As banks introduce copilots and AI agents across software delivery, a familiar architectural instinct is emerging: create a context layer. The problem is that a layer sounds passive. It suggests a place from which information is fetched. Agentic delivery requires something more active. Context has to be captured as the bank changes, assembled differently for […]

Agentic software delivery creates a control problem that conventional SDLC documentation was not designed to solve. When multiple AI agents participate across requirements, architecture, development, testing and release, the bank needs more than a record of what each agent produced. It needs a defensible record of what the agent knew, which sources it relied on, […]

An AI agent can generate a requirement, propose an architecture, modify code and create tests. None of that means it understands the bank. The distinction is becoming one of the most important design problems in AI-powered software delivery. Banking systems are full of knowledge that rarely exists in one place. Product rules sit beside undocumented […]