Specification-Driven Delivery

What we do

We take a specification and decompose it before anything is generated. Features, then use cases under them, then the data model that actually supports both. Each piece small enough that a reviewer can hold it in their head and say whether it is right.

Only then does generation happen, bounded by that structure. The output is reviewed against the use case it came from rather than against a general impression that it looks reasonable.

Why unbounded generation fails

Generated code without a structure above it produces a system where nobody can say which requirement a given module serves. It passes review because it reads well. It fails eighteen months later when somebody has to change it and cannot work out what depends on what.

The failure is not the model’s. It is that nobody did the decomposition, so there was nothing to check the output against.

Where this fits

It suits teams who have a specification and a delivery date and want the speed without the maintenance debt. It also suits organisations adopting AI-assisted development who need a method their reviewers can actually apply.

We run this ourselves on backend delivery, which is how we know where it breaks. The method is the product here, and we will teach it as readily as we will run it.

WHAT THIS RESTS ON

Method in use

Run on our own backend delivery, not proposed in the abstract

Reviewable units

Every generated piece tied to the use case it came from

Maintainable after

Structure survives the handover, which is where generated systems usually fail

Questions we hear before engagements

Is this a tool or a service?

Both exist, but the method is what transfers. We can run the delivery or teach your team to, and the second is often the better buy.

What if our specification is incomplete?

Most are, and the decomposition is what exposes it. Finding a gap during decomposition costs an afternoon; finding it after generation costs a sprint.