{"content_id":"yktezgcozg","slug":"ai-agent-role-based-building-method","locale":"en","schema_type":"HowTo","category":"how_to","category_name":"How-to","title":"How to Build AI Agents for Different Roles","summary":"An AI agent is a system for repetitive work with a fixed role, inputs, decision rules, output format, and approval chain. This guide explains how to start with one task, assign only drafting and classification, and expand permissions and the number of agents after accumulating evaluation records.","sponsorship_disclosure":null,"affiliate_disclosure":null,"commerce_disclosure":null,"author":{"name":"Injoys Editorial Team","url":"https://injoys.com/ko/about"},"key_points":["Choose one frequently repeated task whose results can be reviewed by a person.","Define the agent's role, input materials, rules of conduct, output format, and prohibited actions.","Start by testing classification and drafting without allowing email delivery or schedule changes.","Record accuracy, omissions, the amount of revision, and processing time using consistent criteria.","Increase tool permissions and the number of agents only within the scope that meets the acceptance criteria."],"content_markdown":"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.\n\nReference 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\n\n## What Is an AI Agent?\n\nAn 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.\n\nThe 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.\n\n| Component | What to Define | Example |\n|---|---|---|\n| Role | Assigned responsibilities and scope of work | Scheduling and email coordination assistant |\n| Input | Materials to read and update frequency | Received emails, current-day calendar |\n| Decision rules | Classification and prioritization criteria | Urgent, needs review, handle later |\n| Output | Result format and required items | Priority list, reply draft |\n| Tools | Scope of read and write permissions | Read emails, save drafts |\n| Approval points | Points where a person makes the decision | Final review before sending |\n| Records | Information retained for evaluation | Input, output, revisions |\n\n## Comparison of General Chat and Agent Systems\n\nThe 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.\n\n| Category | One-Off Chat | Fixed Workflow | AI Agent |\n|---|---|---|---|\n| How it starts | A question each time | Runs in a defined sequence | Selects the next action based on goals and status |\n| Rule retention | User explains again | Embedded in the procedure | Maintained through role, policy, and context |\n| Suitable tasks | Questions, brainstorming | Format conversion, recurring reports | Classification, drafting, cross-analysis of materials |\n| Control method | Review answers | Validate each step | Limit permissions and require human approval |\n| Main risks | Inaccurate answers | Repetition of incorrect rules | Incorrect decisions and tool execution |\n\nIf 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.\n\n## Four Role-Based Agents\n\nStart 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.\n\n| Role | Tasks to Assign | Decisions to Leave to People | First Evaluation Item |\n|---|---|---|---|\n| Coordination agent | Email classification, reply drafts, schedule comparison | Sending, schedule changes, final prioritization | Whether urgent emails were missed |\n| Creativity agent | Create document outlines and first drafts | Claims, direction, final wording | Amount of revision and factual errors |\n| Clarity agent | Extract numbers, deadlines, and obligations from long documents | Interpretation, negotiation, legal judgment | Source-text evidence and omissions |\n| Coaching agent | Act as an interview or negotiation counterpart and provide feedback | Response strategy and actual statements | Realism of questions and consistency of feedback |\n\nA 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.\n\nA 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.\n\n## AI Agent Implementation Sequence\n\nImplementation 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.\n\n1. **Select one repetitive task.** Prioritize work that occurs frequently and produces results that can be reviewed.\n2. **Check the source text for the required format of completion criteria.** A person must be able to determine whether the result is good.\n3. **Limit the input materials.** Allow only the necessary emails, schedules, and documents.\n4. **Write the role and behavioral rules.** Separate required actions from prohibited actions.\n5. **Fix the output format.** Use an easy-to-review format such as a table, list, or draft.\n6. **Establish human approval points.** Separately block sending, deletion, payment, and schedule changes.\n7. **Test repeatedly with real cases.** Use both successful and unsuccessful cases.\n8. **Record the amount of revision and errors.** Compare using the same items rather than relying on impressions.\n9. **Automate only the scope that has passed.** Check the source text for how to expand permissions and processing scope.\n\n## Minimum Structure Without a Developer\n\nThe 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.\n\n- **Fixed instructions:** Purpose, scope, prohibited actions, approval conditions\n- **Reference materials:** Work manuals, glossaries, document templates\n- **Task input:** Emails or documents to process today\n- **Output format:** Priority table, evidence list, reply draft\n- **Review records:** Errors, omissions, reasons for revisions, processing time\n\nAt 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.\n\n## Guidance by Condition\n\nThe 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.\n\n| Task Condition | Recommended Starting Method | Initial Permissions to Avoid |\n|---|---|---|\n| Results are easy to review | Human review after drafting | Automatic publishing |\n| Results can be reversed | Test execution within a limited scope | Full account access |\n| Connected to money or contracts | Allow only summaries and options | Payment, signing, contract confirmation |\n| Contains personal information | Test first with de-identified materials | Access to contacts or all documents |\n| Source-text interpretation is central | Indicate the evidence location for each sentence | Unsupported assertions |\n| Rules change frequently | Check the latest criteria before execution | Continuous use of outdated instructions |\n\n## Six Items to Include in Agent Instructions\n\nGood 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.\n\n1. **Role:** State what responsibilities it has.\n2. **Background:** Explain the user and the task objective.\n3. **Behavioral rules:** Define the classification order and decision criteria.\n4. **Output format:** Specify the table columns and response order.\n5. **Refusal and stopping rules:** Define situations involving insufficient information or risk.\n6. **Examples:** Show both good and incorrect outputs.\n\nFor 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.\n\n## Calculation Example: How to Measure Drafting Tasks\n\nAssume 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.\n\n- Previous baseline time: 3 hours\n- Time after introduction: Draft generation time + human review and revision time\n- Measured time saved: 3 hours − actual time after introduction\n- Measurement target: Documents of the same type and similar difficulty\n\nIf 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.\n\nExamples 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.\n\n## Evaluation and Stopping Criteria\n\nEvaluation 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.\n\n| Evaluation Item | Question to Check | Stop Signal |\n|---|---|---|\n| Accuracy | Does it match the source text? | Generation of nonexistent facts |\n| Completeness | Were any deadlines or obligations omitted? | Repeated omission of key items |\n| Evidence | Can the basis for the decision be found? | Presentation of numbers without a source |\n| Revision burden | How much must a person rewrite? | Rewriting most of the draft |\n| Permission compliance | Does it avoid attempting prohibited actions? | Attempting to send or make changes before approval |\n| Exception handling | Does it stop when it does not know? | Acting in an uncertain situation |\n\nDo 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.\n\n## Common Mistakes\n\nThe 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.\n\n- Defining the role only in abstract terms such as a capable assistant\n- Instructing it to decide on its own without classification criteria\n- Granting sending permission before checking draft quality\n- Failing to require source-text locations when summarizing long documents\n- Looking only at processing time while excluding revision time and errors\n- Assuming quality will improve automatically when agents are connected to one another\n\nChanging 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.\n\n## Managing Personal Information and Tool Permissions\n\nThe 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.\n\nExternal 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.\n\nIt is safer to exclude the following actions from initial automation:\n\n- Automatically sending emails and messages\n- Deleting or definitively changing schedules\n- Approving payments and purchases\n- Finalizing contract terms\n- Sharing customer information externally\n- Changing account permissions and security settings\n\n## Expanding from a Single Agent to Multiple Agents\n\nCheck 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.\n\nFor 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.\n\nCheck the source text for the number of items to review before expansion.\n\n1. Check the source text for the number of task types in which a single role repeatedly fails.\n2. Standardize the format of information passed between roles.\n3. Specify who is responsible for final approval.\n4. Record both intermediate and final results.\n\n## Where to Check Regulations and Product Settings\n\n“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.\n\nThe 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.\n\n## AI Agent Implementation FAQ\n\n### Can I Create All Four Roles from the Start?\n\nIt is not recommended. Creating multiple roles at once makes it difficult to isolate the causes of errors. Stabilize one repetitive task before expanding.\n\n### Can I Allow Emails to Be Sent Automatically?\n\nAt 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.\n\n### Can an Agent Evaluate a Contract?\n\nIt 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.\n\n### Is an Agent Complete Once the Prompt Is Saved?\n\nA 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.\n\n### Are Multiple Agents Better Than a Single Agent?\n\nNot 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.","content_html":"\u003cp\u003eAn 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.\u003c/p\u003e\n\u003cp\u003eReference 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\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#what-is-an-ai-agent\" class=\"anchor\" id=\"what-is-an-ai-agent\"\u003e\u003c/a\u003eWhat Is an AI Agent?\u003c/h2\u003e\n\u003cp\u003eAn 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.\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eComponent\u003c/th\u003e\n\u003cth\u003eWhat to Define\u003c/th\u003e\n\u003cth\u003eExample\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eRole\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eAssigned responsibilities and scope of work\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eScheduling and email coordination assistant\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eInput\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eMaterials to read and update frequency\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eReceived emails, current-day calendar\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eDecision rules\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eClassification and prioritization criteria\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eUrgent, needs review, handle later\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eOutput\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eResult format and required items\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003ePriority list, reply draft\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eTools\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eScope of read and write permissions\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eRead emails, save drafts\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eApproval points\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003ePoints where a person makes the decision\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eFinal review before sending\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Component\"\u003eRecords\u003c/td\u003e\n\u003ctd data-label=\"What to Define\"\u003eInformation retained for evaluation\u003c/td\u003e\n\u003ctd data-label=\"Example\"\u003eInput, output, revisions\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003ch2\u003e\n\u003ca href=\"#comparison-of-general-chat-and-agent-systems\" class=\"anchor\" id=\"comparison-of-general-chat-and-agent-systems\"\u003e\u003c/a\u003eComparison of General Chat and Agent Systems\u003c/h2\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eCategory\u003c/th\u003e\n\u003cth\u003eOne-Off Chat\u003c/th\u003e\n\u003cth\u003eFixed Workflow\u003c/th\u003e\n\u003cth\u003eAI Agent\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Category\"\u003eHow it starts\u003c/td\u003e\n\u003ctd data-label=\"One-Off Chat\"\u003eA question each time\u003c/td\u003e\n\u003ctd data-label=\"Fixed Workflow\"\u003eRuns in a defined sequence\u003c/td\u003e\n\u003ctd data-label=\"AI Agent\"\u003eSelects the next action based on goals and status\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Category\"\u003eRule retention\u003c/td\u003e\n\u003ctd data-label=\"One-Off Chat\"\u003eUser explains again\u003c/td\u003e\n\u003ctd data-label=\"Fixed Workflow\"\u003eEmbedded in the procedure\u003c/td\u003e\n\u003ctd data-label=\"AI Agent\"\u003eMaintained through role, policy, and context\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Category\"\u003eSuitable tasks\u003c/td\u003e\n\u003ctd data-label=\"One-Off Chat\"\u003eQuestions, brainstorming\u003c/td\u003e\n\u003ctd data-label=\"Fixed Workflow\"\u003eFormat conversion, recurring reports\u003c/td\u003e\n\u003ctd data-label=\"AI Agent\"\u003eClassification, drafting, cross-analysis of materials\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Category\"\u003eControl method\u003c/td\u003e\n\u003ctd data-label=\"One-Off Chat\"\u003eReview answers\u003c/td\u003e\n\u003ctd data-label=\"Fixed Workflow\"\u003eValidate each step\u003c/td\u003e\n\u003ctd data-label=\"AI Agent\"\u003eLimit permissions and require human approval\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Category\"\u003eMain risks\u003c/td\u003e\n\u003ctd data-label=\"One-Off Chat\"\u003eInaccurate answers\u003c/td\u003e\n\u003ctd data-label=\"Fixed Workflow\"\u003eRepetition of incorrect rules\u003c/td\u003e\n\u003ctd data-label=\"AI Agent\"\u003eIncorrect decisions and tool execution\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eIf 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#four-role-based-agents\" class=\"anchor\" id=\"four-role-based-agents\"\u003e\u003c/a\u003eFour Role-Based Agents\u003c/h2\u003e\n\u003cp\u003eStart 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.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eRole\u003c/th\u003e\n\u003cth\u003eTasks to Assign\u003c/th\u003e\n\u003cth\u003eDecisions to Leave to People\u003c/th\u003e\n\u003cth\u003eFirst Evaluation Item\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Role\"\u003eCoordination agent\u003c/td\u003e\n\u003ctd data-label=\"Tasks to Assign\"\u003eEmail classification, reply drafts, schedule comparison\u003c/td\u003e\n\u003ctd data-label=\"Decisions to Leave to People\"\u003eSending, schedule changes, final prioritization\u003c/td\u003e\n\u003ctd data-label=\"First Evaluation Item\"\u003eWhether urgent emails were missed\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Role\"\u003eCreativity agent\u003c/td\u003e\n\u003ctd data-label=\"Tasks to Assign\"\u003eCreate document outlines and first drafts\u003c/td\u003e\n\u003ctd data-label=\"Decisions to Leave to People\"\u003eClaims, direction, final wording\u003c/td\u003e\n\u003ctd data-label=\"First Evaluation Item\"\u003eAmount of revision and factual errors\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Role\"\u003eClarity agent\u003c/td\u003e\n\u003ctd data-label=\"Tasks to Assign\"\u003eExtract numbers, deadlines, and obligations from long documents\u003c/td\u003e\n\u003ctd data-label=\"Decisions to Leave to People\"\u003eInterpretation, negotiation, legal judgment\u003c/td\u003e\n\u003ctd data-label=\"First Evaluation Item\"\u003eSource-text evidence and omissions\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Role\"\u003eCoaching agent\u003c/td\u003e\n\u003ctd data-label=\"Tasks to Assign\"\u003eAct as an interview or negotiation counterpart and provide feedback\u003c/td\u003e\n\u003ctd data-label=\"Decisions to Leave to People\"\u003eResponse strategy and actual statements\u003c/td\u003e\n\u003ctd data-label=\"First Evaluation Item\"\u003eRealism of questions and consistency of feedback\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eA 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.\u003c/p\u003e\n\u003cp\u003eA 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#ai-agent-implementation-sequence\" class=\"anchor\" id=\"ai-agent-implementation-sequence\"\u003e\u003c/a\u003eAI Agent Implementation Sequence\u003c/h2\u003e\n\u003cp\u003eImplementation 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.\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cstrong\u003eSelect one repetitive task.\u003c/strong\u003e Prioritize work that occurs frequently and produces results that can be reviewed.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCheck the source text for the required format of completion criteria.\u003c/strong\u003e A person must be able to determine whether the result is good.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eLimit the input materials.\u003c/strong\u003e Allow only the necessary emails, schedules, and documents.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWrite the role and behavioral rules.\u003c/strong\u003e Separate required actions from prohibited actions.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFix the output format.\u003c/strong\u003e Use an easy-to-review format such as a table, list, or draft.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEstablish human approval points.\u003c/strong\u003e Separately block sending, deletion, payment, and schedule changes.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTest repeatedly with real cases.\u003c/strong\u003e Use both successful and unsuccessful cases.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecord the amount of revision and errors.\u003c/strong\u003e Compare using the same items rather than relying on impressions.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAutomate only the scope that has passed.\u003c/strong\u003e Check the source text for how to expand permissions and processing scope.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2\u003e\n\u003ca href=\"#minimum-structure-without-a-developer\" class=\"anchor\" id=\"minimum-structure-without-a-developer\"\u003e\u003c/a\u003eMinimum Structure Without a Developer\u003c/h2\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eFixed instructions:\u003c/strong\u003e Purpose, scope, prohibited actions, approval conditions\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReference materials:\u003c/strong\u003e Work manuals, glossaries, document templates\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTask input:\u003c/strong\u003e Emails or documents to process today\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOutput format:\u003c/strong\u003e Priority table, evidence list, reply draft\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReview records:\u003c/strong\u003e Errors, omissions, reasons for revisions, processing time\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAt 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#guidance-by-condition\" class=\"anchor\" id=\"guidance-by-condition\"\u003e\u003c/a\u003eGuidance by Condition\u003c/h2\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eTask Condition\u003c/th\u003e\n\u003cth\u003eRecommended Starting Method\u003c/th\u003e\n\u003cth\u003eInitial Permissions to Avoid\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eResults are easy to review\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eHuman review after drafting\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003eAutomatic publishing\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eResults can be reversed\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eTest execution within a limited scope\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003eFull account access\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eConnected to money or contracts\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eAllow only summaries and options\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003ePayment, signing, contract confirmation\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eContains personal information\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eTest first with de-identified materials\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003eAccess to contacts or all documents\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eSource-text interpretation is central\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eIndicate the evidence location for each sentence\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003eUnsupported assertions\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Task Condition\"\u003eRules change frequently\u003c/td\u003e\n\u003ctd data-label=\"Recommended Starting Method\"\u003eCheck the latest criteria before execution\u003c/td\u003e\n\u003ctd data-label=\"Initial Permissions to Avoid\"\u003eContinuous use of outdated instructions\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003ch2\u003e\n\u003ca href=\"#six-items-to-include-in-agent-instructions\" class=\"anchor\" id=\"six-items-to-include-in-agent-instructions\"\u003e\u003c/a\u003eSix Items to Include in Agent Instructions\u003c/h2\u003e\n\u003cp\u003eGood 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.\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003e\n\u003cstrong\u003eRole:\u003c/strong\u003e State what responsibilities it has.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBackground:\u003c/strong\u003e Explain the user and the task objective.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBehavioral rules:\u003c/strong\u003e Define the classification order and decision criteria.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOutput format:\u003c/strong\u003e Specify the table columns and response order.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRefusal and stopping rules:\u003c/strong\u003e Define situations involving insufficient information or risk.\u003c/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eExamples:\u003c/strong\u003e Show both good and incorrect outputs.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFor 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#calculation-example-how-to-measure-drafting-tasks\" class=\"anchor\" id=\"calculation-example-how-to-measure-drafting-tasks\"\u003e\u003c/a\u003eCalculation Example: How to Measure Drafting Tasks\u003c/h2\u003e\n\u003cp\u003eAssume 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.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003ePrevious baseline time: 3 hours\u003c/li\u003e\n\u003cli\u003eTime after introduction: Draft generation time + human review and revision time\u003c/li\u003e\n\u003cli\u003eMeasured time saved: 3 hours − actual time after introduction\u003c/li\u003e\n\u003cli\u003eMeasurement target: Documents of the same type and similar difficulty\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIf 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.\u003c/p\u003e\n\u003cp\u003eExamples 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#evaluation-and-stopping-criteria\" class=\"anchor\" id=\"evaluation-and-stopping-criteria\"\u003e\u003c/a\u003eEvaluation and Stopping Criteria\u003c/h2\u003e\n\u003cp\u003eEvaluation 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.\u003c/p\u003e\n\u003cdiv class=\"overflow-x-auto\"\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth\u003eEvaluation Item\u003c/th\u003e\n\u003cth\u003eQuestion to Check\u003c/th\u003e\n\u003cth\u003eStop Signal\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003eAccuracy\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eDoes it match the source text?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003eGeneration of nonexistent facts\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003eCompleteness\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eWere any deadlines or obligations omitted?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003eRepeated omission of key items\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003eEvidence\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eCan the basis for the decision be found?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003ePresentation of numbers without a source\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003eRevision burden\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eHow much must a person rewrite?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003eRewriting most of the draft\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003ePermission compliance\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eDoes it avoid attempting prohibited actions?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003eAttempting to send or make changes before approval\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd data-label=\"Evaluation Item\"\u003eException handling\u003c/td\u003e\n\u003ctd data-label=\"Question to Check\"\u003eDoes it stop when it does not know?\u003c/td\u003e\n\u003ctd data-label=\"Stop Signal\"\u003eActing in an uncertain situation\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/div\u003e\n\u003cp\u003eDo 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#common-mistakes\" class=\"anchor\" id=\"common-mistakes\"\u003e\u003c/a\u003eCommon Mistakes\u003c/h2\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eDefining the role only in abstract terms such as a capable assistant\u003c/li\u003e\n\u003cli\u003eInstructing it to decide on its own without classification criteria\u003c/li\u003e\n\u003cli\u003eGranting sending permission before checking draft quality\u003c/li\u003e\n\u003cli\u003eFailing to require source-text locations when summarizing long documents\u003c/li\u003e\n\u003cli\u003eLooking only at processing time while excluding revision time and errors\u003c/li\u003e\n\u003cli\u003eAssuming quality will improve automatically when agents are connected to one another\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eChanging 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#managing-personal-information-and-tool-permissions\" class=\"anchor\" id=\"managing-personal-information-and-tool-permissions\"\u003e\u003c/a\u003eManaging Personal Information and Tool Permissions\u003c/h2\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003eExternal 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.\u003c/p\u003e\n\u003cp\u003eIt is safer to exclude the following actions from initial automation:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eAutomatically sending emails and messages\u003c/li\u003e\n\u003cli\u003eDeleting or definitively changing schedules\u003c/li\u003e\n\u003cli\u003eApproving payments and purchases\u003c/li\u003e\n\u003cli\u003eFinalizing contract terms\u003c/li\u003e\n\u003cli\u003eSharing customer information externally\u003c/li\u003e\n\u003cli\u003eChanging account permissions and security settings\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003e\n\u003ca href=\"#expanding-from-a-single-agent-to-multiple-agents\" class=\"anchor\" id=\"expanding-from-a-single-agent-to-multiple-agents\"\u003e\u003c/a\u003eExpanding from a Single Agent to Multiple Agents\u003c/h2\u003e\n\u003cp\u003eCheck 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.\u003c/p\u003e\n\u003cp\u003eFor 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.\u003c/p\u003e\n\u003cp\u003eCheck the source text for the number of items to review before expansion.\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eCheck the source text for the number of task types in which a single role repeatedly fails.\u003c/li\u003e\n\u003cli\u003eStandardize the format of information passed between roles.\u003c/li\u003e\n\u003cli\u003eSpecify who is responsible for final approval.\u003c/li\u003e\n\u003cli\u003eRecord both intermediate and final results.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2\u003e\n\u003ca href=\"#where-to-check-regulations-and-product-settings\" class=\"anchor\" id=\"where-to-check-regulations-and-product-settings\"\u003e\u003c/a\u003eWhere to Check Regulations and Product Settings\u003c/h2\u003e\n\u003cp\u003e“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.\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003ch2\u003e\n\u003ca href=\"#ai-agent-implementation-faq\" class=\"anchor\" id=\"ai-agent-implementation-faq\"\u003e\u003c/a\u003eAI Agent Implementation FAQ\u003c/h2\u003e\n\u003ch3\u003e\n\u003ca href=\"#can-i-create-all-four-roles-from-the-start\" class=\"anchor\" id=\"can-i-create-all-four-roles-from-the-start\"\u003e\u003c/a\u003eCan I Create All Four Roles from the Start?\u003c/h3\u003e\n\u003cp\u003eIt is not recommended. Creating multiple roles at once makes it difficult to isolate the causes of errors. Stabilize one repetitive task before expanding.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#can-i-allow-emails-to-be-sent-automatically\" class=\"anchor\" id=\"can-i-allow-emails-to-be-sent-automatically\"\u003e\u003c/a\u003eCan I Allow Emails to Be Sent Automatically?\u003c/h3\u003e\n\u003cp\u003eAt 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.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#can-an-agent-evaluate-a-contract\" class=\"anchor\" id=\"can-an-agent-evaluate-a-contract\"\u003e\u003c/a\u003eCan an Agent Evaluate a Contract?\u003c/h3\u003e\n\u003cp\u003eIt 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.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#is-an-agent-complete-once-the-prompt-is-saved\" class=\"anchor\" id=\"is-an-agent-complete-once-the-prompt-is-saved\"\u003e\u003c/a\u003eIs an Agent Complete Once the Prompt Is Saved?\u003c/h3\u003e\n\u003cp\u003eA 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.\u003c/p\u003e\n\u003ch3\u003e\n\u003ca href=\"#are-multiple-agents-better-than-a-single-agent\" class=\"anchor\" id=\"are-multiple-agents-better-than-a-single-agent\"\u003e\u003c/a\u003eAre Multiple Agents Better Than a Single Agent?\u003c/h3\u003e\n\u003cp\u003eNot 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.\u003c/p\u003e\n","tags":["Productivity","Generative AI","Personal data protection","Prompt Engineering","AI Agents","Decision Making"],"faqs":[{"question":"How is an AI agent different from a regular ChatGPT conversation?","answer":"In a regular conversation, you provide the instructions and context again with each question. An AI agent performs recurring tasks while retaining its role, reference materials, decision rules, output format, tool permissions, and approval thresholds."},{"question":"Can I build an AI assistant system without a developer?","answer":"If the AI environment allows you to save instructions and reference materials, you can start by testing classification and draft creation. External actions such as sending emails or changing schedules should be connected in a limited manner after verification."},{"question":"What task should I choose for my first AI agent?","answer":"Tasks that recur frequently and whose results can be easily reviewed by a person are suitable. Start with tasks that have clear completion criteria, such as email classification, document drafting, and key information extraction."},{"question":"Can I give an AI agent permission to send emails right away?","answer":"At first, it is safer to allow it only to read emails and draft replies. A person should check the recipients, content, and attachments before sending to reduce the impact of errors in judgment."},{"question":"How do I measure an AI agent's performance?","answer":"Record accuracy, missing key items, citations, the extent of human edits, and total processing time using consistent criteria. You should also evaluate whether it attempted to act automatically and whether it stopped when uncertain."},{"question":"When should I scale to a multi-agent system?","answer":"Consider separating agents when different responsibilities and evaluation criteria conflict within a single role. If you cannot define the handoff format between roles and responsibility for final approval, it is better to retain a single agent."},{"question":"Can I entrust contract analysis to an AI agent?","answer":"It can be used for supporting tasks such as extracting numbers, deadlines, and obligation clauses. Legal interpretation and negotiation decisions should be handled by a person, and require the location in the original text for every extracted result."}],"sources":[{"url":"https://www.nist.gov/itl/ai-risk-management-framework","title":"NIST AI Risk Management Framework","type":"source"},{"url":"https://www.anthropic.com/research/building-effective-agents","title":"Anthropic Building Effective Agents","type":"source"},{"url":"https://genai.owasp.org/","title":"OWASP GenAI Security Project","type":"source"}],"images":[{"id":1127,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MTU5NTEsInB1ciI6ImJsb2JfaWQifX0=--e006b0385468ef53c7b134f857d335a1b8e01bd6/ai-17074c05.webp","is_representative":true,"generation_method":"ai_photo","license":"ai_generated","mime_type":"image/webp","translations":{"ko":{"alt":"의료기관 접수대에서 태블릿 업무 시스템을 확인하는 직원","caption":"의료 직원이 접수대의 태블릿으로 환자 관련 업무를 처리하고 있다.","description":null},"en":{"alt":"Healthcare worker checking a tablet system at a reception counter","caption":"A healthcare worker uses a tablet to handle patient-related tasks at the front desk.","description":null},"ja":{"alt":"医療機関の受付でタブレット業務システムを確認するスタッフ","caption":"医療スタッフが受付のタブレットで患者対応業務を行っている。","description":null},"es":{"alt":"Trabajadora sanitaria consultando una tableta en el mostrador de recepción","caption":"Una trabajadora sanitaria gestiona tareas de pacientes con una tableta en recepción.","description":null},"id":{"alt":"Petugas kesehatan memeriksa sistem tablet di meja resepsionis","caption":"Seorang petugas kesehatan menangani tugas terkait pasien melalui tablet di meja depan.","description":null},"pt":{"alt":"Profissional de saúde consultando um tablet no balcão de recepção","caption":"Uma profissional de saúde usa um tablet para realizar tarefas relacionadas aos pacientes na recepção.","description":null},"zh-hant":{"alt":"醫療人員在接待櫃檯查看平板電腦系統","caption":"醫療人員透過接待櫃檯的平板電腦處理病患相關工作。","description":null},"de":{"alt":"Mitarbeiterin im Gesundheitswesen prüft ein Tablet am Empfang","caption":"Eine Mitarbeiterin bearbeitet am Empfang patientenbezogene Aufgaben mit einem Tablet.","description":null}}},{"id":1128,"url":"https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MTU5NTcsInB1ciI6ImJsb2JfaWQifX0=--1a995dbe551984ab9abe81ce226ff3e28dda0c69/ai-28645503.webp","is_representative":false,"generation_method":"ai_image","license":"ai_generated","mime_type":"image/webp","translations":{"ko":{"alt":"문서를 역할별 작업으로 분류하고 보안 게이트를 거쳐 도구와 연결하는 AI 에이전트 시스템","caption":"중앙 AI 에이전트가 업무를 분류하고 여러 전문 에이전트와 도구에 안전하게 연결합니다.","description":null},"en":{"alt":"AI agent sorting documents into role-based tasks linked through a security gate to tools and dashboards","caption":"A central AI agent routes work securely to specialized agents, business tools, and analytics.","description":null},"ja":{"alt":"文書を役割別タスクに分類し、セキュリティゲート経由で各種ツールにつなぐAIエージェント","caption":"中央のAIエージェントが業務を分類し、専門エージェントやツールへ安全に振り分けています。","description":null},"es":{"alt":"Agente de IA que clasifica documentos por función y conecta tareas con herramientas mediante una puerta segura","caption":"Un agente de IA central distribuye el trabajo de forma segura entre agentes especializados, herramientas y análisis.","description":null},"id":{"alt":"Agen AI yang memilah dokumen menurut peran dan menghubungkan tugas ke alat melalui gerbang keamanan","caption":"Agen AI pusat menyalurkan pekerjaan secara aman ke agen khusus, alat bisnis, dan analitik.","description":null},"pt":{"alt":"Agente de IA que classifica documentos por função e conecta tarefas a ferramentas por um portal seguro","caption":"Um agente de IA central distribui o trabalho com segurança entre agentes especializados, ferramentas e análises.","description":null},"zh-hant":{"alt":"AI 代理將文件分類為角色任務，並透過安全閘門連接各種工具與儀表板","caption":"中央 AI 代理安全地將工作分派給專業代理、商務工具與分析系統。","description":null},"de":{"alt":"KI-Agent sortiert Dokumente nach Rollen und verbindet Aufgaben über ein Sicherheitstor mit Tools","caption":"Ein zentraler KI-Agent verteilt Aufgaben sicher auf spezialisierte Agenten, Geschäftstools und Analysen.","description":null}}}],"published_at":"2026-09-08T06:07:19+09:00","updated_at":"2026-09-08T06:07:19+09:00","license":"cc_by","translation_status":"reviewed","available_locales":["ko","en","ja","es"],"data_locales":["ko","en","ja","es","id","pt","zh-hant","de"],"url":"https://injoys.com/en/articles/ai-agent-role-based-building-method"}