AI agents need business context and authority

An agent needs to understand the business it acts for

An AI agent may know how to draft an offer, update a record or call a tool. To do that work appropriately for a particular business, it also needs to know which agreement applies, what has changed and what it is allowed to decide.

This is a different problem from producing a fluent answer. A technically valid action can still conflict with a current customer commitment or an approval requirement. Giving the agent more tools increases what it can do without necessarily improving its understanding of what it should do.

Our view is that organizations need to develop context and authority together. Context makes an action better informed. Authority sets the boundary within which it may proceed.

Current context is more useful than a longer standing prompt

Anthropic’s work on context engineering treats the information available to a model as something that must be selected and maintained carefully. Relevant context matters; simply adding more material is not a guarantee of better behavior.

For business work, the information can change while the agent’s instructions remain the same. A customer agrees new terms. A supplier withdraws an option. A reviewer adds a condition. The agent needs a way to obtain the current position when the task requires it.

A living map is useful here because it can connect those updates to the work they affect. The agent can request the relevant agreement and decision history instead of relying on someone to keep copying the background into its prompt. The returned context should still make uncertainty, source access and unresolved conflicts clear.

Sources: [1]

MCP provides a connection, not a business decision

The Model Context Protocol defines a common way for AI applications to connect to external data and tools. Its specification includes ways to share context and expose capabilities. This makes it easier to build connections between an agent and the systems supporting its work.

The existence of that connection does not answer whether a particular action is appropriate for the business. A tool can be available while a proposed use still needs a rule check or someone’s approval. Read access to a customer record is also separate from permission to change that customer’s terms.

For Orcinta, MCP is an important route for authorized agents to request operational context. Governing an action requires an additional practical condition: the execution path must call the required check and honor its result before proceeding.

Sources: [2]

Place the check before the consequential action

Anthropic’s earlier guidance on building agents emphasizes clear stopping conditions, testing and human oversight where needed. NIST’s AI Risk Management Framework adds the organizational requirements of responsibility and oversight. Together, they reinforce why an agent rollout needs more than a successful demonstration.

A business can express a rule in plain English, review it and attach it where it belongs. A request covered by that rule can then be held when a required condition is missing. If a qualified person must approve an exception, they need the proposal and its supporting context before deciding.

The distinction between in-path control and later observation must remain visible. If an agent acts before its activity reaches Orcinta, the record can support investigation. It cannot make that completed action wait retroactively.

Sources: [3][4]

Retain the evidence that makes oversight credible

After an action, the business needs to know which agent made the request, which rule version applied, who reviewed it and what the connected tool confirmed. A later edit to the agent or its rules should not rewrite that history.

This is useful to the team managing the agent and to an auditor reviewing its operation. A scoped packet can bring the related records together so the review spends less time chasing separate logs and more time examining what they establish.

It also needs to retain the limits. Approval is not proof of execution. A sent offer is not proof of customer acceptance. Events outside the connected systems or review period remain outside the account.

We think these are the foundations of useful agent oversight: current business understanding, explicit authority and a record that connects the decision to the outcome. With those foundations, a business can expand automation while keeping responsibility understandable.