An architecture can support a website, an operating system, an automation, or an AI solution. We review its data, rules, integrations, controls, and final evidence without assuming everything needs agents.
/ REFERENCE MAP
First, let’s look at all the layers.
This isn’t a list of brands. It’s a way to know which part receives the request, which searches for information, which decides, and which records what happened.
Before using information, you need to know who is accountable for it.
To govern data is to agree on ownership, quality, lineage, access, retention, and permitted use. That foundation supports reports, software, automations, and also RAG: opening the right file cabinet isn’t enough if the contents are outdated or no one can explain their origin.
01OriginOwner · purpose · version
02PreparationQuality · classification · lineage
03Sign inIdentity · permission · validity
04UsageCite · measure · audit
Source of truth
The operational system remains authoritative; a copy or a model does not invent states.
Responsibility and access
Each data domain has owners and rules that are enforced across all channels.
Lineage and traceability
A relevant output must show which sources, transformations, and versions it used.
03
/ AGENT GOVERNANCE
Autonomy is designed; it’s not assumed.
An agent needs its own identity, a human responsible, bounded tools, and an escalation policy. Autonomy is granted by degrees, and every sensitive action must be observable, reviewable, and, when possible, reversible.
LEVEL 0Reply
No access to external systems.
LEVEL 1Check
Reads governed data with defined permissions.
LEVEL 2Propose
Prepare actions for human review.
LEVEL 3Execute
Act within limits and log evidence.
LEVEL 4Coordinate
Manages long flows with pauses, budget, and escalation.
04
/ SECURITY BY DESIGN
The model is also a risk surface.
Sensitive data
Minimization, encryption, retention, and residency by context.
Prompt injection
Untrusted content must not become privileged instructions.
Excessive permissions
Each tool operates with the minimum required identity and scope.
Incorrect answer
Evaluation, thresholds, abstention, and review in sensitive decisions.
Irreversible action
Explicit confirmation, idempotency, and compensation mechanisms.
Lack of evidence
Technical and business logs that allow reconstructing what happened.
05
/ EVALUATE AND OPERATE
What isn’t evaluated only seems to work.
BEFORE
Assessment set
Real cases, expected answers, and known risks.
DURING
Observability
Latency, cost, errors, decisions, and tool usage.
AFTER
Continuous review
Model changes, drift, incidents, and human learning.
