Essays on building with AI, running agencies, and how work actually gets done. Longer thoughts that started as LinkedIn articles.
For twenty-five years I did one thing under different titles: before anything could be built, somebody had to figure out what it was supposed to be. We called it scoping, briefing, judgment, experience - we never had a clean name for it. Then AI made the skill visible, and it turned out to be the one that matters most.
One of the strange things about running a young agency is that the cost of saying no to a client is always concrete, and the cost of saying yes is always diffuse. Young agencies are not bad at saying no because they lack character - they do not yet have the operating system that makes saying no obvious. I learned this the slow way, on a project that almost ended my agency in its first year.
I currently work around 60 hours a week, more than I ever did running my digital agency, and I am less tired than I was at 40. That sounds like a paradox until you realise what changed: I stopped working Monday-to-Friday. The five-day week is the most expensive habit in knowledge work, and most employers have no idea what it is costing them.
AI has been writing most of the code I ship for a while now. Not small snippets - most of it, across multiple applications with real users. When people hear that, they assume I became a faster coder. That is not what happened. I became a different kind of worker, and the question of what is left for the human turned out to have a better answer than I expected.
For persistent expert systems, memory is not just a recall layer. It is the substrate of continuity and trust. Once an AI is expected to persist as an expert across sessions, projects, and accepted prior work, the real failures are no longer forgetting - they are identity drift, stale truths, and contradictions that never die. My paper argues these systems need a different memory architecture entirely.
You don't need the perfect project to say yes. I've said no to high-paying work that felt wrong, and yes to zero-budget projects that turned into something great. The difference is a simple rule: great people, interesting work, good money - at least two out of three must be true.
I write regularly on LinkedIn about what I'm building and learning: agency growth, AI development, product judgment, and the messy reality behind making things work.
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