Building Temporal & Network-Native AI Ecosystems
🔗 Live Site: https://peacebinflow.github.io/sageworks-ai
This repository hosts the official website for the SageWorks AI ecosystem — an experimental lab for temporal intelligence, network-native computing, and cognitive event processing. Built and maintained by Peace Thabiwa from Botswana, SageWorks AI represents a paradigm shift from static data storage to living, time-aware computational systems.
SageWorks AI explores what happens when you stop treating computation as isolated requests and start treating it as timelines: sequences of events, trades, notifications, and signals that can be measured, replayed, and reasoned about.
Time-labeled signal infrastructure
The network layer that treats every interaction as a time-labeled signal crossing a graph of agents, devices, and services. Instead of "calling an API," you define laws: priority, routes, access, and temporal scope.
- Core Specs: Network layer definitions and device profiles
- N-SQL Engine: Network-aware, time-labeled SQL queries
- Signal Simulator: Testing and validation tooling
- Notebook Hub: Interactive LAW-N experiments
Key Repos:
Cognitive event processing & perception streams
The cognitive layer over LAW-N that treats inboxes, notifications, logs, and ledgers as one continuous perception stream rather than scattered tables and logs.
- Workspace Automation: Google-native ledgers and orchestration
- Agent Fabric: Chrome, Android, and device-layer agents
- Binary Engine: Pattern recognition and entropy scoring
- SQL Bridges: Time-aware database integration
Key Repos:
SQL that routes across networks
SQL reimagined for network-native systems. Queries that understand temporal context, device location, and network topology.
-- Example: Time-aware network query
SELECT * FROM agents
WHERE timestamp > NOW() - INTERVAL '5 minutes'
AND network_hop <= 3
ORDER BY temporal_weight DESC;Key Repos:
Time-native, self-evolving code
A programming model that writes directly into binary ledgers with time as a first-class dimension. Every variable, function, and class carries temporal metadata.
// LAW-T conceptual syntax
temporal function processEvent(data: TimedData) {
let result = compute(data) @timestamp;
return result.withContext(temporal.now());
}Key Repos:
Hypercube interfaces & multi-dimensional interaction
Front-end experiments for agentic, dimensional interfaces that extend beyond traditional 2D UI paradigms.
Key Repos:
Google-to-Network integration stack
Multi-surface cognition layers connecting Google Workspace, device events, and network signals into unified temporal streams.
Layers:
- Google Layer — Workspace event capture
- MindsEye Core Layer — Cognitive processing
- Device Binary Layer — Local event streams
- Dataset Builder — Kaggle integration
Key Repos:
- G2N notebooks available on Kaggle
- Languages: TypeScript, Python, JavaScript, Kotlin, Solidity
- Frameworks: Node.js, React, Next.js
- Databases: MongoDB, PostgreSQL, TigerData (Timescale)
- AI/ML: Google Gemini, LangChain, Custom temporal models
- Infrastructure: Docker, GitHub Actions, Cloudflare Workers
- Version Control: Git, GitHub
- CI/CD: GitHub Actions
- Deployment: GitHub Pages, Vercel
- Testing: Jest, Pytest, Kaggle notebooks
sageworks-ai/
├── index.html # Main website
├── styles.css # Enhanced stylesheet
├── assets/
│ ├── img/ # Visual assets
│ └── docs/ # Documentation
├── README.md # This file
└── LICENSE # Project license
-
Clone the repository:
git clone https://github.com/PEACEBINFLOW/sageworks-ai.git cd sageworks-ai -
Open in browser:
# Using Python python -m http.server 8000 # Using Node.js npx serve # Or simply open index.html in your browser
-
Visit:
http://localhost:8000
The site is automatically deployed via GitHub Pages:
- Branch:
main - Directory:
/(root) - URL: https://peacebinflow.github.io/sageworks-ai
To deploy changes:
git add .
git commit -m "Update: description"
git push origin main
# GitHub Pages automatically rebuilds- 📝 DEV Community Articles — 30+ in-depth posts
- 🔬 Kaggle Notebooks — Live experiments
- 💻 GitHub Repositories — 40+ repos
- 🌐 Forem Profile — Community posts
- LAW-N Network Series (Parts 1-5)
- Google AI Agents Intensive (5-day journey)
- MindsEye Architecture (Building Web4)
- LAW-T Programming Language (Time-native coding)
- Featured in LibHunt developer tools
- Used in production AI farming assistant (Kisan by Yashwanth Krishna Pavush)
- Active participant in Hacktoberfest 2025
- Google AI Challenge contributor
While this is primarily a personal project by Peace Thabiwa, contributions and collaboration are welcome:
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Commit your changes:
git commit -m 'Add amazing feature' - Push to branch:
git push origin feature/amazing-feature - Open a Pull Request
- Maintain the existing design language
- Ensure responsive design principles
- Test across multiple browsers
- Document any new features
- GitHub: Primary development hub
- DEV Community: Long-form technical writing
- Kaggle: Experimental notebooks and datasets
- Forem: Community engagement
All 40+ repositories are part of the SageWorks AI ecosystem:
- MindsEye family: 20+ repos
- LAW Network family: 10+ repos
- LAW-T language: 5+ repos
- Dimensional UI: Experimental UI repos
👉 Explore the full ecosystem: github.com/PEACEBINFLOW
Founder, SageWorks AI · Based in Maun, Botswana
For collaboration, research proposals, or ecosystem questions:
- 📧 Email: peacethabibinflow@proton.me
- 💻 GitHub: @PEACEBINFLOW
- 📝 DEV Community: @peacebinflow
- 📊 Kaggle: @peacebinflow
- 🌐 Forem: @peacebinflow
- Research partnerships in temporal computing
- Open-source contributions to the ecosystem
- Integration with your AI/ML projects
- Speaking engagements and technical writing
This project is open source and available under the MIT License.
- GitHub Pages — Hosting infrastructure
- TigerData/Timescale — Temporal database backend
- Google Gemini — AI orchestration
- Kaggle — Experimental platform
- DEV Community — Publishing platform
Special thanks to everyone who has engaged with, used, or contributed to the SageWorks AI ecosystem. Your feedback and adoption drive innovation forward.
- LAW-T interpreter v1.0 release
- MindsEye mobile apps (iOS/Android)
- Network SQL production deployment
- Expanded Kaggle dataset library
- Web4 specification whitepaper
- LAW-N reference implementation
- Enterprise pilot programs
- Developer documentation hub
Building toward a future where:
- Data flows as time-labeled temporal units
- Networks operate under transparent laws
- Agents possess genuine memory architecture
- Computation is measured in perception, not just cycles
Built with 🧠 by Peace Thabiwa in Maun, Botswana
"Perception redefined through systems."
