Utpal Das1 · The Premise (DO-178B Meets Autonomous Agents)
In airborne software (DO-178B) and industrial robotics, systems are never certified because they "usually behave well in a demo." They are certified because their failure modes are bounded, their telemetry is immutable, and their fallback states are deterministic.
As enterprise AI moves from chat interfaces to autonomous multi-agent workflows with tool-execution privileges, probabilistic drift becomes an operational hazard. Killing a misbehaving agent destroys forensic state; leaving it running risks cascading failure. We need Correctional Infrastructure for Autonomous Agents.
2 · The 4-Stage Rehabilitation Pipeline
- STAGE 01
The Flight Recorder
Deterministic Arrest
Runtime monitors evaluate strict invariants (permission boundaries, schema drift, budget ceilings, PII egress). When an agent violates policy or enters an adversarial loop, its execution thread is suspended in sub-milliseconds while a clean standby instance hot-swaps into production.
- STAGE 02
Quarantine
The Air-Gapped Sandbox
The arrested agent's complete context window, tool-call graph, memory pointers, and random seed are snapshotted into an isolated execution jail where external APIs are replaced by deterministic mock sinks.
- STAGE 03
Interrogation & Rehabilitation
Counterfactual Replay
An automated diagnostic harness classifies the root cause (prompt injection, ambiguous tool schema, context poisoning, or reward hacking) and replays 100+ adversarial mutations of the failure state to synthesize a deterministic guardrail or routing patch.
- STAGE 04
The Parole Board
Verification & Canary Release
The patched agent must pass 100% of the adversarial regression suite and survive shadow-mode canary evaluation against live traffic before earning release back into autonomous production.