Five people answer
A product lead, an engineering lead, a platform lead, a risk and compliance owner and a sponsor. About fifteen questions each, about how teams work today.
Most large companies use AI in some steps of software delivery and not in others. The assessment gives each of the eight steps a level, shows the tools and rules around it, and sets out what to do next, in the right order.
How work arrives, is sorted and is routed.
From a need to clear rules, acceptance criteria and tasks.
Architecture, interfaces and user experience.
Code, tests and documentation.
Automated tests, security analysis and the evidence they leave.
Who reviews a change, and who decides to accept it.
Change approval, deployment and rollback.
Monitoring, incidents, fixes and upgrades.
Security, the audit trail and the knowledge agents can use are assessed inside every step, not as separate ones.
No AI in this step.
People
People use approved AI assistants. No whole task goes to an agent.
People
Agents carry out whole tasks. A person checks every output.
A person, every time
Agents work in a connected pipeline with automated checks.
People, at set points
In categories your rules allow, agents complete the work and evidence accepts each change.
A named owner per category; people handle exceptions
The system measures its own results and proposes improvements to itself.
A person approves every change to the system
The top level is not software delivery without people. At every level, a named person owns each rule and each approval, and no agent approves its own work. For critical systems, review and release stay at L3 unless your internal audit agrees otherwise.
A product lead, an engineering lead, a platform lead, a risk and compliance owner and a sponsor. About fifteen questions each, about how teams work today.
Each answer describes a practice and names what shows it: an approval log, a pipeline, a policy. We record what is declared, what is shown and what is checked.
We go through the answers with your teams in one working session. A step’s level is set by its weakest practice, so a strong tool cannot hide a gap.
You set a target per step. We check what has to come first, split large jumps into single levels and write what to build for the first one.
The AI models you already use under your cloud agreements, in your own tenant.
Dedicated model endpoints in your private cloud, with outbound traffic restricted.
European or open-weight models on your servers or a SecNumCloud-qualified cloud, with no fallback to other models.
We are not tied to any model provider. Which model does which step is decided by how each one performs on your own past work, within your rules.
Tell us how your teams build software today. We will tell you plainly whether the assessment is the right first step, and who should answer.