CrewAI Multi-Agent Agile Scrum Kanban — ใช้ AI Agent จัดการโปรเจค Agile

CrewAI Agile

CrewAI Multi-Agent AI Agile Scrum Kanban Sprint Planning Product Owner Scrum Master Developer QA DevOps Automation LLM GPT-4

Agent	Role	Goal	Tools
Product Owner	จัดลำดับ Backlog	Maximize Value Delivery	Jira API, Analysis
Scrum Master	จัดการ Sprint	Remove Blockers, Improve Process	Board API, Metrics
Developer	เขียน Code	Deliver Quality Code	Code Tools, Git
QA Engineer	ทดสอบ	Ensure Quality	Test Framework
DevOps	Deploy Monitor	Reliable Infrastructure	K8s, CI/CD, Monitor

Agent Configuration

# === CrewAI Agile Team Setup ===

# pip install crewai crewai-tools



from dataclasses import dataclass



# from crewai import Agent, Task, Crew, Process

# from crewai_tools import SerperDevTool, FileReadTool



# product_owner = Agent(

# role="Product Owner",

# goal="Analyze user stories, prioritize backlog by business value",

# backstory="Senior Product Manager with 10 years experience in Agile. "

# "Expert at breaking down requirements into actionable stories.",

# tools=[SerperDevTool()],

# llm="gpt-4",

# verbose=True,

# allow_delegation=True

# )

#

# scrum_master = Agent(

# role="Scrum Master",

# goal="Plan sprints, track progress, remove blockers, improve velocity",

# backstory="Certified Scrum Master with expertise in Kanban and metrics. "

# "Focused on team productivity and continuous improvement.",

# tools=[],

# llm="gpt-4",

# verbose=True,

# allow_delegation=True

# )

#

# developer = Agent(

# role="Senior Developer",

# goal="Write clean, tested code that implements user stories",

# backstory="Full-stack developer with 8 years experience. "

# "Expert in Python, TypeScript, and cloud architecture.",

# tools=[FileReadTool()],

# llm="gpt-4",

# verbose=True

# )

#

# qa_engineer = Agent(

# role="QA Engineer",

# goal="Create test plans, find bugs, ensure quality standards",

# backstory="QA specialist focused on automated testing and quality gates.",

# tools=[],

# llm="gpt-4",

# verbose=True

# )



@dataclass

class AgentConfig:

 role: str

 goal: str

 tools: str

 delegation: bool

 key_tasks: str



agents = [

 AgentConfig("Product Owner",

 "Maximize Value Delivery through Backlog Prioritization",

 "Jira API, Market Research, User Analytics",

 True,

 "Story Writing, Backlog Grooming, Sprint Goal, Acceptance Criteria"),

 AgentConfig("Scrum Master",

 "Improve Team Velocity and Remove Blockers",

 "Board API, Metrics Dashboard, Communication",

 True,

 "Sprint Planning, Daily Standup, Retrospective, Velocity Report"),

 AgentConfig("Developer",

 "Deliver Quality Code on Time",

 "Code Editor, Git, Test Runner, Linter",

 False,

 "Implementation, Code Review, Refactoring, Documentation"),

 AgentConfig("QA Engineer",

 "Ensure Product Quality Before Release",

 "Test Framework, Bug Tracker, Performance Tool",

 False,

 "Test Plan, Test Execution, Bug Report, Regression Test"),

 AgentConfig("DevOps Engineer",

 "Reliable CI/CD and Infrastructure",

 "K8s, Docker, Terraform, Monitoring",

 False,

 "Pipeline Setup, Deploy, Monitor, Incident Response"),

]



print("=== Agent Configs ===")

for a in agents:

 print(f"\n [{a.role}] Goal: {a.goal}")

 print(f" Tools: {a.tools}")

 print(f" Delegation: {a.delegation}")

 print(f" Tasks: {a.key_tasks}")

Sprint Workflow

# === Sprint Workflow with CrewAI ===



# Sprint Planning Task

# planning_task = Task(

# description="Analyze the product backlog and plan Sprint 5. "

# "Select stories worth 40 story points. "

# "Consider team velocity of 38 points/sprint.",

# expected_output="Sprint 5 plan with selected stories, "

# "assignments, and sprint goal",

# agent=scrum_master

# )

#

# development_task = Task(

# description="Implement the top priority story: "

# "As a user, I want to filter products by category",

# expected_output="Implementation plan with code structure, "

# "API endpoints, and database schema changes",

# agent=developer

# )

#

# testing_task = Task(

# description="Create test plan for the product filter feature. "

# "Include unit tests, integration tests, and E2E tests.",

# expected_output="Complete test plan with test cases, "

# "expected results, and automation scripts",

# agent=qa_engineer

# )

#

# crew = Crew(

# agents=[product_owner, scrum_master, developer, qa_engineer],

# tasks=[planning_task, development_task, testing_task],

# process=Process.sequential,

# verbose=True

# )

# result = crew.kickoff()



@dataclass

class SprintPhase:

 phase: str

 agent: str

 input_data: str

 output: str

 duration: str



phases = [

 SprintPhase("Backlog Grooming",

 "Product Owner",

 "Raw Requirements, User Feedback, Market Research",

 "Prioritized Backlog with Story Points",

 "2 ชั่วโมง"),

 SprintPhase("Sprint Planning",

 "Scrum Master + Team",

 "Prioritized Backlog, Team Velocity (38 pts)",

 "Sprint Goal, Selected Stories, Assignments",

 "2-4 ชั่วโมง"),

 SprintPhase("Development",

 "Developer",

 "Sprint Backlog, Acceptance Criteria",

 "Working Code, Unit Tests, PR",

 "8-9 วัน"),

 SprintPhase("Testing",

 "QA Engineer",

 "Working Code, Test Plan",

 "Test Results, Bug Reports, Sign-off",

 "1-2 วัน (ขนานกับ Dev)"),

 SprintPhase("Sprint Review",

 "Product Owner + Team",

 "Working Increment, Sprint Goal",

 "Demo Feedback, Backlog Updates",

 "1-2 ชั่วโมง"),

 SprintPhase("Retrospective",

 "Scrum Master + Team",

 "Sprint Metrics, Team Feedback",

 "Action Items, Process Improvements",

 "1 ชั่วโมง"),

]



print("=== Sprint Phases ===")

for p in phases:

 print(f"\n [{p.phase}] Agent: {p.agent}")

 print(f" Input: {p.input_data}")

 print(f" Output: {p.output}")

 print(f" Duration: {p.duration}")

Kanban Metrics

# === Kanban Metrics Analysis ===



@dataclass

class KanbanMetric:

 metric: str

 formula: str

 target: str

 agent_action: str



metrics = [

 KanbanMetric("Cycle Time",

 "เวลาจาก In Progress → Done",

 "< 3 วัน สำหรับ Story ปกติ",

 "Agent วิเคราะห์ Story ที่เกิน Target แนะนำ Split"),

 KanbanMetric("Lead Time",

 "เวลาจาก To Do → Done",

 "< 5 วัน สำหรับ Story ปกติ",

 "Agent วิเคราะห์ Queue Time แนะนำ WIP Limit"),

 KanbanMetric("WIP (Work in Progress)",

 "จำนวน Story ที่ In Progress",

 "≤ Team Size (5-7)",

 "Agent Alert เมื่อเกิน WIP Limit"),

 KanbanMetric("Throughput",

 "จำนวน Story Done ต่อสัปดาห์",

 "> 8 stories/sprint",

 "Agent Track Trend แนะนำ Improvement"),

 KanbanMetric("Velocity",

 "Story Points Done ต่อ Sprint",

 "Stable ±10% จาก Average",

 "Agent คำนวณ Velocity สำหรับ Planning"),

 KanbanMetric("Blocked Items",

 "จำนวน Story ที่ Blocked",

 "0 (ไม่มี Blocked)",

 "Agent Alert Scrum Master ทันทีเมื่อมี Block"),

]



print("=== Kanban Metrics ===")

for m in metrics:

 print(f" [{m.metric}] {m.formula}")

 print(f" Target: {m.target}")

 print(f" Agent: {m.agent_action}")