Tagged “ai”

I’ve been working on ProjectSpire’s iOS app (codename: Neow’s Cafe) in NicholasClooney/ProjectSpire as a 1:1 Slay the Spire 2 card library, and the useful part is not just the filtering UI and refactor cleanup, but the way I’m trying to work with AI.

I get better results when I lay down the foundations myself first, especially around quality, guard rails, and how the data is modeled, and then let AI work inside that framework instead of asking it to define the framework for me. It also helps a lot when I have AI propose higher-level API or contract changes before it starts making edits.

I shipped d60e0e1 in SwiftyBites with a new SwiftUIComponentsLibrary area for pickers, menus, search scopes and tokens, and width-showcase layouts.

The useful part is not just the snippets themselves, but that AI agents researched the best practices, produced the example code, organized the project, and left me with a runnable playground where I can compare equal-width stacks, GeometryReader, PreferenceKey, and some surprisingly similar results against my actual needs.

I published The Brain That Grew — Then Shrunk: What I Just Discovered, a long-form note that starts from a Cleo Abram YouTube Short and then follows the research on human brain evolution, the unexpected Holocene shrinkage, and the idea that culture may have taken over part of the cognitive load. It is the kind of rabbit hole post I like writing here: one short video, a lot of reading, and a sharper takeaway than I expected.

I published The Confident Lie: What AI Got Wrong About @ViewBuilder, a SwiftUI debugging note that came out of the ProjectSpire card view work. It captures a small but useful lesson: body gets @ViewBuilder from the View protocol, but a custom computed some View property needs the annotation explicitly if I want an if without an else. The compiler was right, the AI was overconfident, and now the mistake is written down somewhere I can find again.

Published The Accelerated Speed of Creation, a reflection on how much faster the path from thought to shipped artifact has become with coding agents handling the translation layer around writing, blog workflow, and routine Git operations. I also kept the earlier Encoding My Blog Workflow for Coding Agents draft as a note rather than a post, because it was useful and concrete but still did not meet my standard for what the real piece needed to be.

This past week I shipped across code and writing at a pace that would have felt unrealistic before AI. The surprising part was that it did not feel frantic; it felt like less friction between thought and artifact. It truly feels like working at warp speed, 😜.

Look at this. This is what I have shipped so far in a single week and growing (full list here):

I published Smart AI Token Consumption as a note on matching model choice to task complexity instead of defaulting to the biggest model. It captures the split I keep using in practice: light models for mechanical work, stronger reasoning only when the problem actually needs it.

I published The Limits of AI and Where Humans Shine — a devlog about a tiny timeline sorting bug that turned into a useful comparison between AI confidence, runtime verification, and human judgement. It follows the fix from plausible-but-wrong timestamp changes to a quoted-date guard that keeps the timeline honest.

I hit a bug that looked too small to be interesting: entries on my timeline page were not sorted correctly within the same day.

The page had a date, a time, and a custom Eleventy collection sort. That sounds like the whole problem space. Sort by date plus time, reverse the collection for newest first, done. Instead, April 12 was rendering in a strange order: 00:01, 10:11, 22:16, 15:49, 22:20.

Published What's Worth Keeping: On Humanness in the Age of AI — a post on what I've been thinking about since attending a thought experiment session on AI and skill erosion. It's about the parts of humanness I think are genuinely worth protecting — junior skill-building, critical thinking, forming a view before outsourcing it — and what I actually try to do in my own daily use of AI tools.

I've been building a habit-logging iOS app called ProjectDawn. Not because the App Store needs another habit tracker, but because I wanted a personal project that was genuinely mine and open source, and a project that can answer this openly: what does it feel like to build a real, modular, native iOS app with AI as a primary collaborator?

This post is part personal log, part technical retrospective. It covers the tools I used, what surprised me, where the AI fell flat, and the biggest shifts in how I think about building things now.

I’ve had the Umami + Ansible post in my head for ages, but it touched three different repositories and a whole bunch of code snippets. Totally doable, but undeniably tedious — which is why it kept slipping down the backlog. You can read the finished article here: Private Analytics With Umami, Docker Compose, and Ansible.

The idea that finally nudged it forward was simple: why not let GPT (Codex) do the heavy lifting while I steer?

For years, I thought of coding as something tied to my desk — Mac in front of me, full keyboard, full IDE. But recently, I found myself dreaming: what if I could carry my entire creative coding studio in my pocket? Not just SSH access, but a true AI-assisted environment where I could code, commit, and preview my projects anywhere.

This blog is half technical walkthrough, half personal reflection. It’s the story of how I explored Cloudflare Tunnel, discovered Tailscale, refined my workflow with tmux and iTerm, and ultimately unlocked the freedom of having a fully fledged Mac in my pocket.

Building small websites with GPT-5 Codex turned out to be less about typing code and more about collaboration. From crude sketches to polished sites, the model took on the heavy lifting while I guided direction and design.

Along the way I discovered both the joy of fast iteration and the limits of relying on an AI partner. These projects became less about the sites themselves and more about exploring a new style of programming — conversational, creative, and sometimes flawed, but always eye-opening.

Last month, my girlfriend mentioned she needed a sleek portfolio site, and I realized I’d been meaning to start a personal tech blog.

I wanted something lightweight—easy to spin up and even easier to tweak. So I dove in: building a small 11ty + Tachyons site from scratch, pushing every iteration live in under a minute, and watching her face light up with each update even though she’s halfway across the country.