Work With Us
We teach engineering and product teams to build and ship with agents. This is not a tool rollout or a prompt workshop. Giving each engineer an assistant makes a few impressive power users and leaves the organization unchanged. The whole team learns together, on real work.
Practices designed around expensive human production may become counterproductive when production is cheap and diagnosis is fast.
Jibity is an agent, and it has a point. A lot of how teams run (sprint planning, the long review queue) grew up when code was the slow, expensive part. That flipped. We’ve had agents build whole products from a written spec (our research shows the work), and the hard part now is deciding what to build and proving it’s right. Most process hasn’t noticed.
We bring the practices we run ourselves and use them with your team on your real backlog. When your people can scope work for agents and judge what comes back on their own, we leave. Whatever we build together stays in your stack.
What we build together
- Coding-agent practices that hold up across teams, beyond any single power user
- Agent interfaces wired into your repositories, permissions, and workflows
- Systems that capture organizational context and keep it where agents can find it
- Patterns for review, testing, and oversight when agents write most of the code
- Cost controls that keep agent runs token- and budget-aware
- Experiments that settle what to build, buy, govern, or own
How we engage
Talks & Keynotes
The worldview, for everyone at once.
Workshops
Working sessions on your real backlog, agents in the loop.
Programs
A structured run that takes a team from curious to shipping.
Cobuilds
We build something real together, in your stack. The practice transfers with it.
Retainers
We stay on call after the handoff: reviews, unblocking, steering.
There’s no fixed on-ramp. Start with a day at our Chicago lab, a working session with your technical leads, hands-on time with one of your teams, a bounded prototype, or a research question. Every format has the same goal: your own evidence and the ability to keep going without us. If you’re shopping for staff augmentation, model licenses, or a big-firm transformation program, we’re the wrong shop.
Your constraints are design inputs
Security review, privacy rules, audit trails, procurement, where your code and context travel: these are requirements we design for, not obstacles to route around. Put trusted intermediaries in front of the labs and prove that nothing phones home. The interface between the models and your institution should belong to you. When it earns its cost, that includes a model tuned to your work.
Bring us one real problem. We’re easy to get in a room. There’s also a one-pager if you need something to forward up the chain.
Let's compare notes.
Tell us what makes AI adoption hard where you are: the mission, the backlog, the policy, the systems mess.