Shipping AI that earns its keep

The hype around AI has made it harder, not easier, to ship something useful. Every week a new demo promises the world; far fewer make it to production and stay there.

Start with the decision, not the model

We start every AI engagement by asking a deliberately dull question: what decision does this actually improve, and how will we measure it? If we can't answer that, no model will save the project.

That single question kills a surprising number of would-be AI features — and saves the budget for the one or two that genuinely move a number.

Then it's engineering, not magic

From there it's the unglamorous work: good data, honest evaluation, a human in the loop where it matters, and monitoring for drift once you're live.

The teams that treat AI as software engineering — with tests, observability and a rollback plan — are the ones still running their models a year later. The rest are rebuilding.