Ship With Agents

Ship with agents.

Four ways to work with an engineering team that wants agents in production and not in demos: find where agents actually pay off, ship one workflow with them, teach your team the method, or keep the agents you already run measured.

Talk to us about your team

First, the honest part.

This line is proven on our own product, not yet on a published client result. We would rather say that than oversell it. The client outcome numbers are not in yet, and we will not pretend otherwise.

We could publish a percentage. Everyone else does. We would have to make it up, so we will not. What we can do instead is show you the system, running, and open any part of it you want to read.

The problem.

Your engineers are experimenting with AI coding, and it is not becoming reliable, repeatable production practice. Two people get remarkable results and nobody can say why. There is more code and less trust in it. Review has quietly become the bottleneck that shipping used to be. And nothing is measured, so the spend is defended on mood rather than on evidence.

What we actually sell.

Not agents. Anyone can wire an agent this year. What is hard, and what holds up six months later, is the delivery system around them: the stages, the contracts between them, the human gates, and the evaluation discipline that catches quality drifting before your users do. That is the thing we built, that is the thing we run, and that is the thing we hand over.

The system we run, in detail.

On TARANSIT, our own app, we run a 15-agent, ontology-grounded delivery pipeline: an orchestrator, an architect, a planner and a developer, passing defined artifacts between stages, with a verify loop capped at three revise rounds, 16 enforced entity types across a knowledge layer of more than 1,140 cross-linked entity files, human approval gates at every bounded step, and an evaluation set with a minimum of 20 ground-truth rows scored by a calibrated judge. It ships real features on a real product. It is capability proof, and it is not a client outcome metric.

Four rungs, from cheapest to deepest.

The recommended path.

Start with the diagnostic. It is deliberately cheap, it is one to two weeks, and it is the only rung that can tell you the answer we are willing to give for free afterwards: that for your team, right now, it is not worth doing. Everything above it is better bought once you know which workflow you are buying it for.

What we do not do.

We do not operate your agents in production, take on-call, or run an incident rota. We do not sell a recorded course or a licensed curriculum. We do not run enterprise AI programs with a procurement track and a steering committee. All three fail the same way: they need a vendor who is permanently available, and we are one person who works with two or three clients at a time. Saying so up front is cheaper for both of us than saying it in month three.

For you if: you lead engineering at a technically-mature team, you have tried AI coding, and you want it to hold up in production.

Not for you if: you have never tried it (there is no felt pain yet), you want someone else to own the build, or you want an outside team to run it for you afterwards.

Different problem?

If the constraint is not shipping speed but knowing what is worth shipping, that is the other half of what we do, and it usually sits with your product lead rather than with you.

See the growth practice