The Aegis AI Release Pipeline, End to End

Planning, pre-release quality, deploy, and monitoring. AI assists at each stage while humans make the critical decisions. The post walks through each stage and emphasizes how the pipeline differs from a typical CI/CD setup, especially in how work is scoped and how the human stays in the loop.

A ticket enters and a smaller ticket leaves, paired with a list of dependencies the team didn't notice the first time around. AI assists, but humans decide what gets scoped in. The post stresses that the unit of work is constrained at planning time, not at deploy time.

When the diff arrives, AI extends test coverage to cover what changed, runs against the regression library for adjacent surfaces, and emits a one-page risk note. The note exists so the on-call engineer has something to read, not a CI page to interpret.

Deploy is the only stage where a human is the primary actor in the critical path: the on-call reads the risk note, confirms the rollback target, and approves the release. The post says this decision was deliberately not automated because the risk of removing the human is greater than the cost of keeping them.

Anomaly detection runs against production traffic in five-minute windows, so the team sees drift before customers do. The output feeds back into stage one, planning, shown as the dashed orange line in the diagram, so monitoring signals re-enter planning explicitly rather than as an after-the-fact incident review.

Three ways the post lists: the unit of work is constrained at planning time, not deploy time; the risk note is generated rather than produced by a human at 1am; and the monitoring signal re-enters planning explicitly, not as an after-the-fact incident review.

It gives the on-call engineer something to read instead of a CI page to interpret. Generated during pre-release quality after AI extends test coverage and runs the regression library, the note summarizes risk so the human approving deploy can make an informed decision quickly.

Because the post states plainly that the risk of removing the human is greater than the cost of keeping them. Deploy is the one stage where a person is the primary actor, reading the risk note, confirming the rollback target, and approving, a deliberate choice to keep accountability with a human.