Separate understanding from execution
Reading an order, suggesting a change and changing the order are different capabilities. Give each task the least access needed and keep the intended result explicit.
AI / CONTROL
Give agents work. Keep the decisions yours.
A useful AI agent needs access to act and boundaries around that access. Define those boundaries around the person, the task and the consequence of a change.
BUILT AROUND THE WORK
What this means
for your business.
Put approval where consequence increases
Customer communications, stock changes, publishing and financial work deserve an intentional policy. Agree what may run directly and what needs an owner’s decision.
Make failure a visible state
Ambiguous requests, unavailable data and failed actions need a clear response. Give the operator a route to inspect the outcome and complete the task without repeated unintended changes.
THE DETAIL IN BUSINESS CONTEXT
Two audiences. Different kinds of work.
A shopper wants help finding and buying. A merchant needs to understand and operate the business. Each journey needs its own context, access and action boundaries.
Shopper intelligence
Explore product discovery and order-support responsibilities without exposing private operator capabilities.
Merchant agents
Move from a business question to a defined task, an authorised action and a result your team can inspect.
INSPECT THE RECORDS AND DECISIONS
The permission belongs to the task.
Reading a record, proposing a change and executing it have different consequences. Give the agent a defined job and make its allowed actions understandable to the operator.
Operating concepts to inspect in your setup; this is not a wire-format schema. Exact API fields belong in the source-derived reference.
- Actor
- The person or agent initiating work.
- Business scope
- The organisation and records the actor may access.
- Task
- The specific outcome requested.
- Proposed action
- The actual change to review, not just an AI explanation.
- Approval point
- The decision required before a consequential action.
- Completion evidence
- The inspectable outcome, including failure or uncertainty.
If the request is ambiguous
Ask for the missing decision or hand the task to a person. Ambiguity should not quietly expand permission.
If execution fails
Distinguish the proposed action from the completed result. Inspect whether anything changed before retrying.
Inspect the supplied workspace.
Supplied Agora ai workspace. This capture provides interface context; the operating scenarios on this page use separately labelled sample data.
FOLLOW THE PROCESS
From the first step
to the next decision.
01
Define the allowed task
Name the role, information and permitted action.
Define the allowed task→Review the consequence→Inspect completion
02
Review the consequence
Show the proposed change and request confirmation where required.
Define the allowed task→Review the consequence→Inspect completion
03
Inspect completion
Check the resulting work and route exceptions to a person.
Define the allowed task→Review the consequence→Inspect completion
Operating walkthrough · Review the exact configuration for your business.
A CLEARER PICTURE
Good questions.
Useful answers.
Does an AI answer prove an action happened?
No. An answer, a proposal and a successful change should be distinguished in the experience.
Can developers expand agent access?
Only within the authorised integration and tool model. Review the scope and approval design with the technical team.
BUILD WITH AGORA
Your next chapter starts here.
Bring your business, your ambition and the questions that matter. Let’s explore what you can build with Agora.