GOVERGENT

Governance and Service-Level Management for Agentic Systems

A working group for defining how autonomous AI systems are governed, measured, and held to explicit service-level commitments.

Agentic systems do more than generate outputs.

They plan, delegate, call tools, interact with external systems, make decisions, recover from failures, and operate over extended periods of time. As autonomy increases, traditional application-level monitoring and static governance controls are no longer enough.

We need a way to answer questions such as:

• What does reliable behavior mean for an AI agent?
• How should an agent's service level be defined and measured?
• Which actions require stronger guarantees than others?
• How do we express constraints, policies, escalation paths, and failure budgets?
• How should SLAs and SLOs apply to multi-agent systems?
• How can agent behavior be audited without eliminating useful autonomy?
• What happens when an agent violates a service-level commitment?

GOVERGENT exists to develop practical answers to these questions.

GOVERGENT explores specifications, patterns, metrics, and reference architectures for:

Governance and Service-Level Management for Agentic Systems

Our goal is to make agentic systems observable, accountable, measurable, and governable without reducing governance to a simple allow/deny layer.

We treat governance as an operational property of the system.

Traditional services are commonly governed through measurable commitments:

Service
  └── SLO
       └── SLI
            └── Telemetry

Agentic systems introduce additional dimensions:

Agentic System
  ├── Goals
  ├── Policies
  ├── Actions
  ├── Tools
  ├── Delegation
  ├── Decisions
  └── Outcomes
        │
        ▼
  Service-Level Commitments
        │
        ├── Reliability
        ├── Safety
        ├── Quality
        ├── Cost
        ├── Latency
        ├── Compliance
        └── Autonomy

GOVERGENT investigates how these dimensions can become explicit, measurable contracts rather than implicit expectations.

The working group is interested in areas including:

Defining measurable indicators and objectives for autonomous systems, including dimensions beyond availability and latency.

Examples may include:

• task completion rate
• successful tool execution
• policy adherence
• decision quality
• escalation rate
• intervention rate
• recovery effectiveness
• cost per successful objective
• bounded autonomy
• execution latency
• reproducibility
• trace completeness

Mechanisms for expressing and enforcing constraints on agent behavior:

• permissions
• action boundaries
• resource budgets
• tool access
• delegation policies
• human approval requirements
• escalation rules
• operational risk tiers

Governance that happens while agents are operating, not only during model development.

This includes:

• policy evaluation
• runtime controls
• dynamic authorization
• circuit breakers
• fallbacks
• graceful degradation
• intervention mechanisms
• automated remediation

Making agent behavior inspectable and measurable through:

• traces
• decisions
• plans
• tool calls
• policy evaluations
• state transitions
• outcomes
• violations
• interventions

Service-level management becomes more complex when agents delegate work to other agents.

GOVERGENT explores questions such as:

• How are guarantees propagated across agents?
• Who owns the failure budget?
• How is responsibility attributed?
• How should delegation affect trust and authorization?
• Can service-level commitments compose across agent boundaries?

GOVERGENT work is guided by a few simple principles.

Measurable over subjective
Governance should rely on observable properties wherever possible.

Runtime over static
Policies must remain meaningful during execution, not only at design time.

Explicit over implicit
Expectations should become contracts, objectives, policies, or constraints.

Outcome-aware
Successful execution is not only about whether a request completed, but whether the resulting behavior satisfied the intended objective.

Composable
Governance mechanisms should work across tools, models, agents, and organizations.

Vendor-neutral
The concepts should apply across agent frameworks, model providers, and infrastructure stacks.

GOVERGENT aims to develop work around areas such as: