I’ve sat in the chair you’re sitting in.

I started writing code sixteen years ago. Since then I’ve built systems for healthcare, fintech, agritech, logistics, and a dozen other industries. I’ve led engineering teams of three and engineering teams of sixty. I’ve shipped products that succeeded, and a few that didn’t. The pattern across all of it: the technology decisions made before the raise determined what was possible after it.

Today I run WireApps, an engineering firm where every engineer ships with AI agents as part of their daily work. Sixty people, multiple AI-native delivery pipelines, real production systems. This isn’t a side project or a research lab. It’s how modern software actually gets built when you take AI seriously.

Alongside WireApps, I’ve been a fractional CTO for multiple startups for the last eight years. That work showed me a pattern: the same issues come up in every diligence. Security gaps that nobody flagged. Architecture decisions that worked at ten customers and won’t at a hundred. Product roadmaps that quietly drift from the revenue story. Founders rarely see these issues because they’re too close to them. Investors don’t see them until it’s too late.

Amila is the practice I’ve built to solve that problem. AI-powered diligence that scans entire codebases and product surfaces in hours, paired with the kind of judgement that only comes from running the systems being assessed. For founders preparing to raise. For investors deciding to commit. Honest, fast, useful.