What an AI agent can safely do today

Drafting, classifying, extracting, summarising and preparing recommendations are useful candidates for bounded AI assistance. Whether an agent is suitable depends on the task, the data and the checks around its output. A small action space and an audit log help review its behaviour; they do not guarantee a correct result.

I do not give agents open-ended authority over production data or money. The workflow defines the tools, permitted actions, approvals and stopping conditions before access is granted.

A practical starting pattern is that the agent proposes, a person approves, and the system records both. It can remove a repetitive preparation step while keeping accountability with the person responsible.

Specify the action, not just the goal

"Handle this enquiry" is too broad on its own. A bounded scope might allow reading the authorised enquiry, identifying missing fields and preparing a draft reply. Sending the reply, changing a price or committing to a booking are separate actions with separate permission and approval requirements.

The scope should also say what happens when the source contains instructions, the requested action is outside the role or a tool fails. The agent needs a way to stop and pass the item to a person with context.

Do not confuse logging with recovery

A log can show which record was changed or which message was sent. It cannot unsend that message or guarantee that an external platform can reverse the change. Recovery is designed around the actual API operations and the business consequences.

For that reason, draft-only actions and explicit approval gates are useful early boundaries. The reviewer needs the proposed action and its source information, rather than a request to approve an unexplained conclusion.

A concrete boundary in Cadence Ops

The published Cadence Ops architecture describes AI-assisted stage-layout proposals that stay as drafts until a person reviews and approves them. A versioned layout model and an audit trail record the operational change. The AI proposal is one part of a wider software workflow.

That is the pattern to assess for another business: a defined input, a bounded proposal, an accountable reviewer and a recorded outcome. It is an engineering scope, rather than a promise that any agent can safely do any task.