Making AI Reliable in the SDLC: The Role of Deterministic Context at Scale

This talk explores how grounding AI coding agents in deterministic, graph-based architectural context instead of probabilistic inference dramatically improves reliability. It presents concrete metrics from enterprise deployments: 50% token reduction, 2x output accuracy, and compressing a seven-year mainframe modernization to three years. Ideal for enterprise architects, AI engineering leaders, and DevOps professionals building reliable AI systems at scale.