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Working Scenario: Efficient Work Tracking System ​

Scenario Description ​

Li is a product manager whose daily work involves multiple parallel projects requiring frequent context switching. She often encounters these problems:

  • 🤔 Boss suddenly asks: "What were the details of last week's requirement discussion?"
  • 📊 When writing weekly reports, can't recall what was done this week
  • 💼 Clients request specific discussion content from a certain meeting
  • 🔄 Multiple projects in parallel, need to recall context when switching
  • ⏰ Not clear where time was spent

After using LifeTrace, Li's work efficiency and response speed greatly improved.

Usage ​

1. All-day Work Recording ​

Li's first task every workday is to start LifeTrace:

bash
# Start LifeTrace service
python start_all_services.py

LifeTrace automatically records:

  • 📧 Email communications
  • 💬 Online meeting discussions
  • 📝 Document editing process
  • 📊 Data analysis charts
  • 🎨 Design draft viewing records

2. Quickly Find Historical Work Content ​

When the boss asks about last week's requirement discussion details, Li immediately searches:

bash
curl -X POST http://localhost:8840/api/semantic-search \
  -H "Content-Type: application/json" \
  -d '{
    "query": "user registration process optimization requirement discussion",
    "filters": {
      "time_range": {
        "start": "2025-10-05",
        "end": "2025-10-12"
      }
    },
    "limit": 10
  }'

Or search "user registration process" in the Web interface, the system will:

  • 🎯 Display all related meeting screenshots
  • 📄 Show specific versions of requirement documents
  • 💬 Find discussion points from chat records
  • 📅 Arrange chronologically, clearly presenting decision process

3. Automatically Generate Weekly Reports ​

Every Friday afternoon, Li can get a weekly work summary with just one command:

bash
curl -X GET "http://localhost:8840/api/timeline?start_time=2025-10-06&end_time=2025-10-12"

The system returns:

  • 📊 Weekly work time distribution
  • 📋 Project time allocation ratio
    • Project A: 40% (16 hours)
    • Project B: 35% (14 hours)
    • Project C: 15% (6 hours)
    • Meetings: 10% (4 hours)
  • 🎯 Main work content overview
  • 📈 Work efficiency trend analysis

Actual Results ​

After using LifeTrace for six months, Li's work performance significantly improved:

⚡ Response Speed Improved ​

  • Information search time reduced 90%: From average 15 minutes to 1.5 minutes
  • Meeting preparation efficiency improved 5x: Quickly review historical discussions
  • Faster response to emergencies: Immediately find relevant historical information

📊 Work Quality Improved ​

  • Decisions traceable: Complete context record for each decision
  • Avoid missing important information: Automatic recording, not relying on manual notes
  • Clear requirement tracing: Complete requirement evolution history

💼 Career Development Bonus ​

  • More detailed weekly/monthly reports: Data-supported, work results visualized
  • Impressive year-end summary: Quantitative display of annual work results
  • Leadership recognition improved: Efficient response, professional and reliable

Configuration Recommendations ​

Work Scenario Specific Configuration ​

yaml
screenshot:
  interval: 90  # Every 1.5 minutes, balance performance and content capture
  quality: 85   # Medium-high quality, balance clarity and storage space
  smart_capture: true  # Enable smart capture
  
work_hours:
  start: "09:00"
  end: "18:00"
  # Don't record outside work hours
  
apps:
  whitelist:
    - Chrome  # Browser
    - Outlook  # Email
    - Teams  # Meetings
    - Slack  # Instant messaging
    - Notion  # Document collaboration
    - Figma  # Design viewing
    - Excel  # Data analysis
    - PowerPoint  # Presentations

Best Practices ​

1. Project Tag System ​

Build clear tag system:

bash
# Tag important work content
curl -X POST http://localhost:8840/api/tags \
  -H "Content-Type: application/json" \
  -d '{
    "screenshot_id": "xyz789",
    "tags": ["ProjectA", "important-decision", "requirement-confirmation"]
  }'

Recommended tag categories:

  • Project tags: ProjectA, ProjectB, ProjectC
  • Content type: requirements, design, data, meeting
  • Importance level: important, urgent, todo
  • Status tags: in-progress, completed, pending-review

2. Weekly Report Automation ​

Create weekly report generation script:

python
# weekly_report.py
import requests
from datetime import datetime, timedelta

# Get this week's data
end_date = datetime.now()
start_date = end_date - timedelta(days=7)

response = requests.get(
    f"http://localhost:8840/api/timeline",
    params={
        "start_time": start_date.strftime("%Y-%m-%d"),
        "end_time": end_date.strftime("%Y-%m-%d")
    }
)

# Generate weekly report
data = response.json()
print(f"## Weekly Summary ({start_date.date()} - {end_date.date()})")
print(f"- Total work hours: {data['total_hours']} hours")
print(f"- Project distribution: {data['project_distribution']}")
print(f"- Key achievements: {data['key_achievements']}")

User Testimonial ​

"LifeTrace is my work black box. Whenever the boss asks about work details, I can find answers in seconds. More importantly, through data analysis, I found I spent too much time in meetings. Now I evaluate meeting necessity more carefully." —— Li, Product Manager

Next Steps ​