Five-Level Agent Progression
Place an agent on a six-step capability ladder. This makes the target level of independence, and the safety checks needed to reach it, clear before anyone builds.
Description
A six-step ladder for how capable an AI agent is. The steps run from Level 0, fully manual, up to Level 5, fully autonomous, with rule-based, automated, and workflow stages in between. A team picks a target step based on how risky the task is and how much value it brings. To climb a step, the lower step's safety checks must be in place and the agent must pass its tests. This rates the agent as a whole, not one action at a time. Teams use it to agree on what 'done' means before they start building.
When to apply
Use this early, when you are scoping an agent project. It helps most when people disagree on how independent the system should be, or when you are planning a roadmap that spans several quarters. It also works as a look-back tool: 'we said L4, we shipped L2.5'. Don't apply it once building is underway and the per-action gate (crawl-walk-run) is the right tool. The ladder is for planning, not for runtime control.
What it involves
- Map tasks to candidate levels
- Declare a target level per task or system
- Define prior-level guardrails as preconditions
- Build to one level above current
- Gate advancement on evidence
- Revisit target level on portfolio shifts
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Diagram, neighbourhood map, code examples, related patterns and full provenance.