interest for you!

What Else I'm Reading

• Exclusive Interview with Billionaire Charlie Munger on Controversial UCSB Dorm | 2021-11-01 | Architectural Record — I'm learning everything I can about this weird dorm story. It's got a lot of stuff to hold your interest: a 97-year old amateur billionaire designing a 4,500-room dorm, and only 6% of the rooms will have windows. It seems like I wasn't the only one watching Squid Game.

• What I learned from a year on Substack » Nieman Journalism Lab — I mean, obviously I'm reading this, having just started my own Substack newsletter!

• Flow — Saw the recent passing of Mihaly Csikszentmihalyi. My dad gave all of us kids a copy of 'Flow' when I was in high school, and we talked about the concept all the time. It's stayed with me, thinking through careers, hobbies, and more.

• The 37-Year-Olds Are Afraid of the 23-Year-Olds Who Work for Them - The New York Times — I think every friend group I have sent this article around, and I'm still deciding what I think of it.

• What happened when a ransomware attack hit Pottawatomie County, Kansas. — Close to home for me.

• Person Furious That Someone Right Click Saved Their Precious NFT — I'm learning a little more about NFTs for some reason, and this story confirmed a lot of my thinking on the topic to date.

• Inside the jaw-clenching world of cricket fighting in China: NPR — Oh. Who knew!

Cheers,
Gabriel

The Facebook Papers are providing interesting, important, and not altogether surprising revelations about the inner workings and thoughts of the teams at Facebook. And the entire story has had me thinking about another unintentional release of internal content that happened to Google almost exactly 10 years ago this month, that of Steve Yegge and his posting on Google+, which has become known as the Google Plus Rant.

In October of 2011, a Google engineer named Steve Yegge posted a 3,700-word essay to his fellow Google employees about that compares and contrasts the product directions of his former employer, Amazon, with his current experience at Google. The essay covered a lot of territory in that amount of works, including areas of hiring, management, platforms, prioritizations, and some frank criticisms on tech culture at these companies. But it was posted internally, as a thought piece for fellow Googlers.

At least, Yegge meant to post it internally. What happened instead is that he accidentally posted it to his over 2,000 Google+ followers — many outside of Google's walled garden.

In many ways, what was even more interesting at the time was that Yegge was "allowed" to keep his viral rant up on Google+, and he even goes into a little more background with his follow-up post.

A Tech Nerd Cult Classic

The story at the time barely registered as a blip on the mainstream media radar, though it was notable for being so forthright in its tone.

But it reverberated with the broader technology industry as it exposed the inner dimensions and distinctions among two large organizations battling it out in similar landscapes, Google and Amazon, when (as now), the inner-workings of these companies were as veiled in secrecy as upcoming Apple product announcements.

The rant was so interesting because it's refreshingly well-written. It does an excellent job of providing context for the environments that he describes, and of the human management decisions and the people behind those decisions in the first place.

For example, we get to hear about Amazon's flawed hiring practices, the obsessive micro-management of Jeff Bezos, perks of employment, and some tech hot takes on things like versioning libraries and databases. But when you read it, you'll realize that it's a lot of shade throw. all over the place too. It can read more like a show bible for Succession or The Thick of It, than a LinkedIn tech opinion post.

He has special criticisms for Google, in peeling back the necessity to understand platforms and managing them in the first place — going out of his way to highlight the success of Facebook's plan of building "an entire constellation of products by letting other people to do the work.”.

One Word: Platforms

After discussing his experiences at Amazon to a now-Google team, Yegge's central point is about the value of Amazon's approach when it comes to platforms and systems — one that should be adopted by Google.

Essentially, Yegge gives a brief synopsis of the internal decision-making that eventually led to Amazon Web Services, or AWS, which runs a large chunk of the entire Internet. The effort began with an internal mandate that all teams had to develop interoperable systems to communicate with one another. And then communication through those systems would be mandatory and enforced. In other words, they had to eat their own dog food for these internal systems and made sure they worked.

It gets a little technical here, but the key takeaway is that everything was forced to be built from the ground up to be as universal and interoperable as possible. While this surely caused much consternation for many teams, it also had the benefit of forcing all systems to be much more secure, scalable, and efficient. And it also provided the building blocks for building a company that does $46B in a single year.

The Ever-Presence of the Rant

Over the last decade, I've worked on a number of technology teams and companies working to transform their own digital products and services. I keep coming back to this rant as a blueprint of sorts on the value of understanding how your technology fits together. For example, "the Golden Rule of Platforms, "Eat Your Own Dogfood", can be rephrased as "Start with a Platform, and Then Use it for Everything." You can't just bolt it on later."

There are many organizations, who while not blessed with the resources at Amazon's disposal, could benefit from the high-level strategy and process inherent in the rant.

I still consider this a must-read for anyone working in the tech sector, particularly if you're working on platforms, systems, and company strategy.

Today

It's actually amazing how ten years on, so much of this continues to be as immediately relevant today.

The feather in the cap, of course, is the fact that Google+ was officially shut down in 2019. The original rant is hosted on GitHub and the Wayback Machine now.

As for Yegge, he's no longer at Google, having left in 2019 to focus on developing video games. It's a fitting coda, you could say.

A What Now?

One of my favorite product analogies is that of the Egg-laying Wool Milk Sow mythical beast. Admittedly, the name rolls off a little bit better in German, as the Eierlegende-Wollmilchsau (pronounced close to eye-er-leegendah-vol-miss-shou, or so I'm told). It conjure in the mind a fun little beast — not quite a hideous beast, but not really adorable, either. Let's call it the Everything Pig, or 'EP', for short.

The basic idea is that it's got all these capabilities in one convenient little domesticated package, ready for use. You want eggs? Before you needed to raise of a bunch of chickens, set up chicken coops, the works. Now? Just call on EP. Milk? Before days, you needed cattle, lots of land, and to get up early — but EP has you covered. Wool? Sheep are such a pain — why don't you just sheer EP while you're getting milk anyway? Multitask! See where we are going?

For farmers and Austin, TX hipsters, this animal would be the dream. It's the Apple iPhone of livestock product announcements.

The Real Meaning of the EP

But really, the Everything Pig is a lesson in tradeoffs.

(And it's also to some extent probably about Jurassic Park and genomic editing ethics.)

The lesson is that the Everything Pig is a myth. We can't simply build this Swiss Army knife chimera out of thin air.

If we want to live in a world of milk, eggs, wool, and bacon (sorry, EP), then we have to consider these features along with the systems needed to be in place to support these things — farms, henhouses, grass, sheep-land, butchers, etc. Each one of these features and their associated system has its own backgrounds, histories, relationships, quirks, opportunities, and constraints. Spend an afternoon with someone who won't stop talking to you about Jersey Cows (not from New Jersey, it turns out), and you'll see what I mean.

What's this have to do with product development, particularly when it comes to building out code?

It seems obvious when we imagine our adorably Cronenberg-esque Everything Pig that we can't always get what we want at no cost, but it's less obvious when we work with teams to design software and to build products.

Single, Monolithic Solutions

One solution to rule them all is an alluring concept, as it seems more plausible, there, that we can combine a website with a company database with an expense system with a business-development-pipeline with a CRM with dashboards with AI. Why not?

I mean really, all one has to do, (the thinking goes), is to just identify all of the features that we want to see, glue them all together, and presto — finished product that does everything you want it to do.

This type of magical thinking is particularly abundant in software because working in code has such porous boundaries of possibilities — coders and marketers alike constantly reinforce that anything is possible, given the right mix of time, money, and resources. I'm surprised it isn't an enterprising tech startup company logo yet.

The notion of a single, all-capable system often also arises because there is separation between the folks looking for the finished product — who end up being the ones defining all the features they'd want to see, and the folks building out the project — who end up thinking through all the tradeoffs that have to be made.

Monolithic solutions that do everything are so tempting because we have a number of different needs that have to be met, so we're looking for a place that offers a one-stop shop for all of them, and many (myself included) are disappointed when faced with the prospect of dealing with multiple, disparate systems. It gets really complicated, really quickly.

The Reality

We often have to consider systems separately that maintain our email, our web browsers, our project management, and our data collection. What's even more frustrating, is that when it comes to the world of software, we actually could, in theory, buy/build systems that encompass all that we would like — would we actually want to? Most most most often, the answer is actually no (!)

It's not just a matter of cost (it's usually cost though). In thinking about our ecosystem of tech (whether an assortment of systems or a monolithic entity), we have to also consider maintainability, usability, security & risk assessments, longevity, flexibility, etc. Choose wrong on this, and you might look like PwC who used Lotus Notes for email until 2017.

When you start stacking all of these together, you start to realize why it's actually more strategic to have a data collection platform separate from your business intelligence software, separate from your intranet site.

There's a whole weeds angle we could get into here about the modern tradeoffs of microservices versus monolith systems — yet even the staunchest of monolith supporters still have to reign in scope creep from flooding their project. But you can also see that as you change the scale, timing, risk profile, existing expertise, etc. that you might construct a wholly new ecosystem built of different parts.

The Real Lessons

For teams that I work with, the takeaway is usually along the lines that there is often an underlying Eierlegende-Wollmilchsau implicit in our thinking. That we haven't done enough to think about the complexity behind the systems we are thinking of, the challenges in bridging them together, the time it takes to build out complicated, multi-part systems (even without the technology).

The Everything Pig is a cautionary reminder on wishing for a perfect product by just imagining the features most obvious and important features to us at the time. We need to think through things at a higher-order systems level, consider the unseen, the upkeep and maintenance costs, the investments, the resources, and the sustainability over time.

They can still be pretty cute, though.

I’ll be launching the Good Tinker newsletter shortly. This will be a weekly email from me with an original essay / article about a particular topic having to do with tech, design, or social impact, and anything in between.

The details are still being ironed out, and I’m playing around with formats, sections, and topic ideas. So if you’re reading this, I’d love to hear what you think might be good to cover that hasn’t already been done.

Looking forward to hearing your feedback, and I hope you enjoy the weekly updates!

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Oh, and in the meantime, seriously, tell your friends!