Most AI coding today is one developer, one agent, one conversation at a time. That is real leverage, and it is capped by how many chats a person can babysit. Meanwhile the bill scales with every token the agent burns getting there.

YAGNI is built for what comes next. Developers stop pairing with a single agent and start managing teams of them: named agent workers with defined responsibilities and permissions, working a real queue and handing pull requests back for review. The skill shifts from prompting well to running an org well, and that is a much higher ceiling.

Every step routes to the model that step actually needs. Planning and adversarial review go to the strongest models available. Mapping, implementation, and fixes go to cheaper open weight models running on US infrastructure. The result is the same work at roughly 60% under frontier API list rates. And because we sell capacity rather than tokens, we are paid to make the loop faster, not to let it run long.

This extends your team instead of replacing it. Your engineers keep architecture, judgment, and final review, and hand off the queue nobody has had bandwidth for: vulnerability findings, dependency upgrades, flaky tests, incident triage, and the backlog items that keep getting bumped a sprint.

Teams earn their autonomy. They start in training, where a person reviews every plan and every diff, and graduate on their track record. Deploys, production credentials, and data migrations stay human held, permanently. Work comes back with a receipt tying what shipped to the number it was meant to move.

Every customer runs an isolated instance, meaning your agents, your infrastructure, your keys. Humans ride free with no per seat charges, and your existing tracker stays the source of truth.

If your developers are still working agents one at a time, come see what happens when they start running teams of them.

yagni.app

YAGNI

Org chart

Teams

Offices

YAGNI

Org chart

Teams

Offices

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