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  • Coding Culture: When Will AI Make Systems More Efficient?

    I’ve adopted AI. Full stop. I’ve gone through a journey since my last post. At first, it was enough to adopt agentic engineering practices and use AI-assisted development tools to write helper scripts, review PRs, and accelerate my engineering. Then I looked at the things that interrupt or steal time unexpectedly, and tried to automate them. I’ve reached the point where anytime I’m manually interacting with a system – a form, a spreadsheet – I’m wondering why it wasn’t automated in the first place.

    What I’m learning is that efficiency in software development using AI tools highlights organizational inefficiencies as engineering bottlenecks are removed. Why are so many company processes manual or Excel-based? Why do I need to read and comprehend an email about the access required for my team to adopt a new tool, instead of the tool and the access being set up for us? Why is there so much process friction that I’m submitting helpdesk tickets to correct configuration errors, request access, or set up new pipelines multiple times per week?

    Photo by John Cameron on Unsplash

    There’s a debate around essays like “Code has always been the easy part“. Some developers claim that the cost of entry was always high and the need to stay technically current was demanding. I never found that to be the case, professionally. I always found that changing leadership, lack of business requirements, frequent pivots, and organizational inefficiency were the biggest bottlenecks to product delivery. Code was always easy; systems were hard.

    So, as I read about engineering groups shrinking and two-pizza teams standardizing around one-pizza teams, I wonder whether the organizations will shrink, too. As a middle manager, I worry about the future. But I also realize that system problems, especially at very large companies, were always my biggest bottleneck as an engineer. If AI helps us collapse bureaucracy so that the people filling out Excel spreadsheets, Google Forms, or IT helpdesk tickets can automate away the need for those systems, we’ll see a massive productivity boost across industries.

    Coding was always the easy part. Onboarding is hard. QA is hard. Shipping products is hard. We’ve made the easy part easier. It’s time to focus on the harder parts.

  • Let Your Hair Down: AI as a Productivity Detour

    Let Your Hair Down: AI as a Productivity Detour

    I was reading Savannah Sullivan’s post on taking your own profile picture for LinkedIn when I thought, “I bet AI can do a great job at this.” And I was right. It just depends on your definition of great.

    I took a selfie with my webcam and asked Google’s Nano Banana to replace my background with one from the Pacific Northwest. After all, my basement is boring, and I love living here.

    Not bad, right? But I noticed that I looked “pasted” onto the background. I wondered how I could achieve feathering with an AI model. Maybe if I added some hair growth (like a quarter inch) the model would better blend the foreground and background. So I prompted, “Add three weeks of hair growth.”

    Now that’s a dude from the Pacific Northwest!

    I had a good laugh and sent the picture to my sister. Then I thought about how to refine the prompt. Obviously three weeks of growth is too much hair. Maybe try twelve hours? Six? I wondered how many iterations of prompts I’d need to go through, waiting for an image to pop out, fully formed, from the other end. Three? Four? More?

    Finally I asked the obvious question: Is this really something worth spending all this time on?

    Last July, METR released a study showing that developers using AI coding assistants felt more productive. They enjoyed using the tools and guessed that they were 20% faster.

    But the study showed that the developers were 19% slower at completing the work. That’s a 39 percentage point gap in perceived vs. actual productivity.

    Personally, working with AI agents has introduced a joy to software development that I haven’t felt in years. The genie is out of the bottle, and it’s hard to imaging these tools going away. The real challenge is learning how to use them well.

    So if you find yourself spending hours refining a prompt for a one-off task, stop and consider whether you should put your figurative phone on a bookcase and snap that photo yourself.

    And finally, per my sister’s suggestion, here’s the result of sending the last image to Wan 2.5 with the prompt: “Make my hair blow in the wind.” Turn your sound on if you love wildlife.