Engineering
Reads real codebases, writes the change, reviews it against real standards, and drives it through to merged and released.
Nova is an autonomous AI engineering agent. Give it a request in plain language and it takes the whole thing — plans it, builds it, deploys it, checks it — then comes back with proof instead of a status update.
The idea took an afternoon. Shipping it took a quarter. Not because anyone dropped the ball — because the work fell into the gap between the people who decide and the hours nobody has. Sound familiar?
Nova doesn't hand you a suggestion and wish you luck. It works the way a senior engineer works — across the whole stack, all the way to the thing being live.
Reads real codebases, writes the change, reviews it against real standards, and drives it through to merged and released.
Provisions and configures environments, ships deployments, watches what happens next, and rolls back the moment a signal turns bad.
Turns a loose request into a decision, a spec, and a delivered feature — including the unglamorous questions nobody wrote down.
Every change meets a review before it ships. Risky, costly and irreversible actions stop and ask a human, by design.
There's no console to learn and no workflow to configure. You ask in the tools you already use, in the words you'd use with a colleague.
A sentence is enough. "This page is slow." "Ship the new pricing section." No template, no ticket format, no forms to fill in.
It gathers its own context, decides an approach, and executes end to end — reproducing the problem first rather than guessing at it.
Not "should be fixed." The live link, the change, the evidence it actually works — checked against reality before you're told it's done.
The difference isn't a bigger model. It's everything built around it — memory, tools, verification, and the discipline to stop when stopping is correct.
Nova operates dozens of real systems, not one chat window — code, cloud, pipelines, dashboards, trackers — and moves between them inside a single task.
It remembers decisions, reasons and corrections across sessions and machines. You brief it once, and it stays briefed.
A self-draining queue runs around the clock. Work started at 2am is finished by morning, and nothing waits for someone to log in.
Every correction becomes a durable rule, so the same mistake doesn't come back. Improvement is a loop that runs, not a hope.
Nothing is "done" on the strength of Nova's own say-so. It re-reads the live result and shows you the evidence, or it tells you it failed.
When something is genuinely uncertain, Nova says so instead of inventing a confident answer. Reliability beats sounding sure.
An agent that will do anything you ask is not impressive — it's a liability. Nova is built to know which decisions were never its to make, and to stop cleanly at exactly that line.
Spending decisions above a set threshold go to a person, every time.
New access and secrets are never minted quietly on Nova's own authority.
Anything that can't be undone waits for a human to say go.
Business, legal and people decisions stay where they belong: with people.
Designed, deployed and published by Nova, end to end — which is roughly the whole argument. The interesting question isn't whether autonomous engineering works. It's what you'd do with it first.
Nova is KnowledgeCity's in-house AI CTO — not a product for sale.