Architecture of the governed action loop
A production agentic platform is more than a model with tools. Intent becomes a decision, a decision becomes an identity-scoped action, an action changes platform state, and telemetry feeds the next decision — with governance, observability, and human authority wrapping every step.
The governed action loop
Intent
A human or event expresses a desired outcome, not a procedure
Reasoning
The agent plans how to reach the outcome
Context
current system state
Memory
what worked before
Policy
what is allowed
Decision
A proposed action, justified and inspectable
Identity
Who is acting, on whose behalf, with what scope
Action
Execution through a platform capability, never raw infra
Platform
Golden paths, pipelines, and APIs reconcile state
Telemetry
Outcomes and action traces feed back into context
Governance
wraps every step
Observability
sees every step
Human authority
bounds every step
How to read this diagram
The spine is the governed action loop. An intent — a human request or a system event — enters the platform. The reasoning plane plans a route to that outcome, drawing on three inputs: context (current system state), memory (what worked before), and policy (what is allowed). Planning produces a decision: a proposed action that can be inspected before it runs.
Before anything executes, the identity plane answers who is acting, on whose behalf, and with what scope. Only then does the action plane execute — through platform capabilities (golden paths, pipelines, provisioning APIs), never raw infrastructure credentials. The platform reconciles state, and telemetry flows back into context, closing the loop.
Around everything run three cross-cutting planes: governance (the rules and approval workflows), observability (the traces of what was decided and done), and human authority (the escalation and approval model that keeps consequential actions in human hands).
The seven planes
Perception
How does the platform know what is true right now?
Telemetry, state, and signals become machine-readable context.
Read the plane →
Reasoning
How does an agent turn intent into a plan?
LLM-driven planning over goals, context, and constraints.
Read the plane →
Action
How does an agent change the world safely?
Execution through golden paths, pipelines, and platform APIs.
Read the plane →
Memory
How does the platform learn from every action?
Persistent, scoped record of resolutions and outcomes.
Read the plane →
Identity
Who is acting, and on whose behalf?
Attributable, scoped, time-bounded authority for every agent.
Read the plane →
Governance
What is the agent allowed to do?
Policy-as-code that validates before anything mutates.
Read the plane →
Observability
How do you see what the agent did, and why?
Traces and evidence for every decision and action.
Read the plane →
Ready for the leap?
Partner with Adventure On The Wave to build governed, agentic platform capability — architecture, guardrails, and the human authority model to match.
A strategic initiative by Adventure On The Wave