INDEBASE EXPLAINER
AI agent governance and controlled autonomy
AI agent governance is the set of decision rights, authority limits, approval rules, evidence requirements, revocation controls, and acceptance conditions that determine how an AI agent may act inside a real organization.
IndeBase approaches governance as a control system rather than a static policy document. The objective is to allow useful autonomy where consequences are bounded while preserving explicit human authority over actions that are high-risk, irreversible, sensitive, or outside the approved envelope.
Govern consequence, not every activity
Requiring a human approval for every small action can make autonomous systems unusable. Removing approvals entirely can make them unsafe or unaccountable. IndeBase uses bounded authority so low-risk, reversible work can proceed while consequential actions remain constrained or escalated.
Core governance controls
Governance can include authority envelopes, approval gates, stop conditions, constraint changes, revocation, escalation rules, evidence requirements, and a separate acceptance decision at completion. Persistent trusted state records the active objective, constraints, approvals, and unresolved uncertainty so the agent does not rely on conversational memory alone.
Controlled autonomy
Controlled autonomy means the AI operator may choose and adapt the path within defined bounds, but does not gain the power to redefine its own authority. The human organization can constrain, pause, revoke, redirect, or stop the work.
Related: AI agent operational control and independent AI outcome verification.