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5 articles from Crelis on Guardrails. Most recent: “Agentic AI Controls: A Working Definition”.
Agentic AI controls are the limits, checks, approvals, and records that decide what an agent may do before it changes money, data, access, or records.
An LLM judge can return a different verdict on the same facts tomorrow; a deterministic policy engine returns the same decision each time and can name the rule that made it — that difference decides w
The gap between an AI's proposal and an enterprise's permission is where catastrophic liability lives. Trust is a systemic vulnerability. You recognize that LLM agents exhibit unpredictable emergent b
Ungoverned AI agents are not assets. They are liabilities. Without a verifiable governance layer, your production models operate in a vacuum of accountability.
An autonomous agent's mandate is only as strong as the infrastructure that constrains it. Accountability for unauthorized actions is a matter of architectural integrity, not better model training.