Evaluation-Driven Development Across the ADLC

The Agentic Development Lifecycle (ADLC) is an innovative methodology designed for the creation, deployment, and governance of autonomous systems, addressing the unique challenges they pose, which are not adequately managed by the traditional Software Development Lifecycle (SDLC). Unlike linear development models, the ADLC operates as a continuous feedback loop where evaluation (eval) is the core component connecting all phases, from design and experimentation to production monitoring and runtime intervention. Evals serve as a unified measurement substrate, enabling consistent metrics across all stages, thus transforming autonomous agents from unpredictable liabilities into reliable systems that can be defended with data. This lifecycle emphasizes the importance of using consistent metric definitions across offline experiments, CI/CD processes, and production environments to prevent metric fragmentation, which can lead to false confidence and system drift. The ADLC also advocates for embedding evaluations as runtime guardrails to block failures before they impact users, leveraging tools like Galileo's platform, which supports evaluation-driven development with features like automated failure detection and real-time guardrails.