AI software delivery · Matt Holmes

The problem

Going fast with AI usually means going sloppy. Context gets lost between sessions, generated code drifts from the product, and nothing has guardrails.

The outcome

4.5× shipping velocity in 6 months, against our own prior rate, with independent checks on every release.

Most teams treat AI-assisted building as a trade: move faster, accept more mess. We don’t. My technical co-founder and I ship real product on a small team, fast, and keep it production-grade.

Speed comes from running several AI models against one source of truth, so each works from the same product reality instead of inventing its own. Safety comes from the discipline around it. Separate AI agents build, verify and audit against that one source of truth, and I orchestrate them. Scoped checks run during development, and the release candidate must pass the full test and security gates before it ships. The independent review says no when it should: 5 of the first 9 audits on the current build came back no-go, and the work went back until it passed.

That’s how 3 of us put out the work of a much larger team without shipping fragile software.

It travels to any product company that wants this speed without giving up control of what ships.

A commit by Matt Holmes titled fix(hardening), resolve every defect the adversarial sweep found, no deferrals, followed by five itemized fixes — One of my commits, typeset from the repository. An independent sweep found defects the automated gates had passed. All fixed, none deferred.