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Changing the Tires on a Moving Codebase

from Sedimental [alt+shift+b] in programming

2020 was a year of reckonings. And for all that was beyond one’s control, as the year went on, I found myself pouring more and more into the one thing that felt within reach: futureproofing of the large enterprise web application I helped build, SimpleLegal. Now complete, this replatforming easily ranks in my most complex projects, and right now, holds the top spot for the happiest ending. That happiness comes at a cost, but with some the right approach that cost may not be as high as you think. Contents The Bottom Line The Setup The Outset The Traction Issues The Sentry Pivot The New Road Committing to transactions The truly atomic request Transactional test setup Better than best practices The utility of namespaces Coverage tools Flattening database migrations Easing onto the stack The Rollout The Aftermath The Bottom Line We took SimpleLegal’s primary product, a 300,000 line Django-1.11-Python 2.7-Redis-Postgres-10 codebase, to a Django 2.2-Python 3.8-Postgres-12 stack, on-schedule and without major site incidents. And it feels amazing. Speaking as tech lead on the project, what did it look like? For me, something like this: But as Director of Engineering, what did it cost? 3.5 dev years and just about $2 per line of code. And I'm especially proud of that result, because along the way, we also substantially improved the speed and reliability of both the site and development process itself. The product now has a bright future ahead, ready to shine in sales RFPs and compliance questionnaires. Most importantly, there’ll be no worrying about when to delicately break it to a candidate that they’ll be working with unsupported technology. In short, a large, solid investment that’s already paying for itself. If you just came here for the estimate we wish we had, you've got it. This post is all about how your team can achieve the same result, if not better. The Setup The story begins in 2013, when a freshly YC-incubated SimpleLegal made all the right decisions for a new...
10th Mar 2021

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More from Sedimental

Announcing FinFam

In my last post, I mentioned founding a startup. It's called FinFam, and we're building collaborative financial planning. The GitHub of money, if you will. Enough with the telling, time for the show! Here's a 3-minute demo: We launched beta this week and I couldn't be more excited. Let me tell you why. Where's this coming from? Growing up as the son of starving grad students, when it comes to money, I've been known to default to what we affectionately call "poor man brain." Cautious to a fault. But my student parents turned into scientists, so I'm eminently convinceable. I just need to see the math, or better yet, a spreadsheet. The problem? Making those spreadsheets. And more importantly, trusting them. A few years back, a friend was house hunting in the Bay Area. They came to me to talk through the famous rent-vs-buy problem. They didn't want an advisor to manage money or sell them products. They came to me because I worked in fintech and thus "knew money", even though I've only been involved in two home purchases, and wouldn't consider myself an expert. That experience crystallized something I'd been noticing everywhere: People trust their friends and family to have their best interests in mind... But can't trust them to have the best information. We can trust experts to have knowledge... but can't always trust their incentive alignment. In an era of ever-advancing information (and misinformation) glut, how do we get to a place of confidence in our hard-won justified true belief? Trust is social After 15+ years building fintech at PayPal and Stripe, I saw money movement simplified and commoditized. But the difficulty of transacting moved upstream. We made the how of buying easier, while advances in technology made the what, when, and why so much harder. From BNPL to crypto to vibecession, our economic realities aren't getting simpler. To compensate, 79% of young adults get financial guidance from social media (Forbes). Not because TikTok or YouTube has better models than Morgan Stanley, but because they trust the people sharing their stories. Millions of people are already collaborating on financial decisions. Privately on WhatsApp, obscurely on Discord, and full-blown publicly on Reddit: /r/personalfinance - 21 million members /r/financialindependence - 2.3 million /r/financialplanning - 1 million And dozens more subreddits and Internet forums (shoutout Bogleheads and Refinery29's Money Diaries). They're sharing detailed financial profiles with strangers on the internet, seeking advice from generous folks in full view. There's a fast-emerging story about AI here, and I've got whole posts dedicated to that coming soon. For now, suffice to say, we need the tools to catch up to the times. Enter FinFam FinFam[^name] lets families and friends collaborate on financial decisions with each other, using expert information without any commitments to said experts. We want to holistically solve the problem of financial decisionmaking using interaction models proven by GitHub + StackOverflow + app stores. How? First, creators publish interactive models, to FinFam's View marketplace. Then, you, a user who has a financial question or decision to make: Pick up a relevant expert view. If one doesn't exist, ask in FinFam's Q&A board. Plug in your own numbers and save it to a private workspace for your inner circle Discuss the results, with optional AI-assisted guidance as needed Move forward with confidence. We scale the expert knowledge while embracing the fundamentals of human social trust. Users get better decisions and peace of mind. Open-source meets fintech My years of work in open-source and wiki ecosystems showed me the power of collaborative, transparent tools. FinFam brings that same philosophy to personal finance. To further scale the knowledge, we make it possible for anyone to create a View. The View "source" format is XLSX, and can be edited with Google Sheets, Excel, or LibreOffice. Any published View can also be open-sourced. Just like with code, financial models are now reviewable, forkable, and improvable by the community. Curious users can check the community's math. Numbers and discussions happen with people you trust. Everything is private by default, shareable by design. What's next We launched beta this week and there are now daily spots available as we add capacity. You can sign up for early access here. I've been using it with friends and family for months now, and it has replaced Google Sheets for the financial decisions we face. There's so much more I want to share about the vision, the technology, and the journey so far. But this feels like we're off to a good start. Want to follow along? Subscribe to FinFam here and Sedimental here. If you're wondering about the name, just log in, go to your default space, create a thread, and ask Finn. ↩

19th Sep 2025 • 1 votes
What I've been up to in 2025

Been quiet around here. Time to change that! The short version up front: Since starting a family and leaving Stripe, I've pursued the dream that brought me to Silicon Valley. I've founded a startup. After taking some parental leave, helping found a Python non-profit, and a nice long visit back home, I was raring for a challenge. So these days, outside of family, I'm all in on something new. Contents Why now? Applications Monetary misunderstandings Showing vs Telling Why now? I've wanted to start my own business since building Access apps in high school. But, the reality of leaving my family and moving to study in the USA, combined with the technical and creative fulfillment of the software industry, took me on a scenic route through enterprise software, free culture, and open-source. That very same reality has since conspired to convince me to return to my original aspirations. I've lived through some exciting times in software, but nothing like now. This isn't something I imagined I'd be working on 10 years ago, but then again it's not something I thought possible even 3 years ago. What better time to be building and launching my most ambitious project ever? Full details on that are coming soon1. For now, here is a post about why. Applications To start my career, I worked on software infrastructure, security, observability, and developer productivity. But after eight years, around 2016, I started longing for something more human. You can see this start to come out in The Packaging Gradient. At a time where it seemed like everyone around me was talking about pip, pipenv, and PyPI, I couldn't help but remind people that the real end goal of software has always been the application (or even the appliance). This impulse came to a head with APA. Perhaps you, dear reader, have also been "lost in the sauce" of software: When you love computers and it dominates your thoughts, you might also spend most of your time thinking about the software that makes the software possible. Don't get me wrong. Languages, libraries, compilers, devtools, we need every bit of help we can get. But I fell in love with software for its potential to effect change in the world writ large. I started eyeing product. The famous full stack. That meant moving on from big tech, to a big startup, to a seed startup. One pandemic-fueled detour through a startup factory later, here we are. Finally, founding the startup. My own full stack. Monetary misunderstandings My 15+ year software engineering career can be summed up as: Building fintech software for pay Shipping open-source Python/wiki for free Professionally enabling commerce while avoiding it in my personal time. I was young and conflicted. Truthfully, I still harbor some reservations, but I have to build what I know. I know about software and money. "Money is the root of all evil." If you look at the state of say, open banking in the USA, or web3isgoinggreat, or just read Money Stuff, you probably agree something's off. Money changes people. But so does the lack thereof. I've watched more talented and deserving developers than myself befall a variety of fates. Hollowed out by monetary excess, blinded by greed, burned out by FOSS, literally working Doordash to keep the lights on. Dropping out of software completely. Shunning the world's favorite fungible has bad outcomes for individuals. Bless my friends at Tidelift, OSTIF, and other orgs working to sustain the maintainers. Paying maintainers is a worthy battle. We just need to open more fronts to navigate what's in store. Showing vs Telling Lately I've been thinking a lot about my favorite David Lynch (RIP) scene. It isn't from one of his films, it's this quote: "The film is the talking." I think it perfectly captures the auteur mindset. Words are extraneous. The consummate creative expresses themselves better in their native medium. Not that I mind words as a medium. After years of blogging and speaking, I've grown confident in my ability to tell. But now it's time for the show. For friends who can't wait a couple weeks, shoot me an email for early access. ↩

25th Aug 2025 • 1 votes
Intentional Creation

Reliably tap into your creativity with the 4 Cs: Consume, critique, curate, create. This is one of my oldest ideas, finally published on the GitHub ReadME Project blog, along with a profile, in June 2022. For more like this, follow me on Twitter or Mastodon. (You can also read it in 中文 here. Thanks Dominic Huang!) We all have creative potential. Whether it gets you up in the morning or keeps you up at night, you've felt its gnaw. Turning that potential into productivity can prove challenging in an internet-connected environment that offers a constant stream of consumables. How do we pick a direction? In this guide, you'll see how to distill the elements of creativity into four deliberate stages, and how to put the process to use: Contents Consume Critique Curate Create Debugging the process Putting it into practice These 4 Cs comprise a straightforward, adaptable approach that works well in both group and solo settings. You've already started on step 1. Read on to find out what to do next. Consume Step 1: Turn passive consumption into active research. From the moment you open your eyes in the morning, you're accosted with calls to consume. Articles, videos, podcasts, the newest Wordle variant. When consumption is the default mode of our modern computing environment, how is a builder supposed to build? To create, we must first recognize its inverse: consumption. Consumption is a useful stage, but can be dangerous if it’s terminal. An infinite loop in this stage kills any chance of creation. Little is created in a vacuum. Creation still starts with consumption, albeit consumption disarmed with an intention. Turn pure consumption into active research, punctuated with critique. Critique Step 2: Capture your reactions in critiques, and research no faster than you can react. As with so many software problems of our day, the answer is simple: React. No, not the JavaScript framework, but the human act of reaction. Intentional creation starts with giving yourself pause on new inputs. Seek a reaction from yourself. A semi-structured reaction, or critique, is a time-honored practice in creative fields, like architecture. Infinite scroll may prove challenging to overcome, but before turning your consideration to the next item in your feed, activate your critical senses. Draw some conclusions. Even unvetted, they're yours. If you're finding it hard to summon a critique, this is a clear sign you're consuming faster than you can reflect. If you're not reflecting, you're not learning. You may need to go deeper on individual items, or just take a break. Your critiques have never been easier to capture, whether typed in markdown, dictated to automatic transcription, or written down in a notepad on your desk. Try opening your editor or critique tool before opening any new resources. Feel free to open one now. If you're not reflecting, you're not learning. Curate Step 3: Curate critiques into collections that act as reservoirs of creative reference. Critiques are only proto-creative output. Writing anything helps prime the creative pump, but criticism is raw reaction. You want a refined synthesis. Once you've got enough critiques under your belt, curate the positive examples into a collection. From interior designers to lab researchers to club DJs, creators recognize the value of a structured, referenceable collection. Sometimes a situation calls for urgency or direction, and an organized, well-researched collection can offer an existing solution. Sometimes, in the context of a comprehensive collection, the lack of a referenceable solution is itself a signal that it's time to invent. Curated collections become artifacts unto themselves. I've helped create a few, including 0ver.org, seealso.org, and the Awesome Python Applications list. There’s more awesome out there beyond Awesome Lists, like explorabl.es, the Cooperpress newsletters, or the “swipe file” phenomenon used among designers and content creators. There's respectable work in curation. Still, curation is more important as a stepping stone to our original higher calling. Less is more. Create Step 4: Return to your curations regularly to discover your creative path forward. Collections of a certain size tend to produce interesting findings. Patterns and gaps emerge that inspire creative next steps. As an example, while researching approaches to Python packaging, a pattern emerged that led to one of my most popular concepts/blog posts/talks, The Packaging Gradient. Whole projects can be born out of connections made with collections. My framework Clastic, which was eventually used by teams at PayPal and Wiki Loves Monuments, came out of the curated combination of pytest dependency-injection semantics with werkzeug primitives. Realistically, the majority of creation happens below the threshold of standalone artifacts. For instance, when adding a feature to an existing system, a parallel approach in a different project serves as a useful guide. I've lost track of the number of times I've swiped techniques from Awesome Python Applications, including ones used to port my dayjob's 300k SLOC codebase from Python 2 to 3. Most creative outputs have a similar lineage. Only now we have an explicit process. Debugging the process It's easy to see creations we appreciate as towering achievements that sprung fully-formed from their creators' genius. But creation comes in fits and starts. If creation comes slowly, here are a few strategies to consider: Search for a natural split in an existing collection that's getting too big, and explore what makes it interesting. Revisit an old, contentious critique and re-react. What did you get right/wrong? Pick a particular exemplar and turn it into a case study. One beautiful aspect of FOSS projects is that going deep can mean getting involved. There's nothing like proximity to a problem to inspire creative thinking. More generally, be wary of one-size-fits-all solutions; while prescriptive techniques such as the Zettelkasten Method may work for some, creation is idiosyncratic. Embrace your own process. Putting it into practice When inspiration hits, connections can form so quickly that we take for granted what goes on. When inspiration proves less willing to strike, we can keep ourselves primed for creativity by ensuring all four activities continue in balance. There are a few notable benefits of intentional creation: When you've built something, the influences are well-documented. It can be easier to involve others when there's a clear creative thread to pull on. Sharing your critiques and curations invites collaboration with other creators and curators. Self-awareness. If you're not finding your critiques crystallizing into new thoughts and ideas for projects, that's a sign you're looking at the wrong stuff. Are you following your interests or passively consuming trending content? Practically, intentional creation means consciously spending less time on consumer sites, from Twitter to Hacker News, and more time taking notes, tagging bookmarks, and creating your own knowledge base. Attempt activities that are less entertainment and more you, ultimately closing the gap between you and your creative goals. If it sounds too simple, that's because it is. You're still accountable to you, that's the hard part. But hopefully you'll find some value in this simple hierarchy that lets you check in on your own activities and make adjustments toward a more creative end. Spend less time consuming, and more time on the other three Cs. Consume only enough to allow yourself to critique, curate, and create. If you made it this far, then start now. Step 2. Use any tool or service you like, from spreadsheets to YAML, and answer this: What's your critique?

4th Jan 2023 • 1 votes
Thanks, 201X!

Thought I'd take a Sunday afternoon to reflect on, oh I don't know, a decade. Been a long ten years, but it's flown past. This particular decade happens to coincide with my first years of full-time professional software engineering. The Quantity I can't possibly summarize it all, and if I tried, it'd still be colored by what's on my mind right now. But I can point to the artifacts I tried to leave along the way: Twitter FWIW1 (2008+) ~20 Open-Source Projects (2012+) ~15 Hatnote Projects (2013+, follow us) ~25 entries on this blog (2015+) +7 here (2014-2016) Not including pythondoeswhat.com or blog.hatnote.com (or other posts on the blogs only real heads know) ~10 Talks (2016+) Lest I forget: O'Reilly's Enterprise Software with Python (2016) And several podcast/media appearances calver.org (2016) and 0ver.org (2018) (Versioning is a fun pastime) Pyninsula (2017+) - YouTube, Meetup, Email Announce Taking a chronological look at each of the above, I'm relieved to see obvious growth. If I were to highlight one resource, it would probably be the talks. Despite the stress of preparation and delivery, I'm least concerned with having a massive miscommunication when we're all in the room and I can see the points hitting home. It's impossible to pick a favorite, but Ask the Ecosystem (2019), the Restructuring Data lightning talk (2018), and The Packaging Gradient (2017) seem like audience faves from where I'm sitting. The Quality Each project, post, and talk had its own reward, but I guess I've got more than just those to show for the decade. On the more profit-driven side, I built tools and teams at PayPal, but once I could manage the risk, I got to dip into startups for the last few years. Lucky for me, it wasn't a total bust, and the wife and I bought a place in my favorite neighborhood (in the USA). Not a millionaire, but I'm hoping and working for a world where no one has to be. More recently, the Python Software Foundation made me a Fellow. This isn't something I can be nonchalant about, and I'm not going to understate how much this means, to me, working in a field like software, where concrete symbols of progress are alternatingly elusive and vanishing. Plus it's Python, and reciprocated love is nice. I have hundreds of people to thank for helping me reach this point, and I have to thank the PSF for dedicating the time to ramping up these awards. They've convinced me more than ever that we need more institutions to build this sort of advancement. To all of you, thank you. The Struggle I like to think I managed to do all of the above while staying away from industry hype, on the principle that massive speculative capital influx isn't where real value is added to society, and doesn't generate the kind of innovation that excites me. I may have been naïve, but I came to Silicon Valley with an idea about the transformative power of software. Changing times may illustrate a grittier interpretation than the one I had and have, but I continue to hold dear software's potential for positive impact. If you've felt that vision waver, let me tell you, you're not alone. In the past decade, I've seen too many engineers sucked in by new technologies and ventures, only to find themselves alienated from their work. Episodes ranging from an afternoon lost to debugging Docker/k8s clusters, to years of work disappearing at the end of a VC runway. Nothing has been harder to watch than those bedraggled-but-persistent idealists regroup, each time a bit more cynical than the last. Even if its seeming intractibility has taken it from the center stage, the burnout conversation continues to smolder, because there's no issue realer. I know; I released more ceramics than software back in 2014. Some problems can be solved by paying the maintainers, but I think the vastly bigger issue is around losing the human connection between the real effort software takes and the real benefits it brings, combined with FOSS's dearth of collaborators in supporting roles (QA, product/project/release management). That's why I'm incredibly thankful for the Wikimedia community for always being there, patient with schedules and issues, as long as the software got the job done. It can be a challenge to juggle projects, but I tell every budding engineer: find that direct connection to people who will appreciate your work, and avoid cynicism at all costs. There are some interesting prospects in the works, but I'm keeping this post retro. Besides, if 2029 rolls around and all I did was break even with 2009-19, I don't see how I can be disappointed. Thanks again for everything in 201X, and for sticking with me in 202X. Despite using Twitter for over a decade, the process of tweeting feels so perfunctory, and the service itself so tenuous, that I still can't bring myself to invest the time. I mostly use it to crosspost my blog posts or help friends promote their posts/projects. But until I start an email newsletter, or really get on top of yak.party, it's still the best I got for announcing where I'm speaking next. ↩

2nd Dec 2019 • 1 votes

More in programming

Glashütte Trash Clock

Artist builds a working mechanical clock from trash collected in the famous watchmaking town

an hour ago • 1 votes
Float and integer arithmetic follow two different paradigms

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).

2 hours ago • 1 votes
A new home for all my apps: apps.chofter.com

Say hello to apps.chofter.com, the new home for everything I build. The speed at which I ship new things has massively increased with the advent of AI, and I’ve been encouraged by the fact that, as I approach my sixth decade, new ideas for useful & fun things to build still come at me apace. These no longer fit on my personal homepage, which is a combination of work experience, interests, things I made long ago that are no longer relevant (but still interesting), and of course, the many apps & tools I have out there in the wild right now. The site was 100% built using Claude Code, which did an amazing job of inspecting all the various websites, app stores and code bases and constructing a site in 30 minutes or so. I had to push it to make the site more SEO friendly, pre-rendered to HTML rather than over relying on client side rendering, but that was it. So there we go, enjoy the delightful and hopefully useful apps that I’ve already built and will continue to build in the future

23 hours ago • 1 votes
SumatraPDF new features: March 18, 2026

New in the SumatraPDF pre-release builds: DDE commands accept arguments Commands sent via DDE can take arguments, the same as in custom shortcuts (#5383). Loading message in tab While a document loads, its tab shows a “loading” message instead of the home page (#5385). Install 32-bit on 64-bit Windows The installer lets you install the 32-bit version on 64-bit Windows (#5379). Changes for this day · Full changelog

yesterday • 1 votes
An Update on Orion for Linux and Windows

Kagi is ending development of Orion for Linux and Windows and open-sourcing both so the community can carry them forward. Our small team will now focus fully on making Orion for macOS and iOS faster, more stable, and more capable.

2 days ago • 1 votes
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