Writing¶

If You Want Taste, You're Gonna Have to Eat

There are songs that make me cry that you'll never hear about. There are poems I read while my mother lay dying in front of me, and unless I tell you, you'll never know which ones. My taste in music, in food, in art, all of it is private by default. You'd have to eat with me to know I'd happily live on fried chicken. Nobody reads my diary unless I show them. Nobody comes into my home unless I invite them in.

But the moment I step outside, they're looking at you. Before I speak, before you know what I do, before you know anything about how I think, you've already seen my taste. Personal style is the most front-loaded expression of taste there is. Every other form you get to keep to yourself. This one you have to subject everyone to. Some days I feel terrible and I put on a fucking blazer. Some days I want to wrap myself up and hide in the shadows, and some days I want to command the room. The clothes go out ahead of me.

So style is where I want to start, because it's the honest lab. But this essay is really about taste, and why I think it's become the thing most people are missing.

Two kinds of scheduled work in Codex

Most automation language is more complicated than the job.

You want Codex to do something later, or keep checking something until it changes. That sounds like one feature. It is actually two different kinds of work, and the difference is simple:

• Scheduled Tasks create a new thread every time they run.
• Scheduled Messages use the same existing thread every time they run.

That is the whole model.

Three Ways Codex Can Use a Computer

Recently I had a package stolen. Amazon told me it would take about 25 minutes to connect me to a person, so I gave the thread Computer Use and told it to check every five minutes. Once someone joined, check every minute and do its best to get me a refund.

I went to take a shower. When I came back, the refund was done.

That was when Computer Use clicked for me. Codex is not just a coding agent. Most of my work is messages, forms, browser tabs, and apps that do not connect neatly to anything else.

Six levels of complexity in a Codex morning brief

This is the easiest way I know to teach someone how to use AI.

Not by starting with models, agents, or some abstract taxonomy of what the technology can do. Start with a job people already understand, then make that job quietly more powerful.

The morning brief works because almost everyone already has one. They just assemble it badly.

I think the morning brief is the first Codex workflow that normal people actually understand.

You wake up, open Slack, check your calendar, click into email, forget why you opened email, go back to Slack, then realize you have a meeting in seven minutes and no idea what happened yesterday.

The appeal is simple: help me remember what is going on.

When we were talking about Codex onboarding, this was the first workflow that felt both boring enough to teach and strong enough to matter. It starts as a dumb little orientation prompt. If you keep pushing it, it turns into a pretty good model for how people actually graduate into using Codex seriously.

Start with the thing a beginner can understand. Then add one real capability at a time until the shape of the whole system becomes obvious.

I think there are six real levels.

Codex-maxxing

I was already using coding agents a lot before Codex. Mostly, though, I used them through interfaces built for coding work: making diffs, changing repos, and shipping code.

Around November, I started pushing them into knowledge work too. I made presentations in Slidev, used agents more like note-takers with voice input, and kept looking for other artifacts a coding agent could help me produce: an index.html, a PDF, a spreadsheet, a slide deck.

The latest Codex app upgrades are the first thing I've used that make that broader mode feel native. Codex is still excellent for coding, but the more interesting shift is that it gives my work somewhere to live.

What changed my behavior was learning to give work an operating loop: a durable thread, shared memory, tools that can act on my computer, ways to steer and resume the task, and a surface where I can review the artifact itself.

What Music Do You Listen To?

People often ask me what kind of music I listen to, and in my mind I almost never remember. Today I wanted to write a little bit more about the music I listen to and share some of my favorite albums with you. A lot of this has been co-written with the Spotify API, so everything is as true as it can be.

Sunsetting 567 Labs and Open Sourcing the Course Content

I am sunsetting 567 Labs. The courses close today, February 2, 2026.

Things

Some links may include affiliate attribution. Recommendations are based on personal use.

In the past 2 decades I went from sharing a bed with my parents renting out the unfinished basement of some Canadian family to doing quite well for myself. This is all the stuff I use, plan to use, and what's on my upgrade roadmap. Each item includes why it works for me.

Do Your Engineers Know How to Leverage AI?

This past spring, two senior engineers at different companies received the same challenge from their CEOs: "We need to move faster. Use AI to get there."

What Is the Coding Agents Speaker Series?

I hosted a series of conversations with the teams behind the most successful coding agents in the industry—Cognition (Devin), Sourcegraph (Amp), Cline, and Augment. Coding agents are the most economically viable agents today—they're generating real revenue, being used daily by professional developers, and solving actual business problems at scale.

This makes them incredibly important to study. While other agent applications remain largely experimental, coding agents have crossed the chasm into production use. The patterns and principles these teams discovered aren't just theoretical—they're battle-tested insights from systems processing millions of real-world tasks.

This series captures those hard-won lessons, revealing what works and what doesn't when building agents that actually deliver economic value.

Context Engineering Series: Technical implementation patterns for agentic RAG systems, including tool response design, context management, and system architecture. This Speaker Series provides strategic insights, while Context Engineering offers implementation details.

**[RAG Master Series](./rag-series-index.md)**: Comprehensive guide to retrieval-augmented generation systems. Many coding agent insights (like why simple approaches beat complex ones) apply directly to RAG system design and optimization.