Why AI agents need decision lineage

Agents are crossing from suggesting to deciding — issuing refunds, filing tickets, changing configs. The moment an agent acts on its own, a new requirement appears: someone has to be able to explain and defend the decision. That’s decision lineage.

The production gap

Most agent pilots stall not because the model can’t act, but because the organization can’t answer for the action. Two gaps recur: agents forget across sessions, and they can’t say why they acted.

Lineage closes it

With MADB, each decision is stored with its causes. When the action is questioned, the agent replays the exact chain with trace_cause — an audit trail captured in the moment, not reconstructed later.

A precondition, not a log

Lineage isn’t a post-hoc report — it’s the substrate enforced governance is built on. Trust, explanation, and defensibility all require the causal record first. That record is live in MADB today; enforced governance is on the roadmap.