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Now that I use AI regularly to help write code and complete tasks, I find myself in a position where I’m not learning as much as I used to. That feels a bit crummy. Fairly often, Claude writes code I don’t fully understand. For example: I know enough TypeScript to be dangerous, but I’m definitely not an expert. Recently I had Claude take some typing I thought was overcomplicated and drastically simplify it. The new version was clearly better — I just couldn’t tell you why. So I asked Claude to explain it in simple terms. Sure enough, it did. I guess that’s a silver lining to using AI: it can at least explain why it did what it did. A coworker mentioned he has Claude write one-off explanations with examples whenever this happens, and I liked that idea. So I built a skill around it. The skill looks at my uncommitted code, breaks it down, and writes a short blog article for me to read. I’m a fan of Josh Comeau’s blog and the way he uses interactive examples to teach a concept, so I made that part of the skill too — Claude generates interactive examples alongside the explanation, then packages everything up in a small Vite environment. The first iteration was expensive to run. At least 3 minutes, and roughly 10K tokens. I’m fine burning tokens, but I’m also thrifty 😬. The second iteration kept the Vite environment and styles already wired up, so Claude only had to write the article and the examples. That brought it down to about a minute and 7K tokens. Better — though I’d still like to get the token usage lower. The blog format is great, but it’s a lot of work (for Claude) to generate all of this just to delete it when I’m done reading. It’d be nice to have these articles persist somewhere I could revisit later, or share with other people. That brought me to my current iteration. It’s an Astro project that lives on GitHub. The skill works roughly the same way — review uncommitted code, generate a post complete with interactive examples — but now it publishes to a TIL subdomain where I can read the articles at my leisure or pass them along. It’s all vibe coded, and that feels appropriate. I’m up front about it on the site itself: Things Claude changed that I didn’t understand — explained… by Claude. I’ll probably keep tinkering to bring the token usage down further, but it was a fun project to put together, and I’m happy to let Claude teach me what it’s doing.
This is an updated list of what I’m using in 2026. I’m only sharing what’s changed since last year’s list. Applications Chrome — Chrome was on my list last year, but I’m mentioning it again because I actually used Brave for most of 2025. I like Brave, and honestly I can’t even remember why I switched back to Chrome 🤷🏻. ChatGPT — I hate that I’m listing AI tools, but if I’m going to be transparent, it has to be here. I use it a bit for code, but mostly for rewording messages or rubber-ducking ideas. Claude Code — I wrote about my thoughts and reluctance to embrace AI for coding. My company pays for it, so I use it. Endel — I’m neurodiverse and have been trying to be more intentional about using tools that help me stay focused. Endel is super cool and has a lot of genuinely helpful features. Hyper — I was previously using iTerm2, but switched to Hyper mostly because it feels prettier. That’s probably a dumb reason since I could have customized iTerm2, but I installed Hyper on my new machine and never felt the need to switch back. Retcon — My team is pretty opinionated about Git history, and rewriting history via the command line or VS Code started to feel tedious. Several coworkers use LazyGit, but I didn’t want another terminal-based tool. Retcon does exactly what it promises and lets me handle more advanced Git workflows without having to be a Git super-nerd. Notion — I was using Bear for notes, but didn’t feel like I was getting enough value out of paying for it. That’s not a knock against Bear—it’s a great product. Notion’s free plan works just fine for me. I also tried Obsidian this year and liked it, but parts of it felt quirky. It also seemed like a bigger time investment to make it feel as polished as Notion or Bear. VS Code — I tried Zed for a bit, and there are things I really like about it. That said, I ran into a few weird and buggy behaviors that I just couldn’t get past. Equipment I got a 2025 M4 MacBook Pro when I started my new job this year. It’s more than powerful enough for anything I need to do.
One of the biggest challenges I’ve faced as a web designer is how often people expect a website for next to nothing. Somewhere along the way, the perception formed that a website is a commodity—quick, cheap, and interchangeable. So when someone asks what I charge (for a very basic marketing site), I usually reply, “That’ll cost around $5,000.” That number isn’t a gimmick—it’s a filter. It immediately reveals who understands the craft behind the screen, who values quality, and who’s serious about investing in their own business. It separates those looking for something fast and inexpensive from those seeking something purposeful and crafted. It used to frustrate me when people balked at the cost. Now? I see it as a helpful sorting mechanism. It shows me who I actually want to work with. The Cost of “Cheap” There’s no shortage of DIY website builders promising professional results at a low price. And honestly—sometimes that’s fine. If you just need something quick and functional, a template might be all you need. But a boutique website is something entirely different. When you hire me, you’re not buying convenience—you’re investing in craft. A boutique site is designed and engineered specifically for you. It’s not a template dressed up with new colors. It’s built intentionally, shaped around your goals, your audience, your brand’s personality, and the experience you want people to have. And cheap solutions often come with hidden costs: lost conversions poor usability and performance accessibility issues a generic, forgettable brand presence The value of a bespoke website isn’t just in what it does. It’s in how it’s made—and what it communicates about you. Why Bespoke Work Matters When I build a custom website, it’s not just about aesthetics. It’s about alignment—making sure every part of the experience supports your story, your content, and your clients’ needs. Every choice—typography, layout, semantics, performance—is intentional. Anyone can make a website that looks good. I handcraft websites that feel right and function beautifully. As a design engineer, I don’t hand off a static mockup and hope the final result captures the original intent. I design with the intent to build, carrying the project from concept to code so the final experience is cohesive, thoughtful, and true to the vision. That’s what boutique design is: every pixel and every line of code has purpose. The Bottom Line If you only need a website, you don’t need me. But if you want a boutique digital experience—something that reflects your values, your vision, and your commitment to quality—then I’m the right fit. You’re not paying for a website. You’re paying for craftsmanship, collaboration, and care. And while not everyone values that, the right clients do. My pricing isn’t just a number—it’s a filter that helps me focus on the people who appreciate the work, the craft, and the impact it can create.
When I first got into hand-lettering, I had a hard time finding people who shared their full process—especially the digitizing phase. So here’s a look at how I typically work. Everyone’s process is different, and a lot depends on your style and how you plan to present the piece. For me, since I don’t have the steadiest hand, I tend to embrace rough, scrappy, distressed looks. Most of my work ends up digital anyway, so mistakes can be fixed later. Here’s a short process video I made a while back. Thumbnails & Sketching Start with quick thumbnail ideas on scrap paper. Refine the chosen direction with a pencil on Bristol Paper. If possible, I use a drawing pencil (softer, lighter lead makes cleanup easier). After inking, I clean up with an art gum eraser. Inking My go-tos are Microns in different thicknesses. In the video I sharedI used a .08 for outlines and Graphic 1 for filling letters. I used a Gelly Roll 10 to add cut-outs, create depth, and fix small mistakes 😬. Digitizing I scan the inked artwork using Scanner Pro on iOS. Clean up in Pixelmator Pro. Add textures for distress and wear (I’ve collected a bunch of texture packs over the years). Where I’ve Used This This is basically the same process I followed for my State Motto series, and most of my other lettering projects. Don’t be afraid to lean into your natural tendencies (like a scrappier style if your hand isn’t steady) and use the digital phase to enhance or correct. Trial and error is a huge part of it.
Does anyone else hate the term vibe coding? I’ve been pretty resistant to incorporating AI directly into my development workflow. I use it all the time to clean up emails, Slack messages, and blog posts (including this one). It’s helped me plan vacations, write my cover letter for Planning Center, and even gain insights from journaling. But coding? That felt like crossing a line. At first, I confined AI to repetitive tasks—formatting long word lists into arrays, deciphering cryptic console errors, or exploring how to integrate Vite into a Rails codebase still using Sprockets. All helpful, but I steered clear of anything that touched “real” engineering. Still, AI isn’t going anywhere. And as much as I hate admitting how much I rely on it, it genuinely makes my life easier. So I gave vibe coding a shot. Spoiler: I’m sold—with a few caveats. Vibe Coding an Alfred Workflow I’d played with basic Alfred workflows before, using the built-in UI or tools like Alfy. But I had an idea for something more complex—and neither the time nor the motivation to learn how to build it from scratch. The Problem At Planning Center, our design system has 300+ tokens (and counting). To grab one, I’d open our Storybook instance, scroll to the search bar, type in a few characters, click to copy, then return to my editor to paste it. Repeat that a few dozen times a day, and the friction starts to add up. The Solution An Alfred workflow that lets me search tokens via fuzzy matching, press Enter to copy, and paste directly—eliminating multiple steps and speeding up my flow. Using Claude Code I’ve tried ChatGPT and GitHub Copilot. They both work well (though I find Copilot’s integration with VS Code a bit invasive). I’m not ready to pay out of pocket, so I started using Claude Code through Planning Center’s access. Setup took less than 10 minutes. Anthropic’s documentation is clear, and their tips on effective usage are actually helpful. Building the Workflow with Claude Code I kicked things off with a prompt: I want an Alfred extension where I can enter “tt” followed by characters, and tokens from URL redacted will be shown using fuzzy search. Claude generated a Python script… that didn’t work. It produced a workflow Alfred couldn’t import. So I responded with: The Alfred extension fails to import. Claude replied something like, “You’re right, let me fix that,” and, impressively, it did. After about three hours of iterative prompts and debugging, I had a fully functional Alfred workflow that: Stores design tokens as a JSON database Caches data locally Refreshes if unused for over an hour Fuzzy-finds tokens on input Displays color swatches for color-based tokens I also used Claude to: Generate 100+ color swatches (since Alfred can’t use data URIs) Write a Bash script that builds the workflow with semantic versioning I don’t know much Python, but I know enough to skim the output and feel confident in the structure. And because this was a small, siloed project, I wasn’t concerned about maintainability or codebase conventions. The Cost Aside from the monthly AI access fee, the entire three-hour build process cost around $10 in usage tokens. That’s ~$3.33/hour—far below the value of my time. And now, every use of the workflow saves me 10+ seconds. That adds up quickly. If I’d tried to build this from scratch, it easily could’ve taken 10+ hours and been half as effective. That’s not even accounting for generating the color swatch images. I did spend about an hour trying to get Claude to scrape the tokens directly from the design system site, but that turned out to be unreliable. Still, the final solution works and required zero extra effort from the rest of my team. The Pros and Cons of AI in the Workflow Pros Efficiency Boost: Great at handling menial but necessary tasks—JSON formatting, token lookups, error decoding, etc. Rapid Prototyping: I built a working Alfred workflow in a single evening. Even if it were only a prototype, it would’ve been valuable. Creative Leverage: Designers and PMs can use AI to sketch out ideas and flows, helping engineers jump into development faster. Cons Skill Stagnation: Over-reliance on AI could erode problem-solving ability or deeper understanding of frameworks and languages. Job Displacement: AI is replacing some roles. At Planning Center, leadership has been clear AI won’t replace people—only support them. But the broader industry picture is less certain. Environmental Cost: Running large AI models consumes a lot of energy. Price Tag: Even if it saves time, AI access and usage can get expensive—especially if you’re footing the bill. So Why Do I Still Feel Icky? It took me a while to name the feeling, but I got there: I’m grieving the loss of what it means to be an engineer. I’ve spent over 20 years solving problems, building UIs, and turning ideas into code. I’ve always taken pride in being able to take a design and bring it to life. But now, what it means to be an engineer is changing—and that’s uncomfortable. I don’t want to become just a prompt wrangler. But I also don’t want to be the person who gets left behind because they refused to adapt. The logic is clear: why pay one engineer for 10 hours of work when another can produce the same result in two with AI? Finding the Sweet Spot I think the answer lies somewhere in the middle. Engineers should still understand their craft—be able to reason through problems, write maintainable code, and build features from scratch when needed. But AI should be a tool we use intentionally to reduce toil and accelerate progress. We don’t call it cheating when someone uses code completion. Why should this be any different?
More in programming
How do you tell friend from foe in a split second? These beautifully designed WWII guides used silhouettes and vehicle details into a system for recognizing tanks, planes, and ships on sight.
The Tetris effect is one of psychology’s most easy to reproduce experiments. Simply spend a bit of time playing the eponymous game every day for a few weeks. After a little while, you’ll start recognizing familiar Tetromino shapes in clouds, buildings, and everyday objects. You might even see them appear before your eyes when you start falling asleep. Tom Tang Attention hijacking There’s one lesson the Tetris effect teaches us: whatever you focus on long enough will end up shaping your thoughts. This can be a good thing since it’s how we learn new skills and discover new ideas. Sadly, less and less of our attention is focused intentionally. Instead of picking what we want to see we let other people decide what is supposed to be good for us. Do you want to watch a video? YouTube knows you like cooking and art streams. But why not also recommend a few clips about the stock market bubble, global warming, and the war in Iran. Doomscrolling will make you stay longer and click on a few more ads. Do you want to listen to music? Just open a Spotify playlist and let the algorithm figure out what you like. Please ignore the AI slop they will insert in between real songs to avoid paying royalties to real artists. Do you want to know how your colleagues are doing? Too bad, LinkedIn will bury any relevant career news between the opinion of complete strangers. It is surely just a coincidence that those strangers happen to be shilling whatever Microsoft is invested in at the moment. Do you want the opinion of strangers on a product? Well those Redditors you wanted to ask are probably just a bunch of LLMs talking to a bunch of Russian trolls now. I hope you didn’t value their opinion too much. If, like me and most people, you spend the major part of your day focused on your device, there’s no doubt it’s affecting you. And when you let someone else dictate what appears on your screen, it’s the same as giving them the key to your brain. New York Said Back to an intentional internet The internet wasn’t always like that. Before recommendation algorithms where a thing, you had to decide what you would be doing on the computer. You didn’t really have one big app that you could open and order it to entertain you. Instead, you had a few dozen of bookmarks to websites, each with a specific idea in mind. A site for video game news, that one website with lots of tutorials, a blog about anime that didn’t update often enough, a wiki about a TV show from the 90s… Of course awful things existed on the web. We had Encyclopedia Dramatica and Rotten.com, but you actually had to put the effort to go there if you wanted. Nobody was going to put pictures of dead kids and far-right propaganda as a suggestion after a pancake recipe or a cat video. The good thing is that this intentional internet is still around. It has just been a bit buried below the corporate web, but it’s not very hard to find. After all you’re on this blog, so you probably already have a good idea about it. The main difference between this time and now is you. When you want to get back to reading blogs, RSS feeds, and finish that tutorial instead of doomscrolling shorts, you have to get used to a slower internet. One where content is not infinite and doesn’t get updated every click. But like every habit, the only thing you have to do is to keep at it. And if you pay enough attention to it, something will click in your brain.
One of the interesting challenges of the AI ecosystem in 2026 is that new, effective patterns emerge faster than I can adopt them. I’ll find a handful, get back to work, and realize a month later that I’d missed four or five more. The adoption cycle for Imprint this year has been something like: January: get every engineer onto Claude Code every single day March: ok, let’s also get everyone else onto Claude Code or Claude Cowork every single day April: local development is bottlenecked on checkout and worktree model, instead create ~10 local workspaces which each have an independent checkout of every repository, and operate at the workspace level, not at the repository level, so it can generate cross-repository pull requests across frontend, backend, infrastructure and data monorepos June: oh boy, agent-driven development is heavily constrained by lack of a common task management system with higher visibility and less permission complexity than Jira, so let’s migrate the entire company over to Linear and hard stop on Jira July: yikes, now we have visibility into all these tickets, many of them are trivial but managing them through local development isn’t scaling, let’s roll out an orchestrated harness which internally we call “Agent Fleet”, along the lines of Stripe’s Minions The most recent question for me has been figuring out how to adopt the software factory pattern. (After some light research, the specific AI-context origin of this term is slightly messy to attribute, but I think it might be Justin McCarthy in February 2026’s Software Factories And The Agentic Moment.) The software factory pattern is looping on a broad goal, and then relying on the harness to drive progress towards that goal. Our first pass at implementation is fairly basic: An agent skill /linear-project-loop which reads in a Linear project and starts by auditing that project’s goal definition on these dimensions: An RFC in Notion that describes the project’s goals, how those goals are measured, and the general approach A Datadog dashboard or Snowflake queries that measure progress against those goals If those are missing, or the Linear project is missing in its entirety, it iterates with you on creating those missing tools. Then it reviews the state of the metrics and issues for the project. If new work is identified, it adds those issues to the project. It updates the state of issues that have moved. It works on the non-blocked tasks based on the project’s current state. This is often writing a pull request, updating a pull request, pinging for review, asking a clarifying question, etc. When a task completes, if the project description is fresh, it takes on the next task. If the description hasn’t been updated in a while, it reruns the loop starting with the first step. Right now I am running this locally in a local harness, but it’s working well enough that I anticipate moving the behavior to be driven by the same orchestrated harness that we assign one-off tasks to. What I particularly like about the factory pattern is that it parallels very closely how I’ve been working locally, while forcing me to recognize the places where I was accidentally hording parts of the state for myself regarding the goals of the project. I was already asking agents to iterate on specific Linear projects, but they didn’t have the ability to evaluate if they were going in the right direction, or if it was missing necessary tasks. Now it does. The other place this has been extremely helpful for me is checking in on projects post release. For example, I shipped our passkeys implementation earlier this year, but some months go by without my checking in on how it’s going. If we saw adoption spike, or error rates start to turn, I might miss it, but running the factory in a less frequent post-release mode would catch it immediately. The final thought that’s been interesting to me is how much all of the pieces here compound only to the extent that you have the other pieces. For example, this factory pattern depends on having Datadog MCP and Snowflake access available to manage goal-tracking, but it also depends on Linear being the single source of state for the company’s work, and an orchestrated harness that can perform work independently from your laptop. Keeping up with this many migrations is a fascinating industry moment.
I owe a lot of my professional identity and success to CSS-Tricks. CSS-Tricks repeatedly gave me the opportunity to write for them. In doing so, they helped to both socialize and normalize accessibility as a mainstream frontend concern. I’m deeply thankful to them for this. The team was also a joy to work with, notably Geoff Graham. He’s a mensch, and one of the nicest people you can interact with in the frontend web space. If you have not been following the news about the site, Kevin Powell has a good video about the whole situation: Content skipped. I’m not speaking on behalf of Geoff, Chris, or others involved with running the current version of CSS-Tricks. I’ve got skin in the game as an author. This is my personal opinion, born of my feelings and beliefs. I think a lot of the web’s infrastructure should be co-ops, and CSS-Tricks is knowledge infrastructure. To that point, I should also point out that the website covers far more than just CSS. The corporate model of ownership can be a risk. If infrastructure is not part of a corporation’s core strategy, it is not a priority. As Kevin’s video touched on, it seems like promotion via owning the frontend content space isn’t part of Digital Ocean’s strategy anymore. It is not that CSS-Tricks does not have value. It is that Digital Ocean cannot see it. It is deeply, tragically ironic to me that Digital Ocean allowed this to transpire. This is because I know for a fact that the techniques and philosophies shared by CSS-Trick authors helped to shape iterations of their product’s UI. Some may be quick to point out that this knowledge now—illegally—exists inside of LLM training data, so the risk of the website going away is mitigated. To this, know that we should be striving to keep resources like CSS-Tricks going. Human creativity is the force that creates new techniques, strategies, and technologies. The web will calcify without voices sharing what they know, forever locking us into endless permutations of a fixed point in time. Unlike corporations, co-ops don’t have to be motivated by profit. By not needing to prioritize growth at all costs it means co-ops can instead prioritize and incentivise things like preservation and cultivation. It is also a successful model of operation, one that even already exists, and flourishes in the tech space. Collective ownership can also serve as checks and balances for, and protection against hierarchical decision-making. I only need to point to the chaotic and aberrant decisions many CEOs in the technology space have been making as of late to demonstrate the value of this approach. Paddy Srinivasan, if you somehow wind up reading this: Save some face and take a big swing. Give CSS-Tricks back to the people who love it.
How can something that “just works” be so annoying? situation We live in Cambridge off a little road down a drive in shared ownership between us and our neighbouring houses. All the utilities are buried under this drive, including the phone line. anticipation Over the last few years we have been canvassed repeatedly by CityFibre saying that they can deliver fibre all way to our house. I saw them digging trenches and leaving tails of purple fibre cladding along nearby roads, ready to hook up all the houses. I thought they would need to do something similar to deliver fibre to us. So when they turned up and knocked on our door, I talked to their salesbods and walked them up and down the drive and pointed out where the existing BT line goes. Then they gave up trying to sell to us. This happened about three times. disaffection We were not eager enough for an upgrade to deal with these impediments. notification A few months ago we were told that CityFibre would soon come and do the upgrade, since there’s a nationwide deadline for turning off the copper phone network at the end of the year. We expected that this would force them to actually plan some digging works, so we talked to our neighbours about it. We were all ready for some huge faff to follow the next visit by the CityFibre bods. installation CityFibre turned up on the promised morning bright and early. To our enormous surprise, a brown fibre housing was already poking out of the ground next to our copper phone line. It had been fed through 50 metres of 5cm duct without us being aware they were even working on the street. Within a couple of hours, the technicians had drilled through our wall, installed the ONT, blown fibre through the unexpected pipe, plugged in the CPE (superficially identical to the old one), and left telling us to anticipate that it might not work properly until tomorrow. activation Around lunch time, the copper phone line stopped working completely. Some faff ensued, switching all our devices over to the new WiFi network. For a while we thought this was the death of our land line, but in the course of debugging other issues, I realised that the router has a built-in VoIP adapter (I don’t think we were told it has a built-in VoIP adapter) so I plugged the phone in and it Just Worked: they had ported our phone number across and everything. Flawless. I was seriously impressed. rumination It has been a few weeks since the switchover, and apart from a couple of horrible Clown-afflicted IoT devices, it has been fairly smooth. What prompted me to write this up was realising that we delayed this upgrade for years because the sales people were not given enough technical information about how the installation process works: the fact that houses typically have a 5cm duct containing the copper lines (probably standard for the last 40 years) and the fact that fibre can be shoved through a few tens of metres without difficulty. And worse, the sales people didn’t have an esclation path for difficult cases: they just gave up instead. From a technical point of view, the installation was impeccable. (I guess the loose 24 hour window for the cutover time was because OpenReach and CityFibre don’t have tight requirements on ISP reconfiguration schedules.) From the sales point of view, it was crap. Maybe it would have gone faster if we offered to switch early without asking if the drive would be a problem? But I guess the difference between “yes!” and “yes, but will this be a problem?” is too much to expect from a minimum-wage door-to-door salesbod whose employer didn’t give them enough information or any escalation path.
