My hypothesis this year around AI was that if I develop some agent skills to speed up repeatable processes, it might clear up my bandwidth and free up time for me to work on non-repeatable doc tasks. It appears to be working.
This month marks the one-year anniversary of the AI Book Club. We’ve now read 12 books in the club — see the list of books. For each session you can view recordings, notes, transcripts, discussion questions, etc. By some measures, the book club might not be considered much of a success. For each session, I record the discussion using Google Meet. Then I publish the recording on YouTube, along with a transcript and other notes. For the 12 vide...
After my post about how work expands to fill the space allotted, for a few days afterwards, I kind of slipped into the mindset that it didn’t matter how hard I worked, since my work and the work of those around me would all be viewed relatively the same, and if it comes time for someone to do massive layoffs (like we see in the news with Meta, Microsoft, Nike, etc.), it’ll be someone who doesn’t know me, who likely doesn’t even consult my mana...
One of the things I dislike about AI is how it takes over everything — every conversation, every process, every tool. But this week I noticed it started taking over my thinking as well. Here’s what happened. While building reference docs for an SDK I support, one of the APIs failed due to some conflicting visibility conditions. I was jumping the gun on writing the release notes before I had all the launch entry info and Gerrit previews, so I ...
Last year I had a goal of getting down to bug zero and started a whole series on this quest. If this is the first you’re hearing of this goal, bug zero really means clearing out all doc requests (~JIRA tickets), finishing them. It’s similar to the idea of inbox zero, but with work. I actually hit a brief moment where I hit bug zero, and I felt pretty accomplished. But within 1 or 2 days of clearing out that bug queue, it filled back up to 10 ...
I don’t entirely understand my relationship with coffee, but I think I have some character flaws that could be advantageous in some situations and disadvantageous in others. In some areas of my life, I’m an all-or-nothing person. This seems to be true with coffee. When I’m drinking coffee, I can’t seem to stop myself from drinking 3-4 cups a day. Before long, I can sense my body basically becoming desiccated (from the way coffee acts as a diur...
This is a recording of the AI Book Club discussion of Dan Wang's Breakneck: China's Quest to Engineer the Future. Our discussion tries to tie some of the book's themes to AI (to align with the book club's theme), but only in places where it makes sense. Some topics we discuss include social engineering, electric vehicles, contrasting energy infrastructures and the ability to power AI compute, mass surveillance networks, the differences between America's lawyerly society and China's engineering state. Fortunately, one of the book club members had recently been to China and could share firsthand experiences and impressions of cities like Shenzhen and Beijing. Among many observations, she describes the tech fatigue of everyday life, where everything (even prices at stores) requires you to use an app.
After receiving a letter from the IRS stating that I owed more taxes on a previous year, I used AI to identify the issue -- a missing cost basis on stock sales. I then successfully disputed the notice, and ultimately claimed a sizable refund by carrying over capital losses. AI tools like Claude and Gemini have become surprisingly capable at analyzing uploaded tax returns and guiding novices like me through complex scenarios.
In this podcast, I chat with Larah Vasquez and Fabrizio Ferri-Benedetti about using skills to extend AI capabilities, the future of agentic engineering, local models like Qwen and Gemma, and whether the tech writer role is shifting into automation architecture. We get into the memory problem in LLMs (and why some of us actually prefer the no memory to extended memory), the progression from prompt engineering to context engineering to compound engineering to orchestrating whole agent systems, and how skills are quietly forcing engineers to write down knowledge they'd never documented before.
I recently gave a presentation to students and faculty in person at Louisiana Tech University on March 30, 2026, focusing on what I call the cyborg model of technical writing. The idea is that the emerging model for tech writing isn't one in which AI replaces tech writers but rather one in which AI augments tech writers. Tech writers interact with AI in a continuous back-and-forth, conversational, iterative manner. This post contains the recording, slides, transcript, summary, notes, and more from my presentation.
In this podcast, I chat with two professors — Nupoor Ranade (Carnegie Mellon) and Jeremy Merritt (James Madison University) — about how AI is reshaping the technical writing profession from the academic side. We discuss dropping enrollments, misconceptions about what tech writers do, historical parallels to past disruptions, agentic AI and organizational restructuring, the cyborg model of human-machine collaboration, and how academics and practitioners can bridge the divide to solve real problems together.
This is a recording of our AI Book Club discussion of If Anyone Builds It, Everyone Dies: Why Superhuman AI Will Kill Us All by Nate Soares and Eliezer Yudkowsky, held March 15, 2026. Our discussion touches on a variety of topics, including whether the book's use of parables strengthens or weakens its argument, the question of whether AI can develop genuine intentions, the competitive dynamics that prevent any single company from pumping the brakes, the limits of recursive self-improvement, and what ordinary people should make of wildly conflicting predictions from leading AI thinkers. This post also includes discussion questions, key themes, and a full transcript.
I recently gave a presentation titled Automation Engineering 101 for Tech Docs at the Write the Docs West Coast Supermeetup. I was one of two presenters. The talk covers seven principles for designing repeatable doc processes that AI can execute, using release notes automation as a running example. This post has the recording, slides, transcript, and a narrative summary of the talk.
If you create content and share it with people around you, whether it's blog posts and podcasts on the web, or educational offerings internally at your company, you become much more visible to those around you. That visibility can be helpful in opening doors and expanding opportunities.
In this podcast, Fabrizio Ferri-Benedetti (passo.uno) and I chat with Manny Silva (instructionmanuel.com), head of documentation at Skyflow and author of Docs as Tests. Manny is working on a follow-up book that incorporates AI, covering validated generation, trusted agents, and self-healing documentation.
