How to Plan a Safe First AI Agent for a Marketing Task

Before allowing an AI agent to carry out steps, write down its boundaries. Define one job, the inputs it may use, the tools and actions it may access, when it must stop, what it should do when something goes wrong and where a person must approve the result.

In this article, “safe” means planned with explicit boundaries. A boundary note is a planning aid, not a guarantee that an agent will behave safely, accurately or reliably.

What is an AI agent?

For this article, an AI agent is a system that receives an objective and can carry out one or more steps using defined tools or actions. That is a practical working definition, not a universal technical standard.

The exact meaning depends on the platform. For example, OpenAI’s current Agents SDK guidance describes agents as applications that can plan, call tools, collaborate across specialists and keep enough state to complete multi-step work. Anthropic’s tool-use guidance describes model interactions with defined tools. These are provider-specific descriptions, and their available controls and behaviour can change.

This is different from asking an AI tool for a single draft. It may also be different from a reusable Skill or a workflow map. A Skill packages instructions for a capability, while a workflow map shows stages and ownership. B5 is about planning the additional boundaries needed when a system may carry out steps through tools or other actions.

Why start with a boundary note?

A boundary note makes important decisions visible before you choose a platform or grant access. It gives you something concrete to question:

• What exactly is the agent meant to do?
• Which information is it allowed to use?
• Which actions are necessary, and which are not?
• When must it stop or ask for help?
• Who reviews or approves the result?

This is a small planning exercise, not a deployment method. A written boundary cannot guarantee that a model will follow the instructions, that an available tool will behave as expected or that every failure will be noticed. It helps identify controls that still need to be checked.

The parts to define

1. One bounded job

Describe one task in plain language. A useful boundary is specific enough that another person can tell whether a proposed action belongs inside it.

“Support marketing” is too broad. “Prepare a draft outline from approved notes” is narrower. It describes an output without granting permission to publish, contact people or change records.

2. Approved inputs

List what the agent may receive. Start with the minimum information needed for the job, such as an approved brief, a reader question or a set of generic notes.

Do not assume that information is suitable merely because it is available. Keep personal information, confidential employer material, credentials and customer data outside the boundary unless there is a separately approved need and appropriate control process.

3. Permitted tools and actions

Name the tools or actions the agent may use, then remove anything that is not necessary. A first planning note may allow the system to read supplied notes and return a draft, while excluding email, publishing, financial actions, record changes and outbound messages.

Least privilege is a useful starting point: give the system the minimum access needed for its defined job. The exact permission model depends on the platform and the organisation's controls.

4. Limits and stop conditions

State what the agent must not do and when it must stop. Examples include:

• stop if the required input is missing, contradictory or outside scope
• stop if a requested action needs permission that is not listed
• stop if an important fact or technical detail cannot be checked
• stop before sending, publishing, deleting, purchasing or changing a record
• stop when the next step would create a material privacy, legal, security or reputational concern

A stop condition should lead to a clear next action, such as asking an authorised person for a decision or returning the work with the uncertainty identified.

5. Failure response

Decide how the agent should respond when it cannot complete the task. It should say what is missing or uncertain, preserve the relevant context for a human reviewer and avoid filling gaps with invented information.

Failure response is not the same as a promise that the agent will identify every error. It is an instruction for what to do when a limitation becomes visible.

6. Human approval point

Name the point at which an authorised person reviews the work. Approval should happen before an external, consequential or irreversible action, such as publishing, sending a message or changing a live record.

The person approving the result remains responsible for making that decision. A quick approval should not become an automatic assumption that the output is accurate, relevant, authorised or suitable for its intended use.

A small illustrative boundary note

The example below is fictional and deliberately narrow. It shows the shape of a planning note, not a working agent configuration or a safety guarantee.

Notice what the note leaves out. It does not grant broad access, decide what “good” means for every situation or claim that the resulting system is safe. Those questions require further review.

Keep privacy and least privilege visible

Privacy should be part of the boundary, not an afterthought. Review the data the agent can receive, the tools it can call, the actions it can take and the records or systems it can access.

For a first marketing task, a sensible starting boundary usually excludes private customer information, confidential employer material, credentials, publishing systems and outbound messaging. If a real task needs any of these, pause for the relevant authorisation, privacy, security or specialist review before implementation.

Markdown or a written note can make a boundary easier to read and share, but it does not create permissions, protect private data or guarantee output quality. The platform and organisation still need their own controls.

What a boundary note does not prove

A boundary note does not prove that an agent is:

• safe in every situation
• accurate or free from invented information
• reliable when tools, inputs or instructions change
• efficient or better than a human-led process
• ready to deploy without testing and approval

It is also not a full workflow map, reusable Skill, deployment plan or testing framework. Those are separate design and review questions.

Your next step: write one note

Choose one recurring marketing task that can be kept small and low risk. Write six short headings:

1. Job
2. Approved inputs
3. Permitted tools and actions
4. Limits and stop conditions
5. Failure response
6. Human approval gate

Under “limits”, include at least one thing the agent must not do. Then ask:

• Does it have more information or access than the task needs?
• What happens when the information is missing or uncertain?
• What action requires a person to approve it?
• Could the task involve private, confidential or consequential information?

If any answer is unclear, keep the agent at the planning stage and resolve the boundary before considering implementation.

Further reading

• OpenAI Agents SDK, current provider-specific guidance on agents, tools and multi-step workflows.
• OpenAI safety in building agents, current provider-specific safety guidance for agent workflows.
• Anthropic tool use overview, provider-specific guidance on defined tools and tool use.
• UK Government Data and AI Ethics Framework, public-sector guidance on accountability, oversight and privacy principles.
• NIST Generative AI Profile, cross-sector risk-management guidance.