I'm Mik Bry, a Fullstack Tech Lead and hands-on CTO. I write here about the same problems I get paid to solve: shipping web and mobile products, making trade-offs between budget, team and technology, and knowing what is safe to put in front of real users, real payments and real data.
I explain the technical parts when they affect a decision. The questions are usually simple: what does this cost, what does it buy, what does it break, and how do we know?
Topics include product choices, costs, team and leadership, applied AI, launch readiness, trust, incident postmortems and the day-to-day of running software in production — not vague thought leadership, just problems founders and teams actually run into.
Your AI agent says the build passed. That tells you the build's configured checks passed — not necessarily that sign-in works, a payment is recorded correctly, or one customer's data stays private.
Your AI-built app runs on code you never chose — most of it code you'll never even see named. Here's what that means, the AI-specific risk worth knowing about, and a safe prompt to check yours.
Your AI agent picked which outside services your app depends on — payments, email, auth, AI. Here's what to check about how those failures show up, and a safe way to verify anything alerts you.
Git keeps a history of the versions of your app that are committed. GitHub stores and shares that history online. Neither requires a command line — here's what to check, and what to ask your AI agent.
A one-question self-diagnostic for AI-built apps: could a new developer pick up your project from the docs alone, or does every quote start with a week of reverse-engineering?
An API key is a password for machines. One easy mistake is bundling a secret straight into the JavaScript your users' browsers download. Here's the F12 check, and what to ask your agent.
CI isn't a second opinion on your agent's work — the same agent may have written the tests and the CI config too. What it gives you is something narrower and just as important: the same checks, rerun the same way, every single time.
A competent AI-built product can still feel like nobody wanted it. A comparison from my own work — one project that drifted, one that converged — shows what was actually missing.