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Issue Generation Examples

Learn how to generate small, deployable work items for AI-assisted development with <1 hour cycle times.

Pattern Definition: This directory provides implementation examples for the Issue Generation pattern - an intermediate-level foundation pattern that uses AI to generate small work items (<1 hour) from requirements, ensuring continuous delivery with clear acceptance criteria and dependencies. Works with any methodology (Kanban, Scrum, or ad-hoc workflows).

🚀 Quick Start

New to AI issue generation? Follow this learning path:

  1. Getting Started - Core concepts, why <1 hour tasks, AI development velocity
  2. Choosing Tools - Decision framework: Beads vs GitHub/JIRA/Linear
  3. AI Prompts - Templates for epic breakdown, progress tracking, dependencies
  4. Workflow Examples - Real-world epic management and relationship patterns
  5. CI Integration - Traceability, file validation, automated reporting

For Beads users: See beads-guide.md for git-native, AI-first issue tracking

Directory Structure

├── README.md                      # You are here - navigation hub
├── 01-getting-started.md          # Core concepts and AI-first principles
├── 02-choosing-tools.md           # Tool comparison and decision framework
├── 03-ai-prompts.md               # AI prompt templates for issue generation
├── 04-workflow-examples.md        # Epic breakdown and relationship patterns
├── 05-ci-integration.md           # CI/CD integration and traceability
├── beads-guide.md                 # Beads setup and usage guide
└── issue-generator.py             # Python script for automated generation

Key Concepts

Why <1 Hour Tasks?

Methodology-Agnostic: Whether you use Kanban, Scrum, or continuous delivery, <1 hour tasks enable rapid feedback and reduce risk.

AI-assisted development is fundamentally faster than manual coding:

Activity Manual AI-Assisted
Code generation Hours Minutes
Iteration cycle Hours 5-15 minutes
Deployment 1-2x/day Multiple times/hour
Total task time 4-8 hours <1 hour

Traditional: Planning (30min) + Coding (6hrs) + Testing (1hr) + Review (30min) = 8 hours

AI-Assisted: Planning (5min) + AI prompting (10min) + Review (20min) + Testing (15min) = 50 minutes

See 01-getting-started.md for detailed velocity comparisons.

Core Principles

  1. Small batch sizing: Split work until each task is <1 hour (enables continuous delivery)
  2. Independent deployment: Every task ships without waiting
  3. RED/GREEN/REFACTOR: Test-first, minimal implementation, then clean
  4. CI/CD always: Every task runs through the pipeline

Works with any methodology: These principles support Kanban (continuous flow), Scrum (sprint tasks), or ad-hoc delivery.

Tool Decision Framework

Choose Beads if:

  • AI-assisted development is your primary workflow
  • Solo developer or small technical team
  • Want git-native issues versioned with code
  • Work offline frequently
  • Need <50ms query speed for AI agents

Choose GitHub/JIRA/Linear if:

  • Team includes non-technical stakeholders
  • Need rich collaboration (comments, mentions, web UI)
  • Open source with external contributors
  • Enterprise requirements (SSO, compliance)

See 02-choosing-tools.md for complete comparison and decision tree.

Comparison Table

Feature Beads GitHub Issues JIRA Linear
AI Agent Access ✅ Native CLI ⚠️ API + token ⚠️ Complex API ⚠️ API + token
Offline Work ✅ Full ❌ Limited ❌ None ❌ None
Git Integration ✅ Native ⚠️ External ❌ Separate ❌ Separate
Setup Time ✅ Instant ⚠️ Minutes ❌ Hours/Days ⚠️ Minutes
Query Speed ✅ <50ms ⚠️ 100-500ms ⚠️ 200-1000ms ⚠️ 100-300ms
Non-tech Users ❌ CLI only ✅ Web UI ✅ Web UI ✅ Web UI
Collaboration ⚠️ Basic ✅ Rich ✅ Enterprise ✅ Modern
Integrations ❌ Minimal ✅ Extensive ✅ Enterprise ✅ Modern
Cost ✅ Free ✅ Free ❌ Paid ⚠️ Paid

Key Insights:

  • Beads excels for AI agent workflows, offline development, and git-native issue tracking
  • GitHub/JIRA/Linear excel for team collaboration, rich features, and stakeholder visibility
  • Consider a hybrid approach: Use Beads for internal tech work, traditional tools for external visibility

Quick Examples

Create Epic with <1 Hour Tasks

ai "Create epic for User Authentication with subissues that are:
1. Deployable in <1 hour each (AI-assisted development)
2. Independently deployable
3. Cross-linked to parent epic
4. Include RED/GREEN/REFACTOR acceptance criteria
5. Have CI/CD pipeline hooks"

Break Down Feature

ai "Break down 'User Dashboard' epic following these rules:
- Each subissue must be deployable in <1 hour (AI-assisted development)
- Create bidirectional epic-subissue links
- Use RED/GREEN/REFACTOR for development tasks
- Include CI/CD pipeline triggers for each subissue
- Auto-update epic progress when subissues complete"

See 03-ai-prompts.md for complete prompt library.

Beads Workflow (CLI)

# Create epic
bd create --title "Epic: User Auth System"

# Create subtask with RED/GREEN/REFACTOR
bd create --title "Add JWT validation" \
  --body "RED: Write failing test
GREEN: Implement validation
REFACTOR: Extract key management" \
  --parent issue-generation-7c9

# Query ready work (<50ms)
bd ready

# Update status
bd update issue-generation-7c9.1 --status done

# Sync via git
git add .beads/ && git commit -m "beads: complete JWT validation"

See beads-guide.md for complete Beads tutorial.

Integration Philosophy

Rather than complex API scripts, use AI prompts that work with your existing issue tracking tools:

  • Direct AI Interface: Let AI tools create issues directly through their integrations
  • Platform-Agnostic Prompts: Same prompt structure works across GitHub, JIRA, Azure DevOps
  • Focus on Requirements: Specify what you need (timing, dependencies, CI/CD), not how to implement
  • Automation Through Simplicity: Use platform's built-in automation rather than custom scripts
  • Git-Native Option: For AI-first workflows, consider Beads for CLI-native, offline-capable issue tracking

Learning Path

Beginners

  1. Start: 01-getting-started.md
  2. Choose: 02-choosing-tools.md
  3. Try: Pick one AI prompt from 03-ai-prompts.md

Intermediate

  1. Review: 04-workflow-examples.md
  2. Implement: 05-ci-integration.md
  3. Automate: Use issue-generator.py

Advanced

  1. Customize: Modify prompts for your workflow
  2. Integrate: Build CI/CD automation
  3. Scale: Implement hybrid Beads + traditional tools

Common Questions

Q: Why <1 hour instead of 4-8 hours? A: AI generates code in minutes, not hours. See 01-getting-started.md#why-1-hour-tasks

Q: Which tool should I use? A: See the decision tree in 02-choosing-tools.md#quick-decision-tree

Q: How do I break down large epics? A: Use AI prompts from 03-ai-prompts.md#epic-creation

Q: Can I use Beads with GitHub? A: Yes! See hybrid approach in 02-choosing-tools.md#hybrid-approach

Resources

Getting Help


Start here: 01-getting-started.md to learn AI-first issue generation principles.