loading
Loading.loading
Loading.An AI-native engineering team's default is operating fleets of AI agents in production — not occasionally prompting an in-editor copilot. The agents carry whole tasks; developers supervise at review gates, with shared context and observability they trust. The craft stays human; the throughput multiplies. It's an operating model, not a tool purchase — which is why buying more seats doesn't make a team AI-native.
A copilot-using team has autocomplete and in-line Q&A — useful, but the developer still does most of the carrying. An AI-native team has agents carry whole tasks end to end against the team's standards, with people supervising. The difference isn't which tool is installed; it's how much of the work the machine actually owns.
Four things: shared context (a source of truth the agents can navigate), observability (you can see what each agent did), review gates the seniors trust, and operators — developers trained to run fleets rather than babysit a single assistant. Take any one away and the team slides back toward copilot-with-extra-steps.
Seats scale autocomplete, not the operating model. Buying more of them gives more developers a copilot; it doesn't give the team shared context, the visibility seniors need to trust the output, or the skill to run fleets. The capability is the thing you build, not the thing you license.
Start from where the team genuinely is, build the operating layer (context, observability, guardrails) into your environment, and train your developers into the operators who run it. We augment your devs, we don't replace them — the goal is your team running this without us.
Compare the options
or have us build it — same capability, the other door