Start with the foundations you recognise.
An AI application still needs networking, identity, compute, storage and operational ownership. The new challenge is connecting those foundations to a system whose responses also need evaluation.
Understand the architecture
Explore the foundation, data, AI and application layers. For each layer, identify what it depends on and what can go wrong.
Explore the layersConnect information to the application.
Learn retrieval and access control
Follow a question from identity through source selection to a grounded response. Learn why source quality and permissions matter before generation begins.
Read about retrieval Work through securityObserve the behaviour.
Experiment, then inspect a project
Use the lab to compare relevant, missing and restricted evidence. Then explore the Caseworker design decisions and identify what needs testing in a real implementation.
Try the lab Read the case studyWhat would you monitor beyond infrastructure availability? Consider answer quality, evidence coverage, latency, cost and inappropriate access.
Put it into practice
Turn a familiar service into an AI design exercise.
Take an application you already understand. Add one narrow feature that answers a question using approved documents.
- Sketch the application, identity service, document store and model connection.
- Trace what happens when evidence is missing or a service is unavailable.
- Define one useful outcome and how you would test it before wider use.
A one-page architecture with a clear user task, trust boundaries, operating responsibilities and success measure.