How to Build AI Agents for Different Roles

An AI agent assistant system starts by selecting one repetitive task and fixing the role, inputs, decision rules, outputs, and approval points. At first, assign it only drafting and classification. The key is to expand permissions and the number of agents only after review records have accumulated.

Reference document: “AI Agent (Assistant) System Implementation Methodology”; check the official help documentation for the AI tool you use for the latest permission and security settings

What Is an AI Agent?

An AI agent is a system that repeatedly performs tasks in a defined role. A general conversational AI receives instructions and background information again for each question. An agent continuously maintains its role, rules, materials, and output structure.

The model is not the only component. Input materials and tool permissions are also part of the system. Human approval points and execution logs must be designed as well.

Comparison of General Chat and Agent Systems

The difference lies more in the work structure than in the intelligence of the answers. One-off chat is suitable for exploration and generating ideas. Repetitive systems require consistent rules and review procedures.

If only a fixed sequence is needed, a workflow is simpler. An agent is useful when decisions must vary by situation. Autonomy is determined by task requirements, not treated as a goal in itself.

Four Role-Based Agents

Start by selecting only the most repetitive role. Each role has different inputs and evaluation criteria. Define the scope of responsibility specifically rather than focusing on the name.

A coordination agent reads emails and calendars together. Have it prepare only reply drafts for urgent emails. During the initial stage, a person must press the send button.

A creativity agent reduces the difficulty of starting from a blank page. A clarity agent must connect required evidence to the source text. A coaching agent is suitable for practicing the same situation multiple times.

AI Agent Implementation Sequence

Implementation proceeds as a single flow from task selection through evaluation. Even without a developer, you can test it in an AI environment that stores instructions and materials. Add connections to external tools only after validation.

1. Select one repetitive task. Prioritize work that occurs frequently and produces results that can be reviewed.
2. Check the source text for the required format of completion criteria. A person must be able to determine whether the result is good.
3. Limit the input materials. Allow only the necessary emails, schedules, and documents.
4. Write the role and behavioral rules. Separate required actions from prohibited actions.
5. Fix the output format. Use an easy-to-review format such as a table, list, or draft.
6. Establish human approval points. Separately block sending, deletion, payment, and schedule changes.
7. Test repeatedly with real cases. Use both successful and unsuccessful cases.
8. Record the amount of revision and errors. Compare using the same items rather than relying on impressions.
9. Automate only the scope that has passed. Check the source text for how to expand permissions and processing scope.

Minimum Structure Without a Developer

The minimum structure is the same in a no-code setup. Put the role and behavioral rules in the saved instructions. Put actual work standards and examples in the reference documents.

• Fixed instructions: Purpose, scope, prohibited actions, approval conditions
• Reference materials: Work manuals, glossaries, document templates
• Task input: Emails or documents to process today
• Output format: Priority table, evidence list, reply draft
• Review records: Errors, omissions, reasons for revisions, processing time

At first, provide the materials manually and review the results. This makes it easier to distinguish connection errors from decision errors. After stabilization, you can connect calendar or email tools.

Guidance by Condition

The level of automation should vary according to the nature of the task. The harder an action is to reverse, the later human approval should be removed. If sensitive information is involved, restrict the input itself first.

Six Items to Include in Agent Instructions

Good instructions do not stop at abstract personality descriptions. Write actions, outputs, and stopping conditions as verifiable statements. Check the source text for the number of items below and manage them in a single template.

1. Role: State what responsibilities it has.
2. Background: Explain the user and the task objective.
3. Behavioral rules: Define the classification order and decision criteria.
4. Output format: Specify the table columns and response order.
5. Refusal and stopping rules: Define situations involving insufficient information or risk.
6. Examples: Show both good and incorrect outputs.

For example, specify three email classifications for a coordination role. Have it provide both a reply draft and the handling time for urgent emails. Clearly state that actual sending is not permitted.

Calculation Example: How to Measure Drafting Tasks

Assume that writing the first page of a document previously took 3 hours. This figure is a task example presented in the reference document. After introducing the agent, separately measure the actual elapsed time.

• Previous baseline time: 3 hours
• Time after introduction: Draft generation time + human review and revision time
• Measured time saved: 3 hours − actual time after introduction
• Measurement target: Documents of the same type and similar difficulty

If you did not measure the time after introduction, you cannot claim time savings. Even if the draft is produced quickly, the benefit may be small if revisions take a long time. Include the time spent correcting factual errors in the review time.

Examples involving 10 or 20 repetitions are provided for the coaching role. Performance cannot be judged by the number of repetitions alone. You must also record changes in responses to the same question.

Evaluation and Stopping Criteria

Evaluation is a safeguard before expanding automation. Looking only at average quality can cause you to miss rare but major failures. Record error types and the conditions under which they occur separately.

Do not expand permissions if a stop signal appears. Revise the instructions and input materials, then retest with the same cases. Keep the results from before and after the revision separate.

Common Mistakes

The most common mistake is assigning every task from the outset. If you create multiple roles simultaneously, it becomes difficult to identify the cause of failure. It is better to start with one task and check the source text for the number of outputs.

• Defining the role only in abstract terms such as a capable assistant
• Instructing it to decide on its own without classification criteria
• Granting sending permission before checking draft quality
• Failing to require source-text locations when summarizing long documents
• Looking only at processing time while excluding revision time and errors
• Assuming quality will improve automatically when agents are connected to one another

Changing the prompt alone does not solve every problem. Incorrect materials and excessive permissions are separate issues. Tool connections and the scope of data must be reviewed together.

Managing Personal Information and Tool Permissions

The risk exposure of an agent increases with the information it reads and the tools it can use. Do not connect documents or accounts that are unnecessary for the task. Read and write permissions must also be separated.

External documents may contain instructions intended to deceive the agent. Configure it to prioritize fixed instructions over commands within documents. Content from unclear sources should not be used as a basis for action.

It is safer to exclude the following actions from initial automation:

• Automatically sending emails and messages
• Deleting or definitively changing schedules
• Approving payments and purchases
• Finalizing contract terms
• Sharing customer information externally
• Changing account permissions and security settings

Expanding from a Single Agent to Multiple Agents

Check the source text for the role-count criteria used to determine whether a multi-agent structure is needed. Consider separating roles when each role has different inputs and success criteria. As the number of agents increases, handoff errors and operating costs also increase.

For example, a coordination role can set priorities. A creativity role creates drafts for the selected tasks. Check the source text for the number of results a person must review before approving the next action.

Check the source text for the number of items to review before expansion.

1. Check the source text for the number of task types in which a single role repeatedly fails.
2. Standardize the format of information passed between roles.
3. Specify who is responsible for final approval.
4. Record both intermediate and final results.

Where to Check Regulations and Product Settings

“AI Agent (Assistant) System Implementation Methodology” is not a statute or official agency notice. Therefore, it contains no official regulatory language that can be quoted verbatim. Check official help documentation for product-specific permissions and data-processing conditions.

The risk management framework can be found in the NIST AI Risk Management Framework. Generative AI security risks can be found in the OWASP GenAI Security Project. The organization’s security and privacy policies must also be applied in actual implementation.

AI Agent Implementation FAQ

Can I Create All Four Roles from the Start?

It is not recommended. Creating multiple roles at once makes it difficult to isolate the causes of errors. Stabilize one repetitive task before expanding.

Can I Allow Emails to Be Sent Automatically?

At first, it is safer to allow only reply drafts. A person must verify the accuracy and recipients. Do not grant sending permission without validation records.

Can an Agent Evaluate a Contract?

It can serve an assistive role by extracting key numbers and deadlines. Legal meaning and negotiation decisions must remain with people. Recheck any summary that does not include source-text locations.

Is an Agent Complete Once the Prompt Is Saved?

A prompt is one component. Input materials, tool permissions, and approval points are also required. Without evaluation records, it is difficult to determine whether there has been improvement.

Are Multiple Agents Better Than a Single Agent?

Not always. If the task can be handled by a single role, a simpler structure is preferable. Separate roles only when responsibilities and success criteria differ.