Autonomous infrastructure is rapidly becoming operational reality. Modern AI systems increasingly: orchestrate distributed runtimes automate infrastructure operations coordinate cloud-native execution manage regulated compute environments execute machine-speed workflows trigger operational state changes This fundamentally changes infrastructure enforcement requirements. Traditional security systems primarily: observe execution collect telemetry inspect logs analyze behavior a

Modern AI infrastructure increasingly operates through autonomous execution. AI systems now: coordinate distributed runtimes orchestrate operational workflows automate infrastructure actions manage regulated compute processes trigger machine-speed decisions operate continuously across cloud-native environments This fundamentally changes infrastructure trust architecture. Traditional runtime security models rely primarily on: monitoring observability telemetry collection post-

Distributed AI systems are rapidly becoming operational infrastructure. Modern AI runtimes increasingly: coordinate autonomous workflows orchestrate cloud-native execution manage distributed runtime actions access regulated environments trigger operational state transitions execute machine-speed decisions operate continuously across hybrid infrastructure This fundamentally changes infrastructure trust architecture. Traditional security models primarily rely on: observability

Traditional infrastructure security was designed for environments where: humans initiated execution response cycles were slower workloads were relatively predictable centralized oversight remained possible That operational model is collapsing under autonomous compute conditions. Modern AI systems increasingly: coordinate distributed infrastructure trigger runtime orchestration manage cloud-native execution flows access regulated systems execute operational decisions automate

Modern infrastructure increasingly depends on autonomous execution systems operating across: AI inference infrastructure distributed cloud runtimes financial execution systems healthcare compute environments edge orchestration platforms autonomous operational networks regulated compute infrastructure This creates a fundamental runtime trust problem. Traditional infrastructure security architectures primarily rely on: monitoring systems observability pipelines reactive telemet

Modern infrastructure still largely operates under an unsafe runtime assumption: that execution should proceed unless something later detects a problem. This operational model was built for: human-driven systems slower execution environments centralized operational workflows reactive security architectures Autonomous compute systems fundamentally change that model. AI inference systems, distributed orchestration layers, autonomous runtimes and regulated compute environments n

EXECUTION WITHOUT VERIFICATION CANNOT BE TRUSTED Runtime integrity must remain continuously verified before, during, and after execution. Abstract RFC-EG-030 establishes the Execution Integrity Verification Protocol (EIVP) for distributed execution governance infrastructure. This specification defines mandatory integrity verification mechanisms required to ensure that execution environments remain: cryptographically verifiable operationally authoritative deterministically gov