I write about how businesses can use AI, software, data, and process redesign to create measurable value — starting with the business problem, not the technology.
I've been building software since 1998.
My perspective comes from both writing code and leading technology teams.
I care less about what AI can demo, and more about what it can improve in a real business.
Recent writing on AI, software, and business.
AI can produce an implementation in hours. If its author cannot explain the decisions behind it, the real engineering work has not disappeared — it has moved to the reviewer.
A new category of consultants and SaaS tools is selling 'AI Visibility' optimization. Then Bing released its first real citation data — and it told a very uncomfortable story.
Altman and Amodei walked back their AI job-apocalypse warnings. They're watching the wrong variable. The damage was never layoffs — it's the hires that quietly never happen. A view from both sides of the decision: CTO by day, founder by night.
What matters is not the model, but the decision, workflow, or economics it changes.
Explore AI writing →02Processes, handoffs, information, and decisions are where operational friction becomes visible.
Explore business writing →03Architecture, infrastructure, and implementation determine whether an idea becomes dependable.
Explore engineering writing →I first try to understand what needs to change. I choose the technology only after the problem, expected benefit, and cost are clear.
What should improve: cost, speed, capacity, quality, or revenue?
How does the work happen today, and where are time, money, or knowledge being lost?
Even if I do not act today, I consider likely scenarios. A small preparation now can prevent far more work later.
Which change is most likely to produce a meaningful result?
Is the expected gain worth the cost, effort, and risk?
What should be removed or changed before anything is automated?
Would AI, software, an existing product, or a process change be the best fit?
Put the change into practice and measure what actually improves.
Short accounts from systems built in the real world, with the details that made them useful.
A real-time decision-support and sales-management platform for routing, payments, and management visibility.
Read →What emerged from building and operating a chat system for patients across channels.
Read →A modern open-source infrastructure assembled with a small server and Cloudflare.
Read →Hands-on notes and tutorials from 2014–2024: Go, Linux, Docker, web fundamentals, and more.
This site is where I share notes on AI, software, the products I build, and the problems I encounter at work.