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Engineering Governance for AI Agents

Continuous Agentworthiness

AI agents act with speed, scale and autonomy. Like aircraft, they must be continuously monitored, maintained and governed to remain fit for their intended purpose — not certified once and trusted forever.

A lifecycle framework borrowed from aviationBy Satya Neerupudiv1.0 · 2026
Definition

Continuous Agentworthiness is the ongoing process of ensuring that an AI agent remains authorized, secure, traceable, compliant, bounded and fit for its intended purpose throughout its operational lifecycle.

01

The eight pillars

Each pillar maps to something aviation already does well. Two — Agent Directives and Grounding / Return to Service — are where the framework earns its keep.

1

Agent Registration

≈ Aircraft Registration

Define purpose, owner, risk classification and operational boundaries.

2

Identity & Credentials

≈ Certificate of Airworthiness

Issue unique identity, credentials, certificates and secrets securely.

3

Authorization & Access Control

≈ Part-21 Design Changes

Grant least-privilege access to data, tools and systems.

4

Configuration Control

≈ Continuing Airworthiness Monitoring

Control and track changes to prompts, models, tools, data sources and workflows.

5

Monitoring & Observability

≈ Continuing Airworthiness Monitoring

Continuously monitor behavior, performance and interactions.

KEY
6

Agent Directives

≈ Airworthiness Directives

Issue mandatory directives, policies and updates (like ADs), with proof of closure.

7

Incident Reporting

≈ Occurrence Reporting

Capture and classify incidents, anomalies and near-misses.

KEY
8

Grounding & Return to Service

≈ Aircraft Grounding

Quarantine or disable agents when risk is unacceptable. Return to service only after validation.

03

Why aviation, why me

I spent 25 years keeping aircraft fit to fly. Aviation already solved this class of problem — with decades of regulatory rigor — and almost nobody is translating it into AI governance.