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How to Set Up an AI Agent Team

How to Set Up an AI Agent Team — Step-by-Step Guide
  • 7
  • April

From EP.1, you now understand what AI Agents are, what they can do, and how global organizations are using them. In EP.2, we will teach you how to set up your own AI Agent team — from defining roles, choosing tools, designing prompts, to building workflows that actually work. No coding required, no programming background needed. Just follow along.

Series: Can AI Agents Be Team Members? (4 Parts)

Step 1: Define Roles — Assign Responsibilities to Each AI Agent

Just like hiring real employees, the first thing you need to do is define what each AI Agent will be responsible for. Don't create an Agent that does everything — because an AI that does everything usually isn't great at anything. Just as you need to clearly divide work between AI and humans, you need clear role definitions.

Role Responsibilities Data access Constraints
Content Writer Write articles, social media posts, emails Brand guidelines, product info, past articles No fabricated pricing data
Data Analyst Analyze sales data, generate reports Sales data, financial data No access to personal data
Customer Support Answer questions, prioritize tickets FAQ, product manuals, customer history Complex issues escalate to humans
Code Reviewer Review code, suggest improvements Codebase, coding standards No automatic deployment
Research Assistant Find information, summarize research Websites, research databases Must always cite sources
Admin Assistant Schedule meetings, summarize meetings Calendar, email, notes No sending emails without approval

Each role must have four clearly defined elements:

  1. Name — Give it a memorable name, e.g., "ContentBot" or "DataSensei"
  2. Responsibilities — Clearly specify what it must do and what it must not do
  3. Data access — Define what data this Agent can see
  4. Constraints — What it is not allowed to do, to prevent risks

Step 2: Choose Your Tools

Several platforms are available today for creating AI Agents, each with different strengths:

Platform Key strength Best for Coding required?
Claude (Anthropic) Long document analysis, detailed writing, deep thinking Research, Content, Analysis No (use Projects)
ChatGPT (OpenAI) Easy Custom GPTs creation, many plugins General tasks, Customer Support No (use GPT Builder)
Gemini (Google) Deep Google Workspace integration Admin, Email, Calendar No
Microsoft Copilot Works within Microsoft 365 Organizations using Microsoft No
Custom Agent (API) Full control, deep customization Specialized tasks, system integration Yes (Python, Node.js)

Start simple: You don't need to write code — ChatGPT Custom GPTs or Claude Projects can create functional AI Agents. Start with simple tasks and expand when you see results.

Step 3: Prompt Design — The Heart of an AI Agent

A prompt is the "instruction" that determines how your AI Agent will work — a good prompt produces excellent results, a bad prompt produces unusable output. The recommended formula is ROLE + CONTEXT + TASK + FORMAT + CONSTRAINTS:

Component Description Example
ROLE Who you are, what expertise you have "You are a senior data analyst"
CONTEXT Background and data needed "Q1 sales data is in this table..."
TASK What needs to be done, clearly stated "Analyze sales trends and summarize in 5 points"
FORMAT Output format requirements "Use tables + bullet points in English"
CONSTRAINTS Limitations, what must not be done "No fabricated numbers, cite data only"

Example System Prompt: Content Writer Agent

ROLE: You are a Content Writer for Grand Linux Solution Co., Ltd., an ERP provider

CONTEXT: Write articles about ERP, technology, and organizational management for the grandlinux.com website

TASK: Write articles on assigned topics with 3+ tables, callout boxes, and internal links to other website articles

FORMAT: HTML format, professional English

CONSTRAINTS: No fabricated pricing. Do not claim Saeree ERP has features it doesn't have

Example System Prompt: AI Accountant Agent

Example: System Prompt for an Accounting AI Agent

ROLE: You are a senior accountant specializing in TFRS and IFRS standards
CONTEXT: Help analyze accounting data from ERP systems, including balance sheets, P&L statements, and accounting tasks AI can assist with
TASK: Audit transactions, identify anomalies, summarize analysis results, recommend corrective actions
FORMAT: Tables + explanations with data-backed figures
CONSTRAINTS: No fabricated numbers. Request additional data if insufficient. Always note that tax advice requires professional consultation

Step 4: Build Workflows — Connect Agents Together

The true power of an AI Agent Team lies in connecting multiple agents together into workflows — just like passing work between team members in real life:

Example Workflow: Content Creation

  1. Research Agent gathers information and summarizes key points
  2. Writer Agent creates the article from the Research Agent's summary
  3. Editor Agent checks grammar, adjusts tone, and verifies facts
  4. Human Review approves before publishing
  5. Publisher publishes the article (automatic or manual)

Example Workflow: Customer Support

  1. Triage Agent receives the query and categorizes it (billing, technical, general)
  2. Support Agent answers basic questions from FAQ and manuals
  3. Escalation sends complex issues to human agents with a problem summary
  4. Follow-up Agent checks resolution status and sends satisfaction surveys

Step 5: Test and Iterate

Don't start with critical tasks — begin with small tasks where mistakes won't cause significant damage:

  1. Start with simple tasks — Such as summarizing documents, drafting emails, searching for information
  2. Measure results — Compare with the previous approach. Is it better?
  3. Refine prompts — Identify where AI performs poorly and fix the prompt
  4. Gradually expand — Increase complexity incrementally
KPI to measure How to measure Target
Time spent Compare work time before and after AI At least 30% reduction
Output quality Human quality rating (1-5 scale) Average no less than 3.5
Cost Subscription + API cost per month Lower than hiring for equivalent work
Revision rate % of work requiring revisions after AI output No more than 20%
User satisfaction Survey from team members using AI Agents Average no less than 4/5

AI Agent + ERP = A Complete Team

When AI Agents work together with an ERP system, the results multiply:

  • Analyze ERP data — AI Agent pulls sales, inventory, and AR data from ERP to analyze and summarize for management
  • Automatic report generation — Instead of manual monthly reports, AI Agent extracts ERP data and generates reports with insights
  • Anomaly alerts — Stock below reorder point, sales below normal, or overdue receivables
  • Help users find information — Instead of clicking through multiple menus, just ask AI "What were last month's sales?"

This is the direction Saeree ERP is developing with its AI Assistant, to provide clients with maximum benefit from AI technology in the near future.

Next EP: Real-World Examples — What Percentage of Work Can AI Agents Handle? will showcase real case studies showing what AI Agents do well, what still requires humans, and the actual results.

Setting up a good AI Agent Team doesn't start with technology — it starts with understanding your team's pain points and using AI to solve them. Start small, measure results, iterate, then expand.

— Sureeraya Limpaibul, Grand Linux Solution

References

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Saeree ERP Author

About the Author

Sureeraya Limpaibul

Managing Director, Grand Linux Solution Co., Ltd. & Founder of Saeree ERP — providing comprehensive ERP consulting and services.