🔮 Signals from Tomorrow

A Scenario Builder's Field Guide - An interactive tool for foresight professionals to discover weak signals and emerging trends

📖 About

Signals from Tomorrow is an interactive web application designed for foresight professionals, scenario planners, and strategic thinkers. It serves as a serendipity engine that surfaces random combinations of change signals to spark imagination and inform scenario development.

Each visit presents a unique constellation of:

• 🌱 Weak Signals (5 items) - Early indicators of potential change
• 👥 Behavioral Shifts (3 items) - Evolving human patterns and adaptations
• 💭 Rising Concerns (3 items) - Emerging anxieties and tensions
• ⚠️ Issues in Motion (3 items) - Evolving problems and challenges
• ⚡ Technology Waves (3 items) - New technological developments

🎯 Purpose

This tool helps foresight practitioners:

• Discover unexpected connections between signals
• Break out of familiar thinking patterns
• Generate scenario seeds through serendipitous combinations
• Explore the edges of change in multiple domains
• Practice pattern recognition across different types of signals

🌐 Live Demo

Visit the live application: [Your GitHub Pages URL]

📊 Data Sources

All signals in this collection are:

• Curated at: substack.kghosh.me
• Processed through: futures.kghosh.me
• Human-guided: Each link is selected and categorized in this newsletter

🚀 Features

• Random sampling for fresh perspectives each visit
• Clean, distraction-free interface optimized for reading and thinking
• Direct linking to source materials for deeper exploration
• Responsive design that works on desktop, tablet, and mobile
• No tracking or analytics - just you and the signals
• Fast loading with all data pre-compiled as JSON

🛠️ Technical Stack

• Frontend: Pure HTML5, CSS3, and vanilla JavaScript
• Hosting: GitHub Pages (static site)
• Data Format: JSON
• Build Process: Python scripts for data preparation

📁 Project Structure

.
├── docs/
│   ├── index.html              # Main application
│   └── data/
│       └── combined_data.json  # All signals data
├── transform.ipynb             # To create the jsons
└── README.md

🔧 Setup & Development

Prerequisites

• Python 3.7+ (for data preparation)

Local Development

1. Clone the repository

   git clone https://github.com/kelu124/2026tarot.git
   cd 2026tarot

2. Prepare your data (if updating signals) Run Transform.ipynb

3. Run a local server

   cd docs
   python -m http.server 8000

4. Open in browser

   http://localhost:8000
   

Deploying to GitHub Pages

1. Push your changes to the main branch
2. Go to repository Settings → Pages
3. Set source to: main branch, /docs folder
4. Save and wait a few minutes for deployment

Your site will be live at: https://yourusername.github.io/your-repo-name/

📝 Data Format

The application expects a JSON file with this structure:

{
  "seeds": [
    {
      "name": "Signal name",
      "description": "Description text",
      "change": "Type of change",
      "10-year": "10-year outlook",
      "driving-force": "Main driving force",
      "relevancy": "Relevance level",
      "src": "unique-id"
    }
  ],
  "behav": [
    {
      "name": "Behavior name",
      "description": "Description text",
      "relevancy": "Relevance level",
      "src": "unique-id"
    }
  ],
  "concern": [...],
  "issue": [...],
  "tech": [...]
}

🎨 Customization

Change Number of Items

Edit the JavaScript in index.html:

// For seeds (currently 5)
const seeds = getRandomSamples(data.seeds, 5);

// For other categories (currently 3)
const samples = getRandomSamples(groupData, 3);

Modify Section Titles

Find the dataGroups array in index.html:

const dataGroups = [
  { 
    name: '👥 Your Custom Title', 
    key: 'behav',
    intro: 'Your custom description here'
  },
  // ...
];

Change Color Scheme

Modify the CSS gradient and accent colors:

/* Main gradient */
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);

/* Accent colors */
color: #667eea;
border-left: 4px solid #667eea;

🤝 Contributing

While this is a personal curation project, suggestions are welcome!

Ways to contribute:

• Report bugs or UI issues
• Suggest improvements to the interface
• Share how you're using this tool in your practice

Please open an issue to discuss any significant changes.

📚 Use Cases

This tool has been used for:

• Scenario workshops - Generating starting points for group exploration
• Personal practice - Daily inspiration for futures thinking
• Research - Discovering connections across domains
• Teaching - Introducing students to weak signals methodology
• Consulting - Client presentation of emerging trends

🔗 Related Projects

• futures.kghosh.me - Full futures library
• substack.kghosh.me - Signal curation and analysis

📄 License

This project is open source and available under the MIT License.

👤 Author

K Ghosh

• Substack: substack.kghosh.me
• Futures Library: futures.kghosh.me

🙏 Acknowledgments

• To all the authors, researchers, and thinkers whose work is linked here
• To the foresight community for inspiring this methodology
• To everyone who believes in thinking carefully about tomorrow

💡 Philosophy

"The future is already here—it's just not evenly distributed."
— William Gibson

This tool is built on the belief that:

• Weak signals matter as much as strong trends
• Serendipity is a feature, not a bug
• Pattern recognition is a learnable skill
• The most interesting futures emerge at intersections
• Good foresight requires both breadth and depth

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Note: The signals displayed are curated interpretations of publicly available information. They are meant to inspire thinking and should not be taken as predictions or recommendations.

Built with ❤️ for futures thinkers everywhere