Applicable (Part 2): ATTRIBUTE 1 - Applicable

These four work types do not live in separate silos. A single sprint or workday will typically contain all of them. A Planner sequencing the week will move between scheduling AI Generated code reviews, tracking an AI Augmented strategy document, noting a hiring outcome, and logging a stakeholder conversation. The framework does not require separate systems for each. It requires a single system that can see all of them clearly — and govern each appropriately. That is what Applicability means in practice: not that the framework bends to fit every context, but that it was built to hold all of them at once. There is, however, a fifth work type that sits in a category of its own — and one that organizations are encountering with increasing frequency. Agentic AI Work. An AI agent does not simply produce an artifact. It takes a sequence of actions — browsing, writing, executing code, calling APIs, updating systems, sending communications — autonomously and across multiple steps, often touching real systems before a human has reviewed anything. This is fundamentally different from AI Generated Output, where the human receives a finished artifact and decides whether to accept or reject it. With an agent, some actions may already be in motion or irreversible by the time a human is in a position to review. The governance challenge shifts from “does this output meet the standard?” to “is this process running within the intended boundaries, and when do I intervene?” WEEFAI governs Agentic AI Work by placing exceptional weight on the Definer role. Because the human cannot easily intervene mid-execution, the scope, guardrails, constraints, and acceptance criteria must be established with precision before the agent is set in motion. A vague brief that is workable for AI Augmented output — where the human shapes and redirects throughout — is not workable for an agent. The Definer’s contribution becomes the primary control mechanism.