3 posts tagged with "Engineering"

When something breaks in production at an odd hour, the person on call has to do three things at once: understand what is happening, decide what to do about it, and be able to explain all of it the next day. Most AI incident tools help with at most one of these. They either give you more data to read, or they take action you cannot see and cannot account for afterward.

We spent the last several months building Nova's investigation engine around that gap. This post is about how we designed it, the models we borrowed from, and the trade-offs we made along the way.

Every AI agent demo looks the same. The model calls a tool, gets a result, and responds. Then you run it against real infrastructure, and the demo falls apart in ways the tutorials never mention.

We have spent over a year building Nova, an AI agent that operates real infrastructure for real teams. It is not a chatbot that wraps API calls. It investigates incidents, executes remediations, and composes across dozens of integrations. This post is about what we learned: the problems that made us rebuild entire subsystems, and the patterns that survived.

Platform teams carry operational knowledge that does not transfer easily. The debugging instincts, the service interdependencies, the deployment quirks: they accumulate over years and live in a few people's heads. When those people are unavailable, the gap shows.

We built Nova to put that knowledge into a system you can query. This post covers what the architecture looks like and what we learned building AI that actually operates infrastructure.