AI software factory vs traditional outsourcing

Outsourcing sells hours; a factory sells verified changes. What actually differs between handing a backlog to a vendor team and running it through a production line on your own codebase.

Both start the same way: a backlog your team cannot clear alone. From there the two models diverge on almost everything that matters.

What each one sells

Traditional outsourcing sells team capacity: a group of developers, billed by time, working through tickets. The AI Software Factory sells throughput of verified changes: a specification goes in, and what comes back is the change plus its tests, its traceability record, and its run log, stopped at a human gate for approval. The unit you pay attention to shifts from hours worked to changes that landed with evidence.

Where the work happens

An outsourced team typically works in its own environment and delivers into yours at intervals. The factory works in your repository and your CI from the first commit, reading your architecture before touching it so changes land where your team would have put them, following your conventions. There is no integration event, because nothing ever lived outside your repo.

How you verify what you got

With an outsourced team, verification is your review process applied to human-written code, and its depth depends on the hours you can spare. The factory ships each change with functional tests derived from the acceptance criteria, visual tests where the interface changed, and an independent check that reviews every test for loosened assertions, skipped steps, and emptied validations. Your engineer approves with the evidence in hand, inside your existing pull request process.

Who ends up owning what

With yaab, the client owns everything: code, IP, and repository. There is no vendor platform your delivery depends on afterward, because the output is standard code and tests living in your own repo and running in your own pipeline.

Where a team still wins

A factory is a production line for specified changes. Work that is mostly discovery, prototyping without acceptance criteria, or product definition still belongs with people. That is why the factory takes specifications as input: the deciding stays human, the producing gets industrialized, and the approving stays human too.

Frequently asked questions

Is an AI software factory cheaper than outsourcing?

The models price differently: outsourcing bills capacity over time, the factory turns specifications into verified changes. The economic difference shows in cost per change and in engineering time recovered for deciding and approving instead of producing and re-reviewing.

Do I need to replace my outsourced team to use a factory?

The factory works spec by spec in your repository. Teams start by bringing three specifications from the backlog and comparing what lands against their current path for the same work.

What does the factory not do?

Discovery, prototyping without acceptance criteria, and product definition. The input is a specification of expected behavior; work that cannot yet be specified stays with people.

Is there lock-in with the factory model?

The output is standard code and tests in your repository, running in your CI, and the client owns code, IP, and repository. Delivery does not depend on any yaab platform after a change lands.