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A lot of frontend teams are very convinced that rewriting their frontend will lead to the promised land. And I am the bearer of bad tidings. If you are building a product that you hope has longevity, your frontend framework is the least interesting technical decision for you to make. And all of the time you spend arguing about it is wasted energy. I will die on this hill. If your product is still around in 5 years, you’re doing great and you should feel successful. But guess what? Whatever framework you choose will be obsolete in 5 years. That’s just how the frontend community has been operating, and I don’t expect it to change soon. Even the popular frameworks that are still around are completely different. Because change is the name of the game. So they’re gonna rewrite their shit too and just give it a new version number. Product teams that are smart are getting off the treadmill. Whatever framework you currently have, start investing in getting to know it deeply. Learn the tools until they are not an impediment to your progress. That’s the only option. Replacing it with a shiny new tool is a trap. I also wanna give a piece of candid advice to engineers who are searching for jobs. If you feel strongly about what framework you want to use, please make that a criteria for your job search. Please stop walking into teams and derailing everything by trying to convince them to switch from framework X to your framework of choice. It’s really annoying and tremendously costly. I always have to start with the cynical take. It’s just how I am. But I do want to talk about what I think should be happening instead. Companies that want to reduce the cost of their frontend tech becoming obsoleted so often should be looking to get back to fundamentals. Your teams should be working closer to the web platform with a lot less complex abstractions. We need to relearn what the web is capable of and go back to that. Let’s be clear, I’m not suggesting this is strictly better and the answer to all of your problems. I’m suggesting this as an intentional business tradeoff that I think provides more value and is less costly in the long run. I believe if you stick closer to core web technologies, you’ll be better able to hire capable engineers in the future without them convincing you they can’t do work without rewriting millions of lines of code. And if you’re an engineer, you will be able to retain much higher market value over time if you dig into and understand core web technologies. I was here before react, and I’ll be here after it dies. You may trade some job marketability today. But it does a lot more for career longevity than trying to learn every new thing that gets popular. And you see how quickly they discarded us when the market turned anyway. Knowing certain tech won’t save you from those realities. I couldn’t speak this candidly about this stuff when I held a management role. People can’t help but question my motivations and whatever agenda I may be pushing. Either that or I get into a lot of trouble with my internal team because they think I’m talking about them. But this is just what I’ve seen play out after doing this for 20+ years. And I feel like we need to be able to speak plainly. This has been brewing in my head for a long time. The frontend ecosystem is kind of broken right now. And it’s frustrating to me for a few different reasons. New developers are having an extremely hard time learning enough skills to be gainfully employed. They are drowning in this complex garbage and feeling really disheartened. As a result, companies are finding it more difficult to do basic hiring. The bar is so high just to get a regular dev job. And everybody loses. What’s even worse is that I believe a lot of this energy is wasted. People that are learning the current tech ecosystem are absolutely not learning web fundamentals. They are too abstracted away. And when the stack changes again, these folks are going to be at a serious disadvantage when they have to adapt away from what they learned. It’s a deep disservice to people’s professional careers, and it’s going to cause a lot of heartache later. On a more personal note, this is frustrating to me because I think it’s a big part of why we’re seeing the web stagnate so much. I still run into lots of devs who are creative and enthusiastic about building cool things. They just can’t. They are trying and failing because the tools being recommended to them are just not approachable enough. And at the same time, they’re being convinced that learning fundamentals is a waste of time because it’s so different from what everybody is talking about. I guess I want to close by stating my biases. I’m a web guy. I’ve been bullish on the web for 20+ years, and I will continue to be. I think it is an extremely capable and unique platform for delivering software. And it has only gotten better over time while retaining an incredible level of backwards compatibility. The underlying tools we have are dope now. But our current framework layer is working against the grain instead of embracing the platform. This is from a recent thread I wrote on mastodon. Reproduced with only light editing.
This is from a recent thread I wrote on mastodon. Reproduced with only light editing. Hm. I feel like I wanted to like this more than I actually do. I definitely think the fediverse needs to continue to grow more capabilities. But this doesn’t feel like the energy I was looking for. Half of it feels like a laundry list of ways to commodify things. Dragging a lot of things people hate about corporate social media into the fediverse. I’ve only just started to engage with the fediverse as a concept and a movement. And mastodon is only one part of a wide ecosystem. I think what has been surprising to me is it at least within mastodon, it doesn’t feel like the culture is centered around enabling people to build and experiment. Maybe this is only how I think about it. But there are only a few good reasons to do all of this work. We want to reclaim our online experiences. So they aren’t fully captured by corporate interests. But after that? I think the goal should be to enable greater diversity of experience. People can have what they want by running it on their own servers. It doesn’t have to be something that we wait for someone else to build and ship. It feels like we’re still trying to over-design corporate solutions that work for “everybody”. And that feels like constrained thinking. I feel like the fediverse should be on the other end of the spectrum. There should be an explosion of solutions. Most of them will probably be crap. But the ones who keep refining and improving will rise to the top and gain more adoption. Honestly I don’t think “gaining adoption” is that important in a truly diverse ecosystem. The reason concepts like adoption become useful is when it drives compatibility. We do want different servers to be able to participate in the larger society. But I think compatibility emerges because people want to participate. You have to add the value first. Then people will do the work to be compatible so they can get to the value. If I was stating what I think is important in the fediverse right now, it would be describing what it takes to be “compatible”. I think the “core” groups around fediverse technologies should be hyper focused on describing and documenting how their foundational protocols behave. And their measure of success should be seeing other groups building compatible servers entirely independent of them. That is a healthy fediverse imo. I don’t want to start too much trouble here. But I’m already on record with my criticisms of the open source community. I hope we can acknowledge that the community of devs, who is doing much of this work for free, has some serious cultural issues to contend with if they’re going to serve the wider set of users who want and need this stuff. We know that corporate interests want to own and capture our experiences for the purposes of profit and control. But open source devs often want to own and capture the work. So that it can only happen the way they say. And as a result, anything we want to see happen is bottlenecked on a small set of humans who have set themselves up as gatekeepers. I’m not suggesting this is always a malicious dynamic. A lot of times people have legitimate concerns for gatekeeping. Like protecting the security and privacy of users. Or preventing data corruption. Some elements of software do need to be scrutinized by experts so that people don’t get hurt. But I believe that’s a smaller area than people seem to think. I’m not that interested in debating the reasons for some of the more frustrating elements of open source culture. All I’m saying today is that I believe that open source culture will need to evolve pretty quickly if it’s going to rise to this moment of enabling a healthy and vibrant fediverse.
This is the first in probably a series of posts as I dig into the technical aspects of mastodon. My goal is to get a better understanding of the design of ActivityPub and how mastodon itself is designed to use ActivityPub. Eventually I want to learn enough to maybe do some hacking and create some of the experiences I want that mastodon doesn’t support today. The first milestone is just getting a mastodon instance set up on my laptop. I’m gonna give some background and context. If you want to skip straight to the meat of things, here’s an anchor link. Some background Mastodon is a complex application with lots of moving parts. For now, all I want is to get something running so I can poke at it. Docker should be a great tool for this. Because a lot of that complexity can be packaged up in pre-built images. I tried several times using using the official docs and various other alternative projects to get a working mastodon instance in docker. But I kept running into problems that were hard to understand and harder to resolve. I have a lot to learn about all the various pieces of mastodon and how they fit together. But I understand docker pretty well. So after some experimenting, I was able to get an instance running on my own. The rest of this post will be dedicated to explaining what I did and what I learned along the way. One final note. I know many folks work hard to write docs and provide an out of the box dev experience that works. This isn’t meant to dismiss that hard work. It just didn’t work for me. I’m certainly going to share this experience with the mastodon team. Hopefully these lessons can make the experience better for others in the future. The approach Here’s the outline of what we’re doing. We’re going to use a modified version of the docker-compose.yml that comes in the official mastodon repo. It doesn’t work out of the box. So I had to make some heavy tweaks. As of this writing, the mastodon docs seem to want people to use an alternate setup based on Dev Containers. I found that very confusing, and it didn’t work for me at all. Once we have all of the docker images we need, all of the headaches are in configuring them to work together. Most of mastodon is a ruby on rails app with a database. But there is also a node app to handle streaming updates, redis for caching and background jobs, and we need to handle file storage. We will do the minimum configuration to get all of that set up and able to talk to each other. There is also support for sending emails and optional search capabilities. These are not required just to get something working, so we’ll ignore them for now. It’s also worth noting that if we want to develop code in mastodon, we need to put our rails app in development mode. That introduces another layer of headaches and errors that I haven’t figured out yet. So that will be a later milestone. For now, all of this will be in “production” mode by default. That’s how the docker image comes packaged. Keep it simple. There are still many assumptions here. I am running on Mac OS with Apple Silicon (M3). If you’re trying this out, you may run into different issues depending your environment. Pre-requisites We need docker. And a relatively new version. The first thing I did was ditch the version: 3 specifier in the docker-compose.yml. Using versions in these files is deprecated, and we can use some newer features of docker compose. I have v4.30.0 of Docker Desktop for Mac. We also need caddy. Mastodon instances require a domain in most cases. This is mostly about identity and security. It would be bad if an actor on mastodon could change their identity very easily just by pretending to be a different domain or account. There are ways around this, but I couldn’t get any of them to work for me. That complicates our setup. Because we can’t just use localhost in the browser. We need a domain, which means we also need HTTPS support. Modern browsers require it by default unless you jump through a bunch of hoops. Caddy gives us all of that out of the box really easily. It will be the only thing running outside of docker. There’s only one caveat with caddy. The way that it is able to do ssl termination so easily is that it creates its own certificates on the fly. The way it does this is by installing it’s own root cert on your machine. You’ll have to give it permission by putting in your laptop password the first time you run caddy. If that makes you nervous, feel free to skip this and use whatever solution you’re comfortable with for SSL termination. But as far as I know, you need this part. Choose a domain for your local instance. For me it was polotek-social.local. Something that mkes it obvious that this is not a real online instance. Add an entry to your /etc/hosts and point this to localhost. Or whatever people have to do on Windows these days. Let’s run a mastodon I put all of my changes in my fork of the official mastodon repo. You can clone this branch and follow along. All of the commands assume you are in the root directory of the cloned repo. https://github.com/polotek/mastodon/tree/polotek-docker-build > git clone git@github.com:polotek/mastodon.git > cd mastodon > git co -b polotek-docker-build I rewrote the docker section of the README.md to outline the new instructions. I’m going to walk through my explanation of the changes. Pull docker images This is the easiest part. All of the docker images are prepackaged. Even the rails app. You can use the docker compose command to pull them all. It’ll take a minute or 2. > docker compose pull Setup config files We’re using a couple of config files. The repo comes with .env.production.sample. This is a nice way to outline the minimum configuration that is required. You can copy that to .env.production and everything is already set up to look for that file. The only thing you have to do here is update the LOCAL_DOMAIN field. This should be the same as the domain you chose and put in your /etc/hosts. You can put all of your configuration in this file. But I found it more convenient to separate out the various secrets. These often need to be changed or regenerated. I wrote a script to make that repeatable. Any secrets go in .env.secrets. We’ll come back to how you get those values in a bit. I had to make some other fixes here. Because we’re using docker, we need to update how the rails app finds the other dependencies. The default values seem to assume that redis and postgres are reachable locally on the same machine. I had to change those values to match the docker setup. The REDIS_HOST is redis, and the DB_HOST is db. Because that’s what they are named in the docker-compose file. Diff of config file on github The rest of the changes are just disabling non-essential services like elastic search and s3 storage. Generate secrets We need just a handful of config fields that are randomly generated and considered sensitive. Rails makes it easy to generate secrets. But run the required commands through docker and getting them in the right place is left as an exercise for the reader. I added a small script that runs these commands and outputs the right fields. Rather than try to edit the .env.production file in the right places everytime secrets get regenerated, I think it’s much easier to have them in a separate file. Fortunately, docker-compose allows us to specify multiple files to fill out the environment variables. Diff of config file on github This was a nice quality of life change. And now regenerated secrets and making them available is just one command. > bin/gen_secrets > .env.secrets Any additional secrets can be added by just updating this script. For example, I use 1password to store lots of things, even for development. And I can pull things out using their cli named op. Here’s how I configured the email secrets with the credentials from my mailgun account. # Email echo SMTP_LOGIN=$(op read "op://Dev/Mailgun SMTP/username") echo SMTP_PASSWORD=$(op read "op://Dev/Mailgun SMTP/password") Run the database Running the database is easy. > docker compose up db -d You’ll need to have your database running while you run these next steps. The -d flag will run it in the background so you can get your terminal back. I often prefer to skip the -d and run multiple terminal windows. That way I can know at a glance if something is running or not. But do whatever feels good. The only note here is to explain another small change to docker-compose to get this running. We’re using a docker image that comes ready to run postgres. This is great because it removes a lot of the fuss of running a database. The image also provides some convenient ways to configure the name of the database and the primary user account. This becomes important because maston preconfigures these values for rails. We can see this in the default .env.production values. DB_USER=mastodon DB_NAME=mastodon_production The database name is not a big issue. Rails will create a database with that name if it doesn’t exist. But it will not create the user (maybe there’s a non-standard flag you can set?). We have to make sure postgres already recognizes a user with the name mastodon. That’s easy enough to do by passing these as environment variables to the database container only. Diff of config file on github Load the database schema One thing that’s always a pain when running rails in docker. Rails won’t start successfully until you load the schema into the database and seed it with the minimal data. This is easy to do if you can run the rake tasks locally. You can’t run the rake tasks until you have a properly configured rails. And it’s hard to figure out if your rails is configured properly because it won’t run without the database. I don’t know what this is supposed to look like to a seasoned rails expert. But for me it’s always a matter of getting the db:setup rake task to run successfully at least once. After that, everything else starts making sense. However, how do you get this to work in our docker setup? We can’t just do docker compose up, because the rails container will fail. We can’t use docker compose exec because that expects to attach to an existing instance. So the best thing to do is run a one-off container that only runs the rake task. The way to achieve that with docker compose is docker compose run --rm. The rm flags just makes sure the container gets trashed afterwards. Because we’re running our own command instead of the default one, we don’t want it hanging around and potentially muddying the waters. Once we know the magic incantation, we can setup the database. > docker compose run --rm web bundle exec rails db:setup Note: Usually you don’t put quotes around the whole command. For some reason, this can cause problems in certain cases. You can put quotes around any individual arguments if you need to. Run rails and sidekiq If you’ve gotten through all of the steps above, you’re ready to run the whole shebang. > docker compose up This will start all of the other necessary containers, including rails and sidekiq. Everything should be able to recognize and connect to postgres and redis. We’re in the home stretch. But if you try to reach rails directly in your browser by going to https://localhost:3000, you’ll get this cryptic error. ERROR -- : [ActionDispatch::HostAuthorization::DefaultResponseApp] Blocked hosts: localhost:3000 It took me a while to track this down. It’s a nice security feature built into rails. When running in production, you need to configure a whitelist of domains that rails will run under. If it receives request headers that don’t match those domains, it produces this error. This prevents certain attacks like dns rebinding. (Which I also learned about at the same time) If you set RAILS_ENV=development, then localhost is added to the whitelist by default. That’s convenient, and what we would expect from dev mode. But remember we’re not running in development mode quite yet. So this is a problem for us. The nice thing is that mastodon has added a domain to the whitelist already. Whatever value you put in the LOCAL_DOMAIN field is recognized by rails. (In fact, if you just set this to localhost you might be good to go. Shoutout to Ben.) However, when you use an actual domain, then most modern web browsers force you to use HTTPS. This is another generally nice security feature that is getting in our way right now. So we need a way to use our LOCAL_DOMAIN, terminate SSL, and then proxy the request to the rails server running inside docker. That brings us to the last piece of the puzzle. Running caddy outside of docker. Run a reverse proxy The configuration for caddy is very basic. We put in our domain, we put in two reverse proxy entries. One for rails and one for the streaming server provided by node.js. Assuming you don’t need anything fancy, caddy provides SSL termination out of the box with no additional configuration. # Caddyfile polotek-social.local reverse_proxy :3000 reverse_proxy /api/v1/streaming/* :4000 We put this in a file named Caddyfile in the root of our mastodon project, then in a new terminal window, start caddy. > caddy run Success? If everything has gone as planned, you should be able to put your local mastodon domain in your browser and see the frontpage of mastodon! Mastodon frontpage running under local domain! In the future, I’ll be looking at how to get actual accounts set up and how to see what we can see under the hood of mastodon. I’m sure I’ll work to make all of this more developement friendly to work with. But I learned a lot about mastodon just by getting this to run. I hope some of these changes can be contributed back to the main project in the future. Or at least serve as lessons that can be incorporated. I’d like to see it be easier for more people to get mastodon set up and start poking around.
In my recent side projet, I’ve been deploying to fly.io and really enjoying it. It’s fairly easy to get setup. And it supports my preferred workflow of deploying my changes early and often. I have run into a few snags though. Fly.io builds your project into a docker image and deploys containers for you. That process is mostly seamless when it works. But sometimes it fails, and you need to debug. By default, fly builds your docker images in the cloud. This is convient and preferred most of the time. But when I wanted to test some changes to my build, I wanted to try building locally using Docker Desktop. This should be easy. The fly cli is quite nice. And there is a flag to build locally. fly deploy --build-only --local-only This failed saying it couldn’t find Docker. > fly deploy --build-only --local-only ==> Verifying app config Validating /Users/polotek/src/harembase/fly.toml Platform: machines ✓ Configuration is valid --> Verified app config ==> Building image Error: failed to fetch an image or build from source: docker is unavailable to build the deployment image I spent quite a bit of time googling for the problem here. You can also run fly doctor --verbose to get some info. (If you run this in your fly app folder, it will show more info not relevant to this topic.) > fly doctor --verbose Testing authentication token... PASSED Testing flyctl agent... PASSED Testing local Docker instance... Nope (We got: failed pinging docker instance: Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?) This is fine, we'll use a remote builder. Pinging WireGuard gateway (give us a sec)... PASSED No app provided; skipping app specific checks I found various forum posts discussing this problem. The folks at fly have spent a lot of time investigating some deep technical issues. I appreciate that work, but ultimately none of it seems to reflect my problem. And the issue felt simpler to me. Fly couldn’t find docker. Why not? Where is it looking? Eventually I found the answer on stackoverflow. It turns out that things have settled pretty recently to a basic config setting. By default, Docker Desktop installs the socket for the daemon in a non-global space. Usually in your personal user folder, e.g. ~/.docker/run/docker.sock. But other tools expect the docker daemon socket to be available in a standard location, e.g. /var/run/docker.sock As of this writing, Docker Deskstop has added a recommended way to enable the standard location. In the Docker Desktop dashboard, got to Settings > Advanced and enable “Allow the default Docker socket to be used”. Docker for Mac settings screen This will require your system password and restart. Then you should be able to see the docker socket in the standard place. And fly will be able to see it! Hopefully the next person who’s banging their head against this will have an easier time.
More in programming
What does it mean when someone writes that a programming language is “strongly typed”? I’ve known for many years that “strongly typed” is a poorly-defined term. Recently I was prompted on Lobsters to explain why it’s hard to understand what someone means when they use the phrase. I came up with more than five meanings! how strong? The various meanings of “strongly typed” are not clearly yes-or-no. Some developers like to argue that these kinds of integrity checks must be completely perfect or else they are entirely worthless. Charitably (it took me a while to think of a polite way to phrase this), that betrays a lack of engineering maturity. Software engineers, like any engineers, have to create working systems from imperfect materials. To do so, we must understand what guarantees we can rely on, where our mistakes can be caught early, where we need to establish processes to catch mistakes, how we can control the consequences of our mistakes, and how to remediate when somethng breaks because of a mistake that wasn’t caught. strong how? So, what are the ways that a programming language can be strongly or weakly typed? In what ways are real programming languages “mid”? Statically typed as opposed to dynamically typed? Many languages have a mixture of the two, such as run time polymorphism in OO languages (e.g. Java), or gradual type systems for dynamic languages (e.g. TypeScript). Sound static type system? It’s common for static type systems to be deliberately unsound, such as covariant subtyping in arrays or functions (Java, again). Gradual type systems migh have gaping holes for usability reasons (TypeScript, again). And some type systems might be unsound due to bugs. (There are a few of these in Rust.) Unsoundness isn’t a disaster, if a programmer won’t cause it without being aware of the risk. For example: in Lean you can write “sorry” as a kind of “to do” annotation that deliberately breaks soundness; and Idris 2 has type-in-type so it accepts Girard’s paradox. Type safe at run time? Most languages have facilities for deliberately bypassing type safety, with an “unsafe” library module or “unsafe” language features, or things that are harder to spot. It can be more or less difficult to break type safety in ways that the programmer or language designer did not intend. JavaScript and Lua are very safe, treating type safety failures as security vulnerabilities. Java and Rust have controlled unsafety. In C everything is unsafe. Fewer weird implicit coercions? There isn’t a total order here: for instance, C has implicit bool/int coercions, Rust does not; Rust has implicit deref, C does not. There’s a huge range in how much coercions are a convenience or a source of bugs. For example, the PHP and JavaScript == operators are made entirely of WAT, but at least you can use === instead. How fancy is the type system? To what degree can you model properties of your program as types? Is it convenient to parse, not validate? Is the Curry-Howard correspondance something you can put into practice? Or is it only capable of describing the physical layout of data? There are probably other meanings, e.g. I have seen “strongly typed” used to mean that runtime representations are abstract (you can’t see the underlying bytes); or in the past it sometimes meant a language with a heavy type annotation burden (as a mischaracterization of static type checking). how to type So, when you write (with your keyboard) the phrase “strongly typed”, delete it, and come up with a more precise description of what you really mean. The desiderata above are partly overlapping, sometimes partly orthogonal. Some of them you might care about, some of them not. But please try to communicate where you draw the line and how fuzzy your line is.
(Last week's newsletter took too long and I'm way behind on Logic for Programmers revisions so short one this time.1) In classical logic, two operators F/G are duals if F(x) = !G(!x). Three examples: x || y is the same as !(!x && !y). <>P ("P is possibly true") is the same as ![]!P ("not P isn't definitely true"). some x in set: P(x) is the same as !(all x in set: !P(x)). (1) is just a version of De Morgan's Law, which we regularly use to simplify boolean expressions. (2) is important in modal logic but has niche applications in software engineering, mostly in how it powers various formal methods.2 The real interesting one is (3), the "quantifier duals". We use lots of software tools to either find a value satisfying P or check that all values satisfy P. And by duality, any tool that does one can do the other, by seeing if it fails to find/check !P. Some examples in the wild: Z3 is used to solve mathematical constraints, like "find x, where f(x) >= 0. If I want to prove a property like "f is always positive", I ask z3 to solve "find x, where !(f(x) >= 0), and see if that is unsatisfiable. This use case powers a LOT of theorem provers and formal verification tooling. Property testing checks that all inputs to a code block satisfy a property. I've used it to generate complex inputs with certain properties by checking that all inputs don't satisfy the property and reading out the test failure. Model checkers check that all behaviors of a specification satisfy a property, so we can find a behavior that reaches a goal state G by checking that all states are !G. Here's TLA+ solving a puzzle this way.3 Planners find behaviors that reach a goal state, so we can check if all behaviors satisfy a property P by asking it to reach goal state !P. The problem "find the shortest traveling salesman route" can be broken into some route: distance(route) = n and all route: !(distance(route) < n). Then a route finder can find the first, and then convert the second into a some and fail to find it, proving n is optimal. Even cooler to me is when a tool does both finding and checking, but gives them different "meanings". In SQL, some x: P(x) is true if we can query for P(x) and get a nonempty response, while all x: P(x) is true if all records satisfy the P(x) constraint. Most SQL databases allow for complex queries but not complex constraints! You got UNIQUE, NOT NULL, REFERENCES, which are fixed predicates, and CHECK, which is one-record only.4 Oh, and you got database triggers, which can run arbitrary queries and throw exceptions. So if you really need to enforce a complex constraint P(x, y, z), you put in a database trigger that queries some x, y, z: !P(x, y, z) and throws an exception if it finds any results. That all works because of quantifier duality! See here for an example of this in practice. Duals more broadly "Dual" doesn't have a strict meaning in math, it's more of a vibe thing where all of the "duals" are kinda similar in meaning but don't strictly follow all of the same rules. Usually things X and Y are duals if there is some transform F where X = F(Y) and Y = F(X), but not always. Maybe the category theorists have a formal definition that covers all of the different uses. Usually duals switch properties of things, too: an example showing some x: P(x) becomes a counterexample of all x: !P(x). Under this definition, I think the dual of a list l could be reverse(l). The first element of l becomes the last element of reverse(l), the last becomes the first, etc. A more interesting case is the dual of a K -> set(V) map is the V -> set(K) map. IE the dual of lived_in_city = {alice: {paris}, bob: {detroit}, charlie: {detroit, paris}} is city_lived_in_by = {paris: {alice, charlie}, detroit: {bob, charlie}}. This preserves the property that x in map[y] <=> y in dual[x]. And after writing this I just realized this is partial retread of a newsletter I wrote a couple months ago. But only a partial retread! ↩ Specifically "linear temporal logics" are modal logics, so "eventually P ("P is true in at least one state of each behavior") is the same as saying !always !P ("not P isn't true in all states of all behaviors"). This is the basis of liveness checking. ↩ I don't know for sure, but my best guess is that Antithesis does something similar when their fuzzer beats videogames. They're doing fuzzing, not model checking, but they have the same purpose check that complex state spaces don't have bugs. Making the bug "we can't reach the end screen" can make a fuzzer output a complete end-to-end run of the game. Obvs a lot more complicated than that but that's the general idea at least. ↩ For CHECK to constraint multiple records you would need to use a subquery. Core SQL does not support subqueries in check. It is an optional database "feature outside of core SQL" (F671), which Postgres does not support. ↩
Omarchy 2.0 was released on Linux's 34th birthday as a gift to perhaps the greatest open-source project the world has ever known. Not only does Linux run 95% of all servers on the web, billions of devices as an embedded OS, but it also turns out to be an incredible desktop environment! It's crazy that it took me more than thirty years to realize this, but while I spent time in Apple's walled garden, the free software alternative simply grew better, stronger, and faster. The Linux of 2025 is not the Linux of the 90s or the 00s or even the 10s. It's shockingly more polished, capable, and beautiful. It's been an absolute honor to celebrate Linux with the making of Omarchy, the new Linux distribution that I've spent the last few months building on top of Arch and Hyprland. What began as a post-install script has turned into a full-blown ISO, dedicated package repository, and flourishing community of thousands of enthusiasts all collaborating on making it better. It's been improving rapidly with over twenty releases since the premiere in late June, but this Version 2.0 update is the biggest one yet. If you've been curious about giving Linux a try, you're not afraid of an operating system that asks you to level up and learn a little, and you want to see what a totally different computing experience can look and feel like, I invite you to give it a go. Here's a full tour of Omarchy 2.0.
In 2020, Apple released the M1 with a custom GPU. We got to work reverse-engineering the hardware and porting Linux. Today, you can run Linux on a range of M1 and M2 Macs, with almost all hardware working: wireless, audio, and full graphics acceleration. Our story begins in December 2020, when Hector Martin kicked off Asahi Linux. I was working for Collabora working on Panfrost, the open source Mesa3D driver for Arm Mali GPUs. Hector put out a public call for guidance from upstream open source maintainers, and I bit. I just intended to give some quick pointers. Instead, I bought myself a Christmas present and got to work. In between my university coursework and Collabora work, I poked at the shader instruction set. One thing led to another. Within a few weeks, I drew a triangle. In 3D graphics, once you can draw a triangle, you can do anything. Pretty soon, I started work on a shader compiler. After my final exams that semester, I took a few days off from Collabora to bring up an OpenGL driver capable of spinning gears with my new compiler. Over the next year, I kept reverse-engineering and improving the driver until it could run 3D games on macOS. Meanwhile, Asahi Lina wrote a kernel driver for the Apple GPU. My userspace OpenGL driver ran on macOS, leaving her kernel driver as the missing piece for an open source graphics stack. In December 2022, we shipped graphics acceleration in Asahi Linux. In January 2023, I started my final semester in my Computer Science program at the University of Toronto. For years I juggled my courses with my part-time job and my hobby driver. I faced the same question as my peers: what will I do after graduation? Maybe Panfrost? I started reverse-engineering of the Mali Midgard GPU back in 2017, when I was still in high school. That led to an internship at Collabora in 2019 once I graduated, turning into my job throughout four years of university. During that time, Panfrost grew from a kid’s pet project based on blackbox reverse-engineering, to a professional driver engineered by a team with Arm’s backing and hardware documentation. I did what I set out to do, and the project succeeded beyond my dreams. It was time to move on. What did I want to do next? Finish what I started with the M1. Ship a great driver. Bring full, conformant OpenGL drivers to the M1. Apple’s drivers are not conformant, but we should strive for the industry standard. Bring full, conformant Vulkan to Apple platforms, disproving the myth that Vulkan isn’t suitable for Apple hardware. Bring Proton gaming to Asahi Linux. Thanks to Valve’s work for the Steam Deck, Windows games can run better on Linux than even on Windows. Why not reap those benefits on the M1? Panfrost was my challenge until we “won”. My next challenge? Gaming on Linux on M1. Once I finished my coursework, I started full-time on gaming on Linux. Within a month, we shipped OpenGL 3.1 on Asahi Linux. A few weeks later, we passed official conformance for OpenGL ES 3.1. That put us at feature parity with Panfrost. I wanted to go further. OpenGL (ES) 3.2 requires geometry shaders, a legacy feature not supported by either Arm or Apple hardware. The proprietary OpenGL drivers emulate geometry shaders with compute, but there was no open source prior art to borrow. Even though multiple Mesa drivers need geometry/tessellation emulation, nobody did the work to get there. My early progress on OpenGL was fast thanks to the mature common code in Mesa. It was time to pay it forward. Over the rest of the year, I implemented geometry/tessellation shader emulation. And also the rest of the owl. In January 2024, I passed conformance for the full OpenGL 4.6 specification, finishing up OpenGL. Vulkan wasn’t too bad, either. I polished the OpenGL driver for a few months, but once I started typing a Vulkan driver, I passed 1.3 conformance in a few weeks. What remained was wiring up the geometry/tessellation emulation to my shiny new Vulkan driver, since those are required for Direct3D. Et voilà, Proton games. Along the way, Karol Herbst passed OpenCL 3.0 conformance on the M1, running my compiler atop his “rusticl” frontend. Meanwhile, when the Vulkan 1.4 specification was published, we were ready and shipped a conformant implementation on the same day. After that, I implemented sparse texture support, unlocking Direct3D 12 via Proton. …Now what? Ship a great driver? Check. Conformant OpenGL 4.6, OpenGL ES 3.2, and OpenCL 3.0? Check. Conformant Vulkan 1.4? Check. Proton gaming? Check. That’s a wrap. We’ve succeeded beyond my dreams. The challenges I chased, I have tackled. The drivers are fully upstream in Mesa. Performance isn’t too bad. With the Vulkan on Apple myth busted, conformant Vulkan is now coming to macOS via LunarG’s KosmicKrisp project building on my work. Satisfied, I am now stepping away from the Apple ecosystem. My friends in the Asahi Linux orbit will carry the torch from here. As for me? Onto the next challenge!
TokyoDev has published a number of different guides on coming to Japan to work as a software developer. But what if you’re already employed in another industry in Japan, and are considering changing your career to software development? I interviewed four people who became developers after they moved to Japan, for their advice and personal experiences on: Why they chose development How they switched careers How they successfully found their first jobs What mistakes they made in the job hunt The most important advice they give to others Why switch to software development? A lifelong goal For Yuta Asakura, a career in software was the dream all along. “I’ve always wanted to work with computers,” he said, “but due to financial difficulties, I couldn’t pursue a degree in computer science. I had to start working early to support my single mother. As the eldest child, I focused on helping my younger brother complete his education.” To support his family, Asakura worked in construction for eight years, eventually becoming a foreman in Yokohama. Meanwhile, his brother graduated, and became a software engineer after joining the Le Wagon Tokyo bootcamp. About a year before his brother graduated, Asakura began to delve back into development. “I had already begun self-studying in my free time by taking online courses and building small projects,” he explained. “ I quickly became hooked by how fun and empowering it was to learn, apply, and build. It wasn’t always easy. There were moments I wanted to give up, but the more I learned, the more interesting things I could create. That feeling kept me going.” What truly inspired me was the idea of creating something from nothing. Coming from a construction background, I was used to building things physically. But I wanted to create things that were digital, scalable, borderless, and meaningful to others. An unexpected passion As Andrew Wilson put it, “Wee little Andrew had a very digital childhood,” full of games and computer time. Rather than pursuing tech, however, he majored in Japanese and moved to Japan in 2012, where he initially worked as a language teacher and recruiter before settling into sales. Wilson soon discovered that sales wasn’t really his strong suit. “At the time I was selling three different enterprise software solutions.” So I had to have a fairly deep understanding of that software from a user perspective, and in the course of learning about these products and giving technical demonstrations, I realized that I liked doing that bit of my job way more than I liked actually trying to sell these things. Around that time, he also realized he didn’t want to manually digitize the many business cards he always collected during sales meetings: “That’s boring, and I’m lazy.” So instead, he found a business card-scanning app, made a spreadsheet to contain the data, automated the whole process, and shared it internally within his company. His manager approached him soon afterwards, saying, “You built this? We were looking to hire someone to do this!” Encouraged, Wilson continued to develop it. “As soon as I was done with work,” he explained with a laugh, “I was like, ‘Oh boy, I can work on my spreadsheet!’” As a result, Wilson came to the conclusion that he really should switch careers and pursue his passion for programming. Similarly to Wilson, Malcolm Hendricks initially focused on Japanese. He came to Japan as an exchange student in 2002, and traveled to Japan several more times before finally relocating in 2011. Though his original role was as a language teacher, he soon found a job at a Japanese publishing company, where he worked as an editor and writer for seven years. However, he felt burned out on the work, and also that he was in danger of stagnating; since he isn’t Japanese, the road to promotion was a difficult one. He started following some YouTube tutorials on web development, and eventually began creating websites for his friends. Along the way, he fell in love with development, on both a practical and a philosophical level. “There’s another saying I’ve heard here and there—I don’t know exactly who to attribute it to—but the essence of it goes that ‘Computer science is just teaching rocks how to think,’” Hendricks said. “My mentor Bob has been guiding me through the very fundamentals of computer science, down to binary calculations, Boolean logic, gate theory, and von Neumann architecture. He explains the fine minutia and often concludes with, ‘That’s how it works. There’s no magic to it.’ “Meanwhile, in the back of my mind, I can’t help but be mystified at the things we are all now able to do, such as having video calls from completely different parts of the world, or even me here typing on squares of plastic to make letters appear on a screen that has its own source of light inside it. . . . [It] sounds like the highest of high-fantasy wizardry to me.” I’ve always had a love for technomancy, but I never figured I might one day get the chance to be a technomancer myself. And I love it! We have the ability to create nigh unto anything in the digital world. A practical solution When Paulo D’Alberti moved to Japan in 2019, he only spoke a little Japanese, which limited his employment prospects. With his prior business experience, he landed an online marketing role for a blockchain startup, but eventually exited the company to pursue a more stable work environment. “But when I decided to leave the company,” D’Alberti said, “my Japanese was still not good enough to do business. So I was at a crossroads.” Do I decide to join a full-time Japanese language course, aiming to get JLPT N2 or the equivalent, and find a job on the business side? . . . Or do I say screw it and go for a complete career change and get skills in something more technical, that would allow me to carry those skills [with me] even if I were to move again to another country?” The portability of a career in development was a major plus for D’Alberti. “That was one of the big reasons. Another consideration was that, looking at the boot camps that were available, the promise was ‘Yeah, we’ll teach you to be a software developer in nine weeks or two months.’ That was a much shorter lead time than getting from JLPT N4 to N2. I definitely wouldn’t be able to do that in two months.” Since D’Alberti had family obligations, the timeline for his career switch was crucial. “We still had family costs and rent and groceries and all of that. I needed to find a job as soon as possible. I actually already at that point had been unsuccessfully job hunting for two months. So that was like, ‘Okay, the savings are winding up, and we are running out of options. I need to make a decision and make it fast.’” How to switch careers Method 1: Software Development Bootcamp Under pressure to find new employment quickly, D’Alberti decided to enter the Le Wagon Coding Bootcamp in Tokyo. Originally, he wavered between Le Wagon and Code Chrysalis, which has since ended its bootcamp programs. “I went with Le Wagon for two reasons,” he explained. “There were some scheduling reasons. . . . But the main reason was that Code Chrysalis required you to pass a coding exam before being admitted to their bootcamp.” Since D’Alberti was struggling to learn development by himself, he knew his chances of passing any coding exam were slim. “I tried Code Academy, I tried Solo Learn, I tried a whole bunch of apps online, I would follow the examples, the exercises . . . nothing clicked. I wouldn’t understand what I was doing or why I was doing it.” At the time, Le Wagon only offered full-time web development courses, although they now also have part-time courses and a data science curriculum. Since D’Alberti was unemployed, a full-time program wasn’t a problem for him, “But it did mean that the people who were present were very particular [kinds] of people: students who could take some time off to add this to their [coursework], or foreigners who took three months off and were traveling and decide to come here and do studying plus sightseeing, and I think there were one or two who actually asked for time off from the job in order to participate.” It was a very intense course, and the experience itself gave me exactly what I needed. I had been trying to learn by myself. It did not work. I did not understand. [After joining], the first day or second day, suddenly everything clicked. D’Alberti appreciated how Le Wagon organized the curriculum to build continuously off previous lessons. By the time he graduated in June of 2019, he’d built three applications from scratch, and felt far more confident in his coding abilities. “It was great. [The curriculum] was amazing, and I really felt super confident in my abilities after the three months. Which, looking back,” he joked, “I still had a lot to learn.” D’Alberti did have some specific advice for those considering a bootcamp: “Especially in the last couple of weeks, it can get very dramatic. You are divided into teams and as a team, you’re supposed to develop an application that you will be demonstrating in front of other people.” Some of the students, D’Alberti explained, felt that pressure intensely; one of his classmates broke down in tears. “Of course,” he added, “one of the big difficulties of joining a bootcamp is economical. The bootcamp itself is quite expensive.” While between 700,000 and 800,000 yen when D’Alberti went through the bootcamp, Le Wagon’s tuition has now risen to 890,000 yen for Web Development and 950,000 for Data Science. At the time D’Alberti joined there was no financial assistance. Now, Le Wagon has an agreement with Hello Work, so that students who are enrolled in the Hello Work system can be reimbursed for up to 70 percent of the bootcamp’s tuition. Though already studying development by himself, Asakura also enrolled in Le Wagon Tokyo in 2024, “to gain structure and accountability,” he said. One lesson that really stayed with me came from Sylvain Pierre, our bootcamp director. He said, ‘You stop being a developer the moment you stop learning or coding.’ That mindset helped me stay on track. Method 2: Online computer science degree Wilson considered going the bootcamp route, but decided against it. He knew, from his experience in recruiting, that a degree would give him an edge—especially in Japan, where having the right degree can make a difference in visa eligibility “The quality of bootcamps is perfectly fine,” he explained. “If you go through a bootcamp and study hard, you can get a job and become a developer no problem. I wanted to differentiate myself on paper as much as I could . . . [because] there are a lot of smart, motivated people who go through a bootcamp.” Whether it’s true or not, whether it’s valid or not, if you take two candidates who are very similar on paper, and one has a coding bootcamp and one has a degree, from a typical Japanese HR perspective, they’re going to lean toward the person with the degree. “Whether that’s good or not, that’s sort of a separate situation,” Wilson added. “But the reality [is] I’m older and I’m trying to make a career change, so I want to make sure that I’m giving myself every advantage that I can.” For these reasons, Wilson opted to get his computer science degree online. “There’s a program out of the University of Oregon, for people who already had a Bachelor’s degree in a different subject to get a Bachelor’s degree in Computer Science. “Because it’s limited to people who already have a Bachelor’s degree, that means you don’t need to take any non-computer science classes. You don’t need any electives or prerequisites or anything like that.” As it happened, Wilson was on paternity leave when he started studying for his degree. “That was one of my motivations to finish quickly!” he said. In the end, with his employer’s cooperation, he extended his paternity leave to two years, and finished the degree in five quarters. Method 3: Self-taught Hendricks took a different route, combining online learning materials with direct experience. He primarily used YouTube tutorials, like this project from one of his favorite channels, to teach himself. Once he had the basics down, he started creating websites for friends, as well as for the publishing company he worked for at the time. With every site, he’d put his name at the bottom of the page, as a form of marketing. This worked well enough that Hendricks was able to quit his work at the translation company and transition to full-time freelancing. However, eventually the freelancing work dried up, and he decided he wanted to experience working at a tech company—and not just for job security reasons. Hendricks saw finding a full-time development role as the perfect opportunity to push himself and see just how far he could get in his new career. There’s a common trope, probably belonging more to the sports world at large, about the importance of shedding ‘blood, sweat, and tears’ in the pursuit of one’s passion . . . and that’s also how I wanted to cut my teeth in the software engineering world. The job hunt While all four are now successfully employed as developers, Asakura, D’Alberti, Wilson, and Hendricks approached and experienced the job hunt differently. Following is their hard-earned advice on best practices and common mistakes. DO network When Hendricks started his job hunt, he faced the disadvantages of not having any formal experience, and also being both physically and socially isolated from other developers. Since he and his family were living in Nagano, he wasn’t able to participate in most of the tech events and meet-ups available in Tokyo or other big cities. His initial job hunt took around a year, and at one point he was sending so many applications that he received a hundred rejections in a week. It wasn’t until he started connecting with the community that he was able to turn it around, eventually getting three good job offers in a single week. Networking, for me, is what made all the difference. It was through networking that I found my mentors, found community, and joined and even started a few great Discord servers. These all undeniably contributed to me ultimately landing my current job, but they also made me feel welcome in the industry. Hendricks particularly credits his mentors, Ean More and Bob Cousins, for giving him great advice. “My initial mentor [Ean More] I actually met through a mutual IT networking Facebook group. I noticed that he was one of the more active members, and that he was always ready to lend a hand to help others with their questions and spread a deeper understanding of programming and computer science. He also often posted snippets of his own code to share with the community and receive feedback, and I was interested in a lot of what he was posting. “I reached out to him and told him I thought it was amazing how selfless he was in the group, and that, while I’m still a junior, if there was ever any grunt work I could do under his guidance, I would be happy to do so. Since he had a history of mentoring others, he offered to do so for me, and we’ve been mentor/mentee and friends ever since.” “My other mentor [Bob Cousins],” Hendricks continued, “was a friend of my late uncle’s. My uncle had originally begun mentoring me shortly before his passing. We were connected through a mutual friend whom I lamented to about not having any clue how to continue following the path my uncle had originally laid before me. He mentioned that he knew just the right person and gave me an email address to contact. I sent an email to the address and was greeted warmly by the man who would become another mentor, and like an uncle to me.” Although Hendricks found him via a personal connection, Cousins runs a mentorship program that caters to a wide variety of industries. Wilson also believes in the power of networking—and not just for the job hunt. “One of the things I like about programming,” he said, “is that it’s a very collaborative community. Everybody wants to help everybody.” We remember that everyone had to start somewhere, and we’ll take time to help those starting out. It’s a very welcoming community. Just do it! We’re all here for you, and if you need help I’ll refer you. Asakura, by contrast, thinks that networking can help, but that it works a little differently in Japan than in other countries. “Don’t rely on it too much,” he said. “Unlike in Western countries, personal referrals don’t always lead directly to job opportunities in Japan. Your skills, effort, and consistency will matter more in the long run.” DO treat the job hunt like a job Once he’d graduated from Le Wagon, D’Alberti said, “I considered job-hunting my full-time job.” I checked all the possible networking events and meetup events that were going on in the city, and tried to attend all of them, every single day. I had a list of 10 different job boards that I would go and just refresh on a daily basis to see, ‘Okay, Is there anything new now?’ And, of course, I talked with recruiters. D’Alberti suggests beginning the search earlier than you think you need to. “I had started actively job hunting even before graduating [from Le Wagon],” he said. “That’s advice I give to everyone who joins the bootcamp. “Two weeks before graduation, you have one simple web application that you can show. You have a second one you’re working on in a team, and you have a third one that you know what it’s going to be about. So, already, there are three applications that you can showcase or you can use to explain your skills. I started going to meetups and to different events, talking with people, showing my CV.” The process wasn’t easy, as most companies and recruiters weren’t interested in hiring for junior roles. But his intensive strategy paid off within a month, as D’Albert landed three invitations to interview: one from a Japanese job board, one from a recruiter, and one from LinkedIn. For Asakura, treating job hunting like a job was as much for his mental health as for his career. “The biggest challenge was dealing with impostor syndrome and feeling like I didn’t belong because I didn’t have a computer science degree,” he explained. “I also experienced burnout from pushing myself too hard.” To cope, I stuck to a structured routine. I went to the gym daily to decompress, kept a consistent study schedule as if I were working full-time, and continued applying for jobs even when it felt hopeless. At first, Asakura tried to apply to jobs strategically by tracking each application, tailoring his resume, and researching every role. “But after dozens of rejections,” he said, “I eventually switched to applying more broadly and sent out over one hundred applications. I also reached out to friends who were already software engineers and asked for direct referrals, but unfortunately, nothing worked out.” Still, Asakura didn’t give up. He practiced interviews in both English and Japanese with his friends, and stayed in touch with recruiters. Most importantly, he kept developing and adding to his portfolio. DO make use of online resources “What ultimately helped me was staying active and visible,” Asakura said. I consistently updated my GitHub, LInkedIn, and Wantedly profiles. Eventually, I received a message on Wantedly from the CTO of a company who was impressed with my portfolio, and that led to my first developer job.” “If you have the time, certifications can also help validate your knowledge,” Asakura added, “especially in fields like cloud and AI. Some people may not realize this, but the rise of artificial intelligence is closely tied to the growth of cloud computing. Earning certifications such as AWS, Kubernetes, and others can give you a strong foundation and open new opportunities, especially as these technologies continue to evolve.” Hendricks also heavily utilized LinkedIn and similar sites, though in a slightly different way. “I would also emphasize the importance of knowing how to use job-hunting sites like Indeed and LinkedIn,” he said. “I had the best luck when I used them primarily to do initial research into companies, then applied directly through the companies’ own websites, rather than through job postings that filter applicants before their resumés ever make it to the actual people looking to hire.” In addition, Hendricks recommends studying coding interview prep tutorials from freeCodeCamp. Along with advice from his mentors and the online communities he joined, he credits those tutorials with helping him successfully receive offers after a long job hunt. DO highlight experience with Japanese culture and language Asakura felt that his experience in Japan, and knowledge of Japanese, gave him an edge. “I understand Japanese work culture [and] can speak the language,” Asakura said, “and as a Japanese national I didn’t require visa sponsorship. That made me a lower-risk hire for companies here.” Hendricks also felt that his excellent Japanese made him a more attractive hire. While applying, he emphasized to companies that he could be a bridge to the global market and business overseas. However, he also admitted this strategy steered him towards applying with more domestic Japanese companies, which were also less likely to hire someone without a computer science degree. “So,” he said, “it sort of washed out.” Wilson is another who put a lot of emphasis on his Japanese language skills, from a slightly different angle. A lot of interviewees typically don’t speak Japanese well . . . and a lot of companies here say that they’re very international, but if they want very good programmers, [those people] spend their lives programming, not studying English. So having somebody who can bridge the language gap on the IT side can be helpful. DO lean into your other experience Several career switchers discovered that their past experiences and skills, while not immediately relevant to their new career, still proved quite helpful in landing that first role—sometimes in very unexpected ways. When Wilson was pitching his language skills to companies, he wasn’t talking about just Japanese–English translation. He also highlighted his prior experience in sales to suggest that he could help communicate with and educate non-technical audiences. “Actually to be a software engineer, there’s a lot of technical communication you have to do.” I have worked with some incredible coders who are so good at the technical side and just don’t want to do the personal side. But for those of us who are not super-geniuses and can’t rely purely on our tech skills . . . there’s a lot of non-technical discussion that goes around building a product.” This strategy, while eventually fruitful, didn’t earn Wilson a job right away. Initially, he applied to more than sixty companies over the course of three to four months. “I didn’t have any professional [coding] experience, so it was actually quite a rough time,” he said. “I interviewed all over the place. I was getting rejected all over town.” The good news was, Wilson said, “I’m from Chicago. I don’t know what it is, but there are a lot of Chicagoans who work in Tokyo for whatever reason.” When he finally landed an interview, one of the three founders of the company was also from Chicago, giving them something in common. “We hit it off really well in the interview. I think that kind of gave me the edge to get the role, to be honest.” Like Wilson, D’Alberti found that his previous work as a marketer helped him secure his first developer role—which was ironic, he felt, given that he’d partially chosen to switch careers because he hadn’t been able to find an English-language marketing job in Japan. “I had my first interview with the CEO,” he told me, “and this was for a Japanese startup that was building chatbots, and they wanted to expand into the English market. So I talked with the CEO, and he was very excited to get to know me and sent me to talk with the CTO.” The CTO, unfortunately, wasn’t interested in hiring a junior developer with no professional experience. “And I thought that was the end of it. But then I got called again by the CEO. I wanted to join for the engineering position, and he wanted to have me for my marketing experience.” In the end we agreed that I would join in a 50-50 arrangement. I would do 50 percent of my job in marketing and going to conferences and talking to people, and 50 percent on the engineering side. I was like, ‘Okay, I’ll take that.’ This ended up working better than D’Alberti had expected, partially due to external circumstances. “When COVID came, we couldn’t travel abroad, so most of the job I was doing in my marketing role I couldn’t perform anymore. “So they sat me down and [said], ‘What are we going to do with you, since we cannot use you for marketing anymore?’ And I was like, ‘Well, I’m still a software developer. I could continue working in that role.’ And that actually allowed me to fully transition.” DON’T make these mistakes It was D’Alberti’s willingness to compromise on that first development role that led to his later success, so he would explicitly encourage other career-changers to avoid, in his own words, “being too picky.” This advice is based, not just on his own experience, but also on his time working as a teaching assistant at Le Wagon. “There were a couple of people who would be like, ‘Yeah, I’d really like to find a job and I’m not getting any interviews,’” he explained. “And then we’d go and ask, ‘Okay, how many companies are you applying to? What are you doing?’ But [they’d say] ‘No, see, [this company] doesn’t offer enough’ or ‘I don’t really like this company’ or ‘I’d like to do something else.’ Those who would be really picky or wouldn’t put in the effort, they wouldn’t land a job. Those who were deadly serious about ‘I need to get a job as a software developer,’ they’d find one. It might not be a great job, it might not be at a good company, but it would be a good first start from which to move on afterwards. Asakura also knew some other bootcamp graduates who struggled to find work. “A major reason was a lack of Japanese language skills,” he said. Even for junior roles, many companies in Japan require at least conversational Japanese, especially domestic ones. On the other hand, if you prioritize learning Japanese, that can give you an edge on entering the industry: “Many local companies are open to training junior developers, as long as they see your motivation and you can communicate effectively. International companies, on the other hand, often have stricter technical requirements and may pass on candidates without degrees or prior experience.” Finally, Hendricks said that during his own job hunt, “Not living in Tokyo was a problem.” It was something that he was able to overcome via diligent digital networking, but he’d encourage career-changers to think seriously about their future job prospects before settling outside a major metropolis in Japan. Their top advice I asked each developer to share their number one piece of advice for career-changers. D’Alberti wasn’t quite sure what to suggest, given recent changes in the tech market overall. “I don’t have clear advice to someone who’s trying to break into tech right now,” he said. “It might be good to wait and see what happens with the AI path. Might be good to actually learn how to code using AI, if that’s going to be the way to distinguish yourself from other junior developers. It might be to just abandon the idea of [being] a linear software developer in the traditional sense, and maybe look more into data science, if there are more opportunities.” But assuming they still decide ‘Yes, I want to join, I love the idea of being a software developer and I want to go forward’ . . . my main suggestion is patience. “It’s going to be tough,” he added. By contrast, Hendricks and Wilson had the same suggestion: if you want to change careers, then go for it, full speed ahead. “Do it now, or as soon as you possibly can,” Hendricks stated adamantly. His life has been so positively altered by discovering and pursuing his passion, that his only regret is he didn’t do it sooner. Wilson said something strikingly similar. “Do it. Just do it. I went back and forth a lot,” he explained. “‘Oh, should I do this, it’s so much money, I already have a job’ . . . just rip the bandaid off. Just do it. You probably have a good reason.” He pointed out that while starting over and looking for work is scary, it’s also possible that you’ll lose your current job anyway, at which point you’ll still be job hunting but in an industry you no longer even enjoy. “If you keep at it,” he said, “you can probably do it.” “Not to talk down to developers,” he added, “but it’s not the hardest job in the world. You have to study and learn and be the kind of person who wants to sit at the computer and write code, but if you’re thinking about it, you’re probably the kind of person who can do it, and that also means you can probably weather the awful six months of job hunting.” You only need to pass one job interview. You only need to get your foot in the door. Asakura agreed with “just do it,” but with a twist. “Build in public,” he suggested. “Share your progress. Post on GitHub. Keep your LinkedIn active.” Let people see your journey, because even small wins build momentum and credibility. “To anyone learning to code right now,” Asakura added, “don’t get discouraged by setbacks or rejections. Focus on building, learning, and showing up every day. Your portfolio speaks louder than your past, and consistency will eventually open the door.” If you want to read more how-tos and success stories around networking, working with recruitment agencies, writing your resume, etc., check out TokyoDev’s other articles. If you’d like to hear more about being a developer in Japan, we invite you to join the TokyoDev Discord, which has over 6,000 members as well as dedicated channels for resume review, job posts, life in Japan, and more.
