IKEVAR

Agentic AI Architecture Note

Designing secure agentic systems with explicit control boundaries

Agentic AI requires identity, tool-use governance, authorization paths, prompt-injection defenses, and evidence trails before it can safely operate near enterprise workflows.

Architecture NoteMay 6, 20268 min read

Problem

Agents can retrieve context, call tools, and influence workflows, which creates an authority problem rather than only a model-quality problem.

Architecture principle

Treat each agent as a governed workload identity. Retrieval, tool use, secrets, and mutating actions should sit behind explicit authorization and policy gates.

Control implications

  • Scope tool permissions by role, task, and data sensitivity
  • Authorize retrieval before context reaches the model
  • Require review for high-impact or irreversible actions

Architecture and implementation guidance

  • Treat agents as governed workload identities, not generic chat interfaces.
  • Create policy gates between model reasoning and external tool execution.
  • Validate retrieved context before it reaches the model.
  • Build logs that support investigation, audit, replay, and control testing.

Design tradeoffs

  • Agent autonomy versus approval and policy latency
  • Tool breadth versus least privilege
  • Rich context versus retrieval and data-exposure risk

Evidence to design for

  • Tool-call logs
  • Policy decision records
  • Context-source provenance
  • Human approval records where required

Implementation artifacts

  • Agent trust model
  • Tool authorization matrix
  • Gateway policy design
  • Prompt-injection threat model

What leadership should decide

  • Which actions may be autonomous
  • Which actions require human approval
  • What level of evidence is required for investigation and audit

What engineering should build

  • Agent identity and scoped credentials
  • Policy gates between reasoning and execution
  • Retrieval authorization and tool allowlists
  • Replayable audit telemetry

Continue from architecture thinking to action

Use the related service to understand engagement scope, the industry path to add operating context, and Evidence to inspect how IKEVAR turns architecture ideas into reviewable technical artifacts.

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