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We run an AI-assisted SDLC on a multi-tenant SaaS platform for a client in a regulated industry, with Claude Code writing code, requirements, and tests. The agent has no permission a junior engineer would not have: three levels of CI gates and five human decision points tie every change to a requirement, a test, and a release.

When the board asks for a replatform, the first question is whether the platform is the cause at all. Think of a warehouse: messy shelving, too few staff and badly sequenced pick routes are clutter problems, fixable by reorganising and certain to follow you into any new building.

A DevOps transformation is an operating-model change: teams own software from commit to production, and delivery is measured by outcomes, not tool adoption. Pipelines, infrastructure as code and platforms are the means, not the goal.

A data readiness assessment answers one question: does the data behind a specific use case exist, can it be used legally and technically, and is it good enough? Readiness is a property of the pairing between data and use case, so the same warehouse can be ready for a dashboard and unfit for a RAG assistant.

Security architecture is the design layer that decides where trust changes, which controls guard each boundary and which risk or requirement each control answers. A set of purchased tools is not an architecture, because tools without that traceability leave gaps nobody owns.