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Value Discovery & Portfolio
Prioritize GenAI investments with defensible stop criteria and risk-aware gating, using resources on initiatives that can scale.
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Agentic AICase Study
Agentic AI with Bounded Autonomy
Enable bounded autonomy with tool governance and delegation boundaries, keeping agents’ actions safe with a controlled blast radius.
Executive Outcome
01
Governed tool use through explicit contracts and scope boundaries, reducing invalid calls and uncontrolled side effects.
02
Controlled execution for high-stakes actions through approval paths and reversible action policies, limiting blast radius.
03
Decision records and traces that support auditability, post-incident analysis, and iterative governance refinement.
Engagement focus
Tool governance and bounded autonomy controls for agentic systems.
Context
Agentic systems shift the primary risk from 'bad content' to 'bad actions.' The objective was to enable autonomous workflows while ensuring tool access is permissioned, side effects are controlled, and reasoning and execution are traceable for audit and incident response.
The Challenge
- 01Agents could generate invalid parameters or call tools outside intended operating constraints.
- 02Insufficient traceability of why actions were selected, limiting debuggability and assurance.
- 03Looping and runaway execution risked compounding errors and consuming excessive resources.
- 04Unclear delegation and confirmation boundaries increased the chance of sensitive or high-impact actions being executed without oversight.
Approach
- →Defined a tool registry with strict tool contracts covering schema, scope, idempotency expectations, and side-effect classification.
- →Established an action policy that distinguishes reversible vs. irreversible actions and routes high-impact actions through approval steps.
- →Enforced bounded autonomy through explicit delegation boundaries and risk-based execution rules.
- →Implemented decision record and trace stitching formats to capture the intent, checks, evidence, and outcomes around tool use.
Key Considerations
- Stronger constraints can reduce speed and flexibility in exchange for safety and operability.
- Tool schema and contract maintenance require ownership and discipline as tools evolve.
- Approval paths introduce latency and must be designed to minimize operational bottlenecks.
Alternatives Considered
- ✕Unbounded agents: rejected due to unacceptable operational and security risk in enterprise environments.
- ✕Hardcoded workflows only: rejected because they fail to handle unstructured inputs and evolving edge cases effectively.
Representative Artifacts
01Tool registry specification and tool contract schema
02Action policy model (auto-approve vs. human review by risk tier)
03Decision record format (intent, checks, evidence, outcome)
04Trace stitching model (plan → tool → outcome)
05Connector governance checklist (credentials, scopes, rotation, approvals)
Acceptance Criteria
Verified that agents cannot call tools outside their permitted scope and contract constraints.
Verified that irreversible actions consistently trigger the defined approval path before execution.
Verified that every tool call is preceded by a recorded decision record and enforcement checks.
Verified that recovery from tool errors is demonstrated without entering runaway loops.
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