This week, I started back up at work after nearly 4 months on an extended paternity leave, and boy has it been a tough one! By Wednesday I was so tired that I fell asleep in the middle of eating dinner, waking up suddenly to find a half-eaten summer roll still in my hand 😵‍💫

Regardless, I’m happy to be getting back to my ‘normal’ life, whatever that will turn out to be. Hopefully, one consequence will be more posts about software leadership, as I gather thoughts during my workdays.

This week, my notes tell me I miraculously found time for the following activities and discoveries:

• Adding two books to my reading list for 2025 (on AI, on Rom-coms),
• Loving every line of Rachel By the Bay’s “Web page annoyances that I don’t inflict on you here”, and pining for a simpler, more personal web, without the ubiquitous commercial cruft,
• Reading David Crawshaw’s approach to programming with LLMs, and happily finding myself in agreement with both his experiences and takeaways (short of the ‘LLM-enhanced Go Playground’ prototype they made, of course 😛),
• Finding “Stimulation Clicker” to be an intensely provocative little game, even after I cheated through it by wiring up an auto-clicker in the browser console,
• Learning about the jank programming language (WIP), which interestingly hosts a Clojure-like language on C++ instead of the JVM,
• Playing the “CodingFont” tournament and crying joyful tears when my current go-to typeface Fira Code ended up winning 🎉 (I have terrible visual memory so I wasn’t picking it just through recognition),
• Skimming through James Shore’s “The Best Product Engineering Org in the World”, and thinking how these are largely my instincts and practices…if only I wasn’t still enjoying being at perhaps the only software consulting company I think I could do motivating and valuable work at, so I could go and try my hand at shaping a world-class product engineering org instead,
• Appreciating Ethan Mollick’s analysis of the swelling tides in AI performance, but mostly noting his parting remarks that feel all-too-disturbingly prophetic:

  What concerns me most isn’t whether the labs are right about this timeline - it’s that we’re not adequately preparing for what even current levels of AI can do, let alone the chance that they might be correct. While AI researchers are focused on alignment, ensuring AI systems act ethically and responsibly, far fewer voices are trying to envision and articulate what a world awash in artificial intelligence might actually look like. This isn’t just about the technology itself; it’s about how we choose to shape and deploy it.