Requirements, development, testing. That lifecycle built the software industry, but it breaks down when the system you are shipping is probabilistic. Here is the eight-stage lifecycle we use to build AI systems that survive production.

AI technical debt is building up in months, not the years software debt used to take. Scattered prompts, duplicated agents, and unmanaged vector stores all carry a growing cost. This guide covers the six warning signs and the four disciplines that fix them.

Most AI projects do not fail because of a bad prompt. They fail because nobody built the engineering underneath: authentication, permissions, audit, observability, evals, token budgets, deployment and rollback. Here is what production AI actually needs.