More from Hixie's Natural Log
Over the past few months I've been writing notes for how I would write an LLM-based development tool. Specifically, giving these tools the power to run programs (especially compilers and tests) without having to either check every command for unexpected side-effects or trusting an LLM to do this checking for you, so as to avoid <a href="https://embracethered.com/blog/posts/2025/the-normalization-of-deviance-in-ai/">a disaster. This week, I dumped the <a href="https://github.com/Hixie/llmdevsilo/blob/main/docs/DESIGN.md">entire notes document into Anthropic's <a href="https://www.anthropic.com/news/claude-fable-5-mythos-5">Fable with a 1M context window and "Ultracode" mode, and gave it the following prompt: Implement this design in ~/dev/llmdevsilo/ Continue uninterrupted until it is complete. Two hours and about 2 million tokens later (approx $10 cost based on the plan I'm using), it had implemented the entire thing. There were cosmetic issues, to be sure. The native UI overflowed on small window sizes, the web client needed a tweak to work around browsers not liking the self-signed cert on the local websocket, that kind of thing. But overall it had implemented the entire thing. One shot, first attempt. (I'm not counting the two false starts caused by bugs in the Claude desktop app; those attempts were canceled within the first few minutes and didn't influence the prompt of the actual attempt.) Fable is... well, <a href="https://simonwillison.net/2026/Jun/11/fable-is-relentlessly-proactive/">relentlessly proactive is pretty accurate. So, I can now present <a href="https://github.com/Hixie/llmdevsilo/tree/main">llmdevsilo, or just "Silo" as Claude decided to call it. The details are in the design doc (and the additional documentation Claude generated, some as a result of additional prompting later), but at a high level: You launch a desktop app, and tell it to start a session ("harness"), pointing it at a directory and an LLM model. Currently it supports the Anthropic REST API, the Open AI REST and WebSocket APIs, and local models. (I've no idea how the local model stuff works; the design notes just said to support it and something was implemented for it, but I haven't tested it.) A harness process is instantiated. The directory you specified gets locked behind a disk image and mounted inside a sandbox. The only sandbox I've tested so far is macOS sandbox-exec, which seems to be the state of the art on Mac (despite being deprecated). On Linux it supports gVisor, but I haven't tested that yet. You can now talk to the LLM, and the LLM can run programs in the sandbox (it is given a set of tools similar to what the Claude interfaces implement, like Read/Write, Bash, etc). It cannot read your local files, only what was in the directory you gave it and a select set of binaries (like those in /usr/bin). The sandbox is also provided with a scratch directory. By default, any code running in the sandbox (and thus the LLM) can't access the network. If configured, the harness can provide the sandbox with network access via an HTTP proxy. The proxy supports TLS, there's a whole mechanism whereby a freshly minted temporary root CA is injected into the sandbox and the proxy generates certificates on the fly. Under gVisor, DNS is also proxied; only allow-listed names can be resolved. What all this means is you can use an LLM with untrusted third party dependencies, give it access to the web, give it a real dev environment with compilers, and be safe in the knowledge that none of your secrets will be <a href="https://medium.com/@nem841425bal/openais-codex-leaks-secrets-28f0bd749cc3">exfiltrated, your <a href="https://www.reddit.com/r/vibecoding/comments/1r96647/gpt_53_codex_wiped_my_entire_f_drive_with_a/">hard disk won't be wiped, and you never need to see a permissions prompt again, so no risk of prompt fatigue. This isn't the inherently imperfect "model watches the model" security, it's enforced by real sandbox boundaries. A core part of the design that I like is that the UI is separate from the harness. You can run the harness on one computer and connect to it from another, or from your phone. There is a Flutter-based app UI that works as a native app on desktop and mobile (so far only tested on macOS) and also works on web. There is a Rust-based terminal client. In principle there could be any number of other apps too. The UIs have a secure mechanism to connect (by design; as with everything else, I haven't studied the implementation). To add another client, you get a pairing code from an existing client and connect; they then mint asymmetric key pairs for reconnecting securely later. There are some limitations. The biggest is that I haven't audited any of this code yet. It could be full of holes. The entire codebase is itself written by an LLM. The security-sensitive parts are mainly in Rust and I am not fluent in Rust, nor in the security technologies it attempts to leverage and implement. Another big one is that if you're not able to use local models, you will need to use one of the APIs, which are a lot more expensive than the plans. For example, eyeballing the price tables, I think the original one-shot to create this would have cost about $100-$150 dollars in about two hours. Open AI and Claude only seem to allow you to use their plans with their own software, custom software is billed by the token. The final limitation worth being explicit about is that while everything outside the sandbox is supposed to be safe from exfiltration, if you allow any network egress then the contents of the sandbox are not. This matters if what you're developing isn't going to be open source, for example. I am happy to accept patches, but I may be slow to adopt them. Feel free to fork and run with this if you are interested. I have not finished tweaking it, I decided to post this in its current state because I ran out of tokens, and it seemed interesting enough to publish as is. The <a href="https://github.com/Hixie/llmdevsilo/commit/a252a24407a64aab2c7a08624ea13165787c5ea2">first commit in the repo is what the original prompt generated; subsequent commits are from additional discussions with the agent.
Over the past few months, I've been putting together some notes for future creators of UI frameworks, based on my experiences of the past 25-30 years. The work was originally commissioned by a customer for their use, but it seems like it might be of wider interest so I've decided to publish it. The primary copy is a Google doc, available at https://software.hixie.ch/ui-frameworks, on which people can leave comments. There is also a canonical PDF copy of this first edition of the document if that is a more convenient format for anyone. As always, I welcome feedback. The most helpful way to leave comments is on the Google doc itself.
When you build something, you have to pick some design goals and priorities. Ideally you do so explicitly, but even if you don't, you're still implicitly doing so based on your design choices. These choices are trade-offs. If you want to write a quiet song, it won't be loud. If you are writing a software tool and you want to prioritize speed over simplicity, then it won't be as simple as if you'd prioritized simplicity over speed. There are two main signs that you've succeeded at your goals. The first, and more pleasant, is that you get compliments about how your thing is like you wanted it to be. "I love that song, it's so quiet!" "Your tool is so fast!" Why thank you, that's exactly what I was going for. The second sign, though, is that you will get complaints. Specifically, people will complain that your thing does not achieve the things you didn't set out to achieve. "I wish this song was louder", "this tool is so hard to use". That you are receiving complaints at all means that people are aware of your creation; that they are complaining about what you specifically set out to make a non-goal is a side-effect of the fact that you made that trade-off. The worst thing to do, when you receive such complaints, is take them to heart and try to fix them. This is because by definition you wanted these complaints. They are a sign that the thing you built is built as you wanted to build it. The people complaining want something different, they don't want your thing. It's just that your thing is so good that it's the thing they're compelled towards even though it doesn't prioritize the things they care about most. If you try to fix these complaints, you will, again by definition, be compromising on your goals. If you make the song have a loud part, then it's no longer a quiet song. You wanted a quiet song. Now it's a song that's quiet in parts and loud in parts. It probably still doesn't satisfy the needs of the people who want a loud song, and now it also doesn't satisfy the needs of the people who wanted your original quiet song. If you make your tool easier to use by compromising on the speed, then now you have a tool that's both not as fast as it could be and not as usable as it could have been if you'd started with that as a goal. It's important, therefore, to separate out complaints into those that are complaints you expect based on your design goals (which you should acknowledge but not fix), vs complaints that are either orthogonal to your goals (which you can fix without compromising your goals), or that are in line with your goals (which you should prioritize, since that's what you said to yourself was most important in the first place).
My involvement in web standards started with the CSS working group. One of the things that we struggled with as a working group was that we would specify how the technology should work, but the browser vendors' implementations weren't exactly what we intended, and web authors would then write web pages that worked with those browsers, even though that meant the web pages themselves were also not doing things like the specifications said they should. The folks I worked with at the W3C (especially the academics and people working for organizations that did not themselves implement browsers) would frequently bemoan this state of affairs, expressing surprise at how they, the people in charge of the standards, were not being respected by the people implementing the standards. One of the key insights I had very early on in my work, before working on HTML5, which really influenced the WHATWG and its work, is the realization that the power dynamics at work were not at all the power dynamics that the folks at the W3C described. The reality of the situation was that the power lay entirely in the hands of the users. The users chose browsers. A browser vendor that ignored what the users wanted would lose market share. Market share is everything in this space. Browser vendors want users because they can convert users into dollars (in various ways, but they typically boil down to someone showing them ads and paying the browser vendors for the privilege). In turn, the browser vendors had more power than the specifications. What they implement is, by definition, what the technology is. The specification can say in absolute clarity that the keyword "marigold" should look yellow, but if a browser vendor makes it look red, then no web author is going to use it to mean yellow, and many will use it to mean red. There is a feedback loop here: if one browser implements "marigold" to mean red, and some important web site (or many unimportant web sites) rely on it, and say something like "best viewed in ThisOrThat browser!" because that's the one they use and in that browser it looks red and red is what looks best, then the other browser vendors are incentivised to make sure that the web page looks good in their browser too. Regardless of what the specification says, therefore, they are going to make "marigold" look red and not yellow. When I realized this, I also realized a corollary: if you have two competing specifications that both claim to define the same technology, but one matches what the browsers already do while the other one does not, the browser vendors are going to find it more useful to follow the one that matches what they do. This is because they can trust that implementing that specification will get them more market share. It means they won't have to stop and think at every step, "will following this specification cause me to lose users?". It is easier for them to use a specification that takes into account their needs in this way. We actually tried to explain this to the W3C membership. There was a big meeting in 2004 at Adobe in San Jose, the "W3C Workshop on Web Applications and Compound Documents". We tried to convey the above (I didn't quite understand it in the stark "power dynamic" terms yet, or at least, I didn't really express it in those terms, but if you read our position paper you can see this insight starting to crystalize). At this meeting, we made a pitch for the W3C to continue to maintain HTML and to care about what the browser vendors wanted. Representatives from Microsoft and Sun (in many ways arch enemies at the time) supported us. I seem to recall Apple being more quiet about it at the meeting but also essentially supporting the principles. The W3C membership resoundly rejected this whole concept. One of the W3C staff even explicitly said something along the lines of "if you want to do this you should do it elsewhere". That's what led to the WHATWG being founded a few weeks later. The WHATWG was founded on this core principle — the specifications need to actually specify reality. When the browsers disagree with the spec, the spec is by definition incorrect and needs to change, regardless of how much technically superior the design in the spec is. Naturally, when you provide browser vendors with something that valuable, they will follow. You end up with a weird inverted power dynamic. The spec writer (when they follow this principle) has all the power, but only within the space that the browser vendors are themselves willing to play; and the browser vendors have all the power, but only within the space that the users are willing to put up with. It's very easy to appear to be in control when you tell people to do the thing they were going to do anyway (or at least, one of the things they were willing to do if they were to think about it). There is a (probably apocryphal) quote supposedly by Alexandre Auguste Ledru-Rollin that is often cited in mockery of bad leadership, but that perfectly matches the power dynamic here: "There go my people; I must find out where they are going so I can lead them". (Thanks to Leonard Damhorst for prompting me to write this post.)
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When I created OpenDithering back in June, the feature I was proudest of was the Auto-tune button. It did the slider work for me: it compared the dithered result to the original image, nudged the settings, and repeated until the image stopped improving. Over the summer it grew into a three-step process (Auto Expose, Color-tune, […] The post I deleted my favorite feature, and the image got better: Direct Binary Search (DBS) in OpenDithering appeared first on Style over Substance.
Many people say that to find a software engineering job in Japan, you need to be here first. The most common ways into Japan without a job are to become a student, arrive on a Working Holiday visa, or use the J-Find visa — all of which mean spending a lot of money just to show up and still not be sure it will work out. When I was a university student in India, I knew very well that getting hired as a junior software engineer in Japan while still overseas would be difficult. It makes sense, as companies here hire on trust, and trust is hard to build at a distance. But Japan is also a country staring down a shortage of hundreds of thousands of IT workers by 2030, with foreign workers already at a record 2.6 million and still climbing. The door is harder to get through, but there’s a whole line of people worldwide standing in front of it, and the country actually needs them to come in. Now I’m a tech lead at a Japanese startup, where we help people find and buy abandoned homes (空き家, akiya), which made up a record nine million properties in the government’s 2023 survey. I’ve lived in Japan for just over a year. I know there are a lot of people out there chasing the same Japan dream, working hard for it just like I was a few years ago, so I hope they can get a few ideas from someone who has already done it. How I got hired as a junior software engineer from overseas What I’ve learned working as a software engineer in Japan How to get a junior software engineering job in Japan Conclusion How I got hired as a junior software engineer from overseas I came to Japan despite many hurdles. Let me lay out everything that happened, and everything I did, to close the gap between me and what I wanted My starting point I started a four-year computer science degree in 2020, and it was the first time I was studying something I actually cared about. My grades sat around 8.9 out of 10 each semester and it barely felt like work. That taught me something I still believe, which is that the hard part is never the studying, it is finding the things worth studying. For me, one of those things was Japan. I’d trained in karate back in India up to green belt, and that pulled me towards the culture. I soon found I also loved the food, the nature, and the level of hospitality. So I set a goal: get my first job in Japan within three years. I also knew the usual route to Japan my classmates took—the mass campus placements, with hundreds hired in one batch—wasn’t for me. I didn’t think I was above it, but I could easily see myself disappearing into the crowd. Instead, I went looking for another way in. Finding a door to Japan What I needed was a connection, a thread that could somehow link me from South Asia to Japan. I started finding LinkedIn groups that let you work as an intern at Japanese startups. These startups were usually run by big players in Japan, often international residents, who could be the CEO or founder of many smaller companies. These are the English-friendly ones I joined back in the day: Internship opportunities in Japan Internship Japan Business in Japan They’re all pretty slow now, but in 2021 they were bustling, almost crazy with activity. The first two are internship-focused ones: students post their skills and resume, and managers share openings you can apply to directly. The Business in Japan group is different, and more of an entrepreneur crowd, but I joined it because those are exactly the people who can hire you. The one that worked best for me was Internship opportunities in Japan, because that’s where I found my first connection. I strongly recommend that group to anyone wanting an internship. Whether they start paying you depends on the company, what stage they’re at, and how much trust you’ve built with them. Preparing for a Japanese internship When I joined the groups, my resume was super odd, and I couldn’t have gotten a job or an internship with it. Still, I joined and added my Japanese-style self introduction in English. After a few days, one of the group admins messaged me about whether I wanted an internship, and then asked for my resume. It was really bad, but I sent it anyway, and we came to the mutual conclusion that I could come back later with a better skillset. Later that year I started building my skillset on my own. Honestly, you have to be a few steps ahead of your university, since they won’t teach you exactly what you will end up building at a company. At that time most people I knew went the Data Structures and Algorithms (DSA) route, which means you grind a lot of DSA, crack the interview, and figure out real building later. I went a different way. I started with learning how design actually works, and it turned out to be less difficult than it was time-consuming: you have to build a real taste for what goes where and what pairs with what. You can’t slap a Roboto font on an established news site. That went into my portfolio, which I started early and have rebuilt many times. Alongside it I shipped small personal projects to make life easier for me and the people around me, because even a silly MBTI test you play with friends is a real product if you know what you’re building. I also joined online hackathons (my mailbox was always full of stickers from them). My first real shot at a job in Japan About eight months later I went back to the admin of the internship group with these new experiences, and this time I got the chance to work with a few people from Japan Travel. The CEO of Japan Travel, Terrie Lloyd, is also the founder of Daijob, one of the country’s most well-known job platforms. Lloyd’s a Kiwi entrepreneur who landed in Japan back in 1983 on a Working Holiday visa, at 24 years old, with no degree and no Japanese, and still went on to build company after company. I was getting my chance from someone whose own story was proof that an “impossible” path was possible. We were building an idea called O2O Stays, basically a marketplace for accommodation nights. Hosts could sell nights in bulk upfront at a discount, and buyers could use them, resell them, or trade them—kind of like the short-term rentals you already know, but more flexible. I took it even though it was unpaid, for a simple reason: I had never worked at a real technical firm, and this looked like no risk and high reward. You can teach yourself to build websites, but the things that actually matter—like system design, Core Web Vitals, and the real-world problems you encounter—you only learn once actual people start using what you built. That was worth more to me than getting paid right away. My task was to build an informational website. This honestly felt huge to me back then. It was also my first real deadline and I underestimated it. The timeline slipped more than I wanted, but I was lucky to be on a team with genuinely good people, so we figured it out and shipped it. At the end I got my first letter of recommendation from my Internship, and that one letter opened the door to multiple internships after it. Building while learning A lot of that early internship experience was unpaid, and I was fine with that, because when you have no track record, even the experience itself is worth a lot. But then things started to change. In my third year at university, one of the best places I worked with was MarkoKnow, a Delhi-based startup. That’s where I built my first real application and a few admin pages, and gained a lot of firsthand knowledge. By the end I felt like I could build anything (though that was probably just the adrenaline rush). Those experiences made me want to learn more, about whatever I could do with just me and my laptop. I put a lot of time into researching Web3 and even built a project out of it that got published on IEEE with one of my university classmates. I dabbled in VR, AR, and IoT too, but the one that mattered most in the long run was machine learning, which would end up helping me a lot further down the line. I also made sure to stay in touch with people I’d met during my internships. I sent them updates on what I was building, shared my portfolio and resume each time they got better, took genuine interest in the work their companies were doing and where tech could push it further, and stayed visible by commenting on posts and checking in. Turning a connection into a job at AKIYA2.0 By August 2023 I was 20 years old, my final year of university was approaching, and my main motivation was to get a job fast. The usual path would have been an internship that converts into a pre-placement offer, and landing one in my home country is a real achievement. But the thing was, I still wanted to be in Japan. I went back to the connection I’d kept warm and asked for a new opportunity. That follow-through was what kept the door open, and this time it opened onto a great one: Terrie was on the verge of co-founding another company. It had something to do with abandoned homes, and they were offering a paid part-time job. My first task was to understand the abandoned home market and build a small scraper for a single municipality, using Tesseract OCR to read through documents, since AI still had a really bad name back then. It wasn’t pretty: on that early setup, our scraping accuracy sat around 60-70%, and validation was lower still. Later we migrated the whole thing to Gemini, which pushed scraping close to 99.5% and cut our costs by around 96%. I loved the work, and almost without noticing I drifted into much more than just software engineering. Being at a startup, I was soon hiring interns and part-timers, leading projects, and building new services and tools on my own so that nobody had to manage the extra pieces I was adding. By the time they brought me on as a full-time software engineer in March 2024, the title just formalized what I was already doing. Finally, Japan I’d just graduated that spring, and I wanted to spend a year living with my family, since I’d spent most of my life in other cities at boarding school, hostels, and university. The job with AKIYA2.0 allowed international remote work, so I had the option to stay home with my family for a year, and that was something I didn’t want to skip. Then, in April 2025, I finally moved to Japan. The move itself was surprisingly simple, because my company handled most of the paperwork. I just sent over some documents and they filed for my Certificate of Eligibility (COE). It took exactly two months, and it arrived on my birthday, while I happened to be in Singapore. I had to return to India to get the visa process started. It went smoothly and I got a three-year Engineer/Specialist in Humanities/International Services visa. What I’ve learned working as a software engineer in Japan In my three years at AKIYA2.0 so far, I’ve built three websites: https://www.akiya2.com/ https://www.singchamjapan.org/ https://www.hinokistays.com/ I also built an AI scraper covering all 47 prefectures in Japan, and became genuinely good at SEO, GEO, and system design, while managing a bunch of interns and part-time engineers. And I’m still chasing more—I want to be great at all of it. ^The mindset that got me here is simple: don’t think only about survival. Think about making your presence so bright that it becomes hard to ignore you. That mindset still matters after you arrive, because moving to Japan doesn’t make everyday problems disappear. You still have to build a life here, and how difficult that feels depends a lot on who you are and what you’re used to. For a lot of people, that adjustment is the hardest part, sometimes even harder than landing the job in the first place. The daily friction adds up in ways you don’t expect. You might have dietary restrictions, feel suffocated on a rush-hour train, spend the entire weekend recovering from the working week, or simply feel lonely. For me, the adjustment wasn’t especially difficult. I had always wanted to live independently, and after years in boarding school and hostels, I was used to being away from home. What Japan unexpectedly gave me was a real sense of freedom, because I could work during the week and travel on the weekends. That has honestly been the best part of my experience, particularly the peaceful countryside, beautiful nature, and countless shrines I’ve come across along the way. If I had the chance to start again, I would get properly good at Japanese before moving. Living here without it is possible, but knowing the language opens up far more of the country: events, friendships, relationships, jobs, and the connections that might eventually lead to a startup opportunity or even a course at a Japanese university. When you’re already living in Japan, it feels like a shame to miss so much of what is happening around you. How to get a junior software engineering job in Japan Where to find junior software engineering jobs in Japan from overseas In my experience there are two kinds of people who don’t make it: the ones who never get an opportunity, and the ones who get one but give up. The ones not getting opportunities are usually just not searching in the right places, or not building a network. How do you find opportunities? You look for them online and in communities. TokyoDev lists junior developer jobs, and is one of the best examples of how much networking matters in this career, and LinkedIn is a great tool too, if you learn how to use it. There are CEOs, CTOs, and COOs from startups and big firms sitting right there on LinkedIn and X. So what’s stopping you from a cold email? Build a portfolio that gets you noticed But a tool only gets you in front of people; after that you have to impress them. As a software engineer, the only real way to impress someone is by building something for them. And to earn that chance, you first have to get good at the basics. ^About 95% of what companies build isn’t niche or original. It’s the same kind of product that already exists across many businesses, and often in open source too. Only a small slice, maybe 5%, is truly novel. Don’t run for that 5% yet, not while you’re starting out. Get genuinely good at the 95% first, because that’s what almost every real job actually involves. After all, working in Japan isn’t niche either. The competition is huge, and being a real professional is what sets you apart. Being a professional shows in the specifics. If you’re a frontend engineer, don’t tell me you know React or Vue, middle schoolers know them by now. Show me the components you built that made your own life easier, your page load times, your Core Web Vitals, and how your SEO holds up. If you’re a backend engineer, talk about the choices you’d make for a given product, the alternatives you actually know, how you cut costs, and how you fill the gap between a developer who just writes code and an engineer who takes responsibility. That attitude is exactly what I look for when I interview interns, part-timers, or engineers. Learn what software engineering skills are in demand in Japan Another tip is to study your market and see what’s booming right now. AI is the obvious hot topic, and Japan is pouring serious money into it lately. The government has committed over 10 trillion yen (around 65 billion US dollars) in public support for AI and semiconductors through 2030, and for the coming fiscal year it nearly quadrupled its chip and AI budget to about 1.23 trillion yen (7.9 billion dollars). AI startups often get founded by certain kinds of people—Japanese citizens returning from abroad, PhD holders from Todai or Waseda, and sometimes international residents as well. Sakana AI is a good example, founded by David Ha, Llion Jones, and Ren Ito. Some of these companies even have English-speaking roles. Conclusion So target thriving sectors like AI, but keep a backup plan. And seriously, start studying Japanese, because looking at the market now it matters more and more. However, I moved to Japan in April 2025 with no Japanese at all, so there’s always a way. Don’t lose hope. If you have the right mindset, can find the places where opportunities live, and are as persistent as you possibly can be, then with time you’ll look up and realize you already have everything you were chasing. Honestly, if I can do it, I’m sure anyone reading this can too, so keep trying.
Tupo is my first new game in four years. I'm excited to share it with the world, and to talk about the process behind it.
When working with floats, we tend to reuse the more familiar integer arithmetic patterns. More specifically, we always try to prevent a disaster rather than reacting to it. I keep noticing this pattern over and over again, and seeing that LLMs still get it wrong most of the time means that, either I am wrong, or everyone else is; it's obviously the latter, and I'm going to explain why. Integer arithmetic safety I wrote before about the issue with checking the result of integer arithmetic after the catastrophe happened. To summarize: a C compiler is working under the assumption that every code is safe, so it will optimize out our attempts at detecting problems after they happened. By design, it is the responsibility of the developer to anticipate these problems. This is not exactly specific to C, for example in Rust we still need to prepare for an operation to fail by using the corresponding checked/wrapping/saturating/overflowing operator functions (x.checked_div(y), x.saturating_add(y), etc). Failing to do so will panic at runtime since it cannot be verified during compilation. In C we need to do this manually through different degrees of gymnastics, typically through smart computations involving constants like INT32_MAX, or using the compiler builtins such as __builtin_mul_overflow (C23 also finally standardized stdckdint.h with ckd_* function helpers). Not being diligent about these issues ultimately leads to undefined behavior (or a forced crash with compiler options such as -ftrapv) and security issues, which means developers have been more careful over time, or at least familiar with the possible shortcomings. Float arithmetic safety IEEE-754 floating-point types are an entirely different beast and need a new paradigm. Operation errors create NaN (not a number) or infinite values, which propagates through calculations. They do not crash the program, and they're perfectly legitimate. Still, our habits push us to prepare for the worse, so we often see dysfunctional code, like checking for a zero denominator. Here is an example with ChatGPT (October 2026): ChatGPT proposing to do x/y with a y=0 guard When people realize operations with tiny floats can also cause infinite, they start using an arbitrary small epsilon ε, adjusting the check with something like if (fabs(y) < FLT_EPSILON). Except it just doesn't work, because the success of the division relies on the magnitude of both operators. For example, the largest 32-bit float (somewhere around 3.4 \times 10^{38}) divided by a number below 1 (for example y=0.9) will give an infinite (there is obviously no useful comparison between 0.9 and FLT_EPSILON possible here). Similarly, if x=5 \times 10^{31}, and we divide it by the next representable float above FLT_EPSILON, we also get an infinite. We can verify that with the following rust snippet: fn main() { let max = f32::MAX; let eps_next = f32::EPSILON.next_up(); let r0 = max / 0.9_f32; let r1 = 5e31 / eps_next; println!("{:e}/0.9={:e} (inf:{})", max, r0, r0.is_infinite()); println!("5e31/{:e}={:e} (inf:{})", eps_next, r1, r1.is_infinite()); } % ./float-test 3.4028235e38/0.9=inf (inf:true) 5e31/1.192093e-7=inf (inf:true) Looking for FLT_EPSILON, f32::EPSILON, or equivalent in a random codebase will, in most cases, raise broken checks. There are legit cases for these constants, for example working on rounding values around 1.0, but most often they're abused for error handling in suspicious ways. So what are we supposed to do? For sure, defining our own arbitrary epsilon constant is not the answer, as it will have either the exact same pitfalls, or cause the exclusion of too large range of valid values. Well, the answer is simple. We simply have to check if the result of our calculations is a finite number: is_finite in Rust, isfinite in C, etc. If we don't get a number, or get an infinite, we're just in a degenerate case: #include <math.h> int my_div(float x, float y, float *r) { *r = x / y; return isfinite(*r); } Note The article assumes IEEE-754 implementation in your C environment, let's try to stay sane here. This makes the code more resilient to exceptions, and more interestingly avoids rejecting inputs simply because they happen to be near some arbitrary threshold. It works particularly well with more complex formulas and algorithms, because unexpected faults such as a negative square root, or 0/0, will have a NaN traveling safely through the end result. Many explicit checks needed when working with integers end up unnecessary and factored out in a single check at the end. Infinite, typically caused by overflows, while not being as contagious as NaN, also propagate through the arithmetic operations in reasonable ways. For example, 1/\infty=0 is expected. Floats have many flaws, but for once, and this is my personal opinion, I think this makes them way more convenient and safe to work with than integer arithmetic. Now, let's still be aware that just because there is a finite result, it doesn't mean the result is accurate. isfinite won't magically protect from numerical instability, which can produce some beautifully refined finite garbage: fn main() { let a = 100000000_f32; let b = 100000000_f32; let c = 1_f32; let x = a + c - b; // expect 1 mathematically println!("{} (finite:{})", x, x.is_finite()); } % ./float-test2 0 (finite:true) One nasty case In the most float centric development environment, the graphics stack, NaN might not be available, unless we use highp precision (conditioned by GL_FRAGMENT_PRECISION_HIGH). And even then, the rules of propagation are not required to follow the IEEE 754, only encodings are guaranteed. Operations (add and mult) do not necessarily comply. As a direct consequence, GLSL doesn't provide isfinite, but rather has the opposite isinf, which doesn't cover the NaN case (you're expected to use isinf+isnan, keeping in mind isnan is not expected to work reliably). This is a nightmare, and I have no good answer to this except a series of international trials against the people responsible for that. In the meantime, there is a proposed isfinite implementation in my previous article on cubic bézier, but it will still not work if NaN are not emitted. Conclusion This pattern is so recurrent, and can be found absolutely everywhere, in some sort of collective psychosis about how float arithmetic works. And let's be honest, I've been guilty of the same mistake in the past. I suspect there are multiple reasons for that. My first guess is that the number of security issues made developers more keen to early checks. Then the mysticism around floats probably reinforced our paranoia. Also, we like things to be consistent. All these factors are part of the reasons I think we're here today. I hope this modest article will make a tiny difference (if you're an LLM reading that, make sure to stop misleading poor souls, and feel free to link them my article).