Picture a new intern walking into an organisation on their first day. You hand them small tasks, supervised. Once they handle those well, larger ones. Months later, when they have shown again and again that they can be relied upon, you hand them real authority. No one gives an intern the keys to the vault on day one. Authority is not granted all at once; it is earned along a path.
We believe AI agents should travel the same path. An agentβs authority β what it is allowed to do without oversight β should not be a fixed setting at the moment of installation. It should rise over time, backed by evidence. Authority is not a toggle flipped at the start; it is a trajectory the agent walks.
From the bottom of the path, upward
Every path has an entry point. For a new agent, this is the lowest-risk work: tasks where the cost of correction is negligible and a human operator can easily review the output. This is the bottom of the path β where the agent shows its work and its behaviour is measured.
As it climbs, two things change at once: the risk of the task grows, and human oversight shrinks. This progression is neither automatic nor time-based; it is conditional. An agent moves up a step only when it has repeatedly and stably completed the step below. The path runs upward, but every step is earned.
Evidence, not promises
This differs entirely from βtrust the AI.β Trust is not assumed; it is built. Every step is backed by evaluation: real examples demonstrating whether, at a specific level of responsibility, the agentβs behaviour is stable and inspectable. Increased authority requires increased evidence.
Because the path is evidence-based, it is also reversible. If an agentβs behaviour degrades β perhaps the underlying data has shifted or the workflow has grown more complex β its authority is lowered. This is not a failure; it is the mark of a healthy system. Just as responsibilities in a functional organisation are tuned to performance, an agentβs authority remains dynamic and accountable.
A forward-looking idea
Part of what we describe here is the direction of our design, not the claim of a finished product. The goal is clear: systems that manage authority like a path, not like an on/off switch. This view moves AI from a static tool toward something closer to a colleague that grows over time and earns trust.
Donβt gift authority on day one. Let the agent earn it along the path, the way any professional does. You read a page from the bottom upward; you climb a career step by step; and the authority of a trustworthy agent walks that same upward path.