Ten of the twelve agentic AI terms are renames. Two of them are your problem

A post on dev.to takes the "twelve must-know agentic AI terms" infographic genre and does the thing the infographics do not: it checks which terms describe something platform teams do not already run. Its answer is ten of the twelve are re-labellings and two are genuinely new ^[1], which matters because the vocabulary rarely arrives on its own. It arrives with an executive who has read the list and wants to know how soon an agent can have production access ^[2].

The translation table is unremarkable, which is the point. The ten map onto control loops, IAM, sandboxes, admission policies, change gates and schedulers ^[3]. Guardrails are admission control ^[4]. Sandboxing is what infrastructure teams have been doing to untrusted workloads since cgroups ^[5]. The agent loop that every explainer draws as perceive, plan, act, observe, repeat is the observe-diff-act-verify cycle anyone who has written a Kubernetes controller has already drawn and called something else ^[6].

Two of the translations carry an operational instruction rather than just a synonym. Tool use is an IAM question, not an AI question: an agent's blast radius is exactly the union of the credentials you handed its tools, and nothing about the model changes that ^[7]. Prompt injection is privilege escalation with a content payload instead of a binary one, and your telemetry is one of the delivery channels ^[8]. Neither of those requires new machinery to reason about. They require you to answer the credentials question before the model question, including which environments are in scope and what the audit trail actually records ^[9].

Then the part with no analogue. The post identifies the two genuinely new things as nondeterminism and unbounded runtime cost ^[10]. Nondeterminism is where the controller comparison stops paying. Give a controller the same cluster state twice and you get the same action twice, and that single property is load-bearing for most of what you know about operating control loops: it is why a controller is testable, why a stuck reconcile can be reasoned about, why a rerun is a diagnostic rather than a gamble, and why "it did something different this time" is a bug report rather than expected behaviour ^[11]. An agent given identical inputs may take a different path, usually not a wild one, but enough that reproducing a failure is no longer a controlled experiment, passing once no longer establishes that a path is safe, and post-incident analysis may bottom out at "it sampled a different token" ^[12].

That reframes a lot of existing process rather than adding to it. A change gate that assumes a dry run predicts the real run is doing less work than you think it is. The post also notes, from the agent side of the loop, that the thing judging the work has to be separate from the thing doing it ^[13].

The weaker half of the argument is cost. It is named as one of the two new problems but the material develops determinism in detail and leaves runtime spend as an assertion ^[14].

Worth watching: whether anything you are asked to approve comes with a per-run ceiling on tool calls and spend, and whether your audit trail records the tool call together with the credential it used ^[9]. If it records only that an agent acted, you have logging, not an audit trail, and the blast radius stays theoretical until an incident prices it.