SDLC vs. ADLC vs. ASDLC: Clarifying AI Development Methodologies

In a recent analysis, developer Remo Jansen highlights the confusion surrounding the terminology used in modern software engineering, specifically the overlapping definitions of SDLC, ADLC, and ASDLC. While the traditional Software Development Lifecycle (SDLC) focuses on deterministic systems, the Agentic Development Lifecycle (ADLC) is a specialized framework for building, testing, and governing AI agent systems. Conversely, the Agentic Software Development Lifecycle (ASDLC) refers to the practice of using AI agents as workers to build any type of software. Jansen argues that distinguishing these terms is crucial for project success. Building AI agents requires specific concerns like non-determinism and continuous behavioral monitoring, whereas using agents to build standard applications requires a well-governed ASDLC approach. By clarifying these definitions, teams can better align their methodologies with their specific development goals, avoiding the pitfalls of applying the wrong lifecycle to agent-based projects.