8 posts
AI & Tools
Agent workflows and tools examined through experiments, worklogs, and practical limits.
Blog
This is one body of work organized into five editorial tracks. Each track keeps a stable voice and reading rhythm, while tags connect related ideas across the whole collection.
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Editorial Tracks
Every post belongs to one track with its own subject, reading rhythm, and voice. Tags connect ideas across tracks.
15 posts
Engineering Systems
Architecture, reliability, languages, and the mechanisms behind engineering choices.
16 posts
Field Notes
Personal history, retrospectives, portfolios, and observations from work in progress.
6 posts
Leadership & Teams
Ownership, autonomy, communication, and the systems that shape how teams operate.
18 posts
Quest Engine
The connected framework, from Search, Drive, and Renew to practical applications.
My Swift Journey: Why I Love It but Can't Use It at Work
Swift might be my favorite language, striking a rare balance between low-level and high-level features, yet I've never been able to use it professionally. This is why, and what it takes for a language to break out of its home ecosystem.
The Four Capabilities and the Human Singularity of the Quest Engine
Mustafa Suleyman named four capabilities that would make him shut an AI down. They map exactly onto the Quest Engine: one of them (setting its own goals) is the Objective Function, and the other three are Search, Drive, and Renew. The full mapping exposes the one layer the framework leaves to you: staying conscious of your own why while the loop closes on itself.
25 Years of Operating Systems: Windows, macOS, and Back Again
A personal retrospective spanning 25 years of operating systems, from Windows 98, 2000, and XP through a decade of macOS to a return to Windows 10 and 11, and a look at where a fully Linux development environment might fit next.
The Bicycle of the Mind: Fast, Slow, and Automatic Thinking About Agents
Kahneman's two modes of thinking (fast System 1 and slow System 2) map onto learning to ride a bicycle. Attention gives way to automaticity, and that same arc is a methodology for thinking about agents, leverage, and engineering systems.
Blameless Engineering: No Heroes, Just Systems
Blameless engineering, borrowed from Google's SRE culture, is usually filed under postmortems. But the postmortem is only the last place the culture shows up. Blamelessness shifts all the way left into how you design systems, and it lands on one uncomfortable rule: the team is the unit of work, and heroes are a symptom of a system that is not yet well crafted. In the age of agents, where there is no one to blame, that rule stops being a nicety and becomes the only way to debug at all.
A Case Against Using the Word 'Bad' in Engineering
I used to say bad version, bad rollout, bad payload. I stopped, because a version isn't good or bad in the abstract. It's a distribution of outcomes across a population of users, configs, and use cases. The same payload can be flawless for 99% and broken for 0.5%, and calling it bad collapses that spectrum onto one label that quietly dictates how you triage, communicate, and remember the incident.
Fearless Engineering
When I was starting out, hesitation held me back from trying things. Over time it faded, not because I got braver, but because I got a better handle on risk. Fearless engineering is not the absence of caution. It is a calculated read of what you know, what you do not, and how far a change can reach.
9 Years of Copious Notes
Nine years of work notes, from sort-of-daily Markdown files in 2017 to monthly Word docs to a single yearly running document, and how AI agents finally took over the writing through worklogs.
The Word "Impact" Considered Harmful at Work
A reflection on why the word impact is too overloaded for work conversations, and why accomplishments and outcomes are clearer alternatives.
Orthogonal, Not Opposite
Salty is not the opposite of sweet. They are separate receptors, separate dials, and salted caramel exists because you can turn up both at once. Most 'balance' advice is secretly slider-thinking. The method is to catch the false opposite, test for a real tradeoff, and go to the corner everyone told you was impossible.