AI Dev Days Hackathon: Build the Future with AI Apps, Agents, and Secure DevOps ($80k+ Prizes)

Ayub Henry — Thu, 19 Feb 2026 06:00:38 +0000

Join the 5-week global challenge for developers to create AI agents, agentic DevOps workflows, and intelligent applications using Microsoft's AI platform, GitHub, VS Code, and Azure services.

Leverage Microsoft's AI platform, which provides an end-to-end toolchain for building production-ready AI systems. Utilize the latest AI, agent, cloud, and developer technologies to address real-world problems across various industries.

Consider building:

An AI agent with Microsoft Agent Framework
An Agentic DevOps workflow using GitHub Copilot Agent Mode
A multi-agent application powered by Model Router
A secure enterprise AI app with Microsoft Foundry
An agent-to-agent (A2A) or MCP-connected system using Azure MCP
A next-gen SRE workflow with Azure SRE Agent

Core Requirements:

Build an AI-powered solution using one or more of the following technologies: Microsoft Foundry, Microsoft Agent Framework, Azure MCP, or GitHub Copilot Agent Mode.
Deploy your application to Azure, leveraging Azure services.
Host your project in a public GitHub repository, developed with VS Code or Visual Studio, and enhanced with GitHub Copilot.

Prize Categories:

Grand Prize for the best overall solution with real-world impact: $20,000 (up to 4 team members), a ticket to Microsoft Build 2026, social promotion, and a mentoring session with the Microsoft team.
Grand Prize for the best solution leveraging agentic DevOps: $20,000 (up to 4 team members), a ticket to Microsoft Build 2026, social promotion, and a mentoring session with the Microsoft team.
Best Use of Microsoft Foundry Project: $10,000 (up to 4 team members) and a ticket to Microsoft Build 2026.
Best Enterprise Solution: $10,000 (up to 4 team members) and a ticket to Microsoft Build 2026.
This hackathon is your playground—let's innovate together!
https://developer.microsoft.com/en-us/reactor/events/26647/?wt.mc_id=studentamb_253040

Python + Agents: Building AI agents and workflows with Agent Framework

Ayub Henry — Thu, 19 Feb 2026 05:39:58 +0000

Join us for an engaging 6-part livestream series where we will explore the foundational concepts behind building AI agents in Python using the Microsoft Agent Framework.

This series is designed for anyone interested in understanding how agents function, including their tool interactions, memory usage, context application, and workflow construction. Over the course of two weeks, we will delve into the practical building blocks that define real agent behavior.

You will learn how to:

Register and structure tools
Connect local MCP servers
Add context with database calls
Compare memory strategies
Monitor agent behavior using OpenTelemetry
Evaluate the safety and quality of agent output

All live examples will be conducted in Python, and we will share the complete code so you can run everything on your own. Additionally, you can follow along live using GitHub Models and GitHub Codespaces.

For more details, visit: https://developer.microsoft.com/en-us/reactor/series/S-1631/?wt.mc_id=studentamb_253040

laptopXplorer

Ayub Henry — Fri, 06 Feb 2026 21:55:54 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

LaptopXplorer - A modern, production-ready Django marketplace platform for discovering and comparing laptops.

🚀 Key Features

Smart Laptop Catalog: Browse laptops with advanced filtering by brand, category, price range, and specifications
Multi-Image Galleries: Each laptop can showcase multiple images with smooth navigation
Article System: Tech news and buying guides with full CRUD capabilities
SEO Optimized: XML sitemaps, Schema.org structured data, Open Graph tags, and dynamic meta tags
Futuristic UI: Gradient-heavy design with animations and responsive layouts
Production Ready: Dockerized deployment with nginx, SSL support, and proper static file handling

🎯 What This Project Means to Me

This project represents a complete journey from concept to production deployment. It showcases:

Modern web development practices with Django 5.0
Full-stack development (backend, frontend, DevOps)
Production-ready architecture with Docker and nginx
SEO best practices for content discovery
Real-world problem-solving and debugging

Demo

🌐 Live Site

Production URL: laptopxplorer.onrender.com

Username: admin@gmail.com
Password: P@@$$word

📸 Screenshots

Homepage - Futuristic Design

Laptop Detail - Multi-Image Gallery

Article System

Admin Panel

🛠️ Technical Stack

Backend: Django 5.0.7, Python 3.12
Database: SQLite (development), PostgreSQL-ready
Frontend: HTML5, CSS3 (Custom futuristic design)
Deployment: Docker, Docker Compose, Gunicorn, Nginx
Server: Ubuntu 22.04 LTS
SEO: XML Sitemaps, Schema.org, Open Graph, Twitter Cards

My Experience with GitHub Copilot CLI

GitHub Copilot CLI was absolutely transformative for this project. Here's how it impacted my development:

🎯 Lightning-Fast Development

Before Copilot CLI: Setting up a Django project with Docker, nginx, and production deployment would take days of research, trial-and-error, and debugging.

With Copilot CLI: Went from zero to production in a single development session. The AI understood the entire context and built everything systematically.

💡 Key Wins

1. Intelligent Architecture Decisions

# I simply asked:
"Create a Django laptop marketplace with brand filtering"

# Copilot CLI:
- Generated proper model relationships (Brand → Laptop → Images)
- Created intuitive URL structures
- Set up admin interfaces automatically
- Added proper model methods and meta classes

2. SEO Implementation Made Simple

The most impressive part was SEO setup. I requested "implement SEO basics" and got:

✅ 5 comprehensive XML sitemaps (laptops, brands, categories, articles, static pages)
✅ Schema.org structured data (Product, Article, Organization schemas)
✅ Custom Django template tags for SEO
✅ Open Graph and Twitter Card meta tags
✅ Dynamic canonical URLs
✅ Complete documentation (SEO_GUIDE.md)

All in minutes, not hours!

3. Production Deployment Mastery

Copilot CLI handled the entire production setup:

# My request:
"Deploy using Docker on Ubuntu, nginx external, port 1480"

# What it created:
- Dockerfile with multi-stage optimization
- docker-compose.yaml with proper volume mapping
- docker-entrypoint.sh for migrations and static files
- nginx.conf with SSL-ready configuration
- Automated deployment scripts (setup-nginx.sh, deploy-production.sh)
- Complete Ubuntu deployment guide

4. Real-Time Debugging

When I hit the static files issue (admin panel styles not loading), Copilot CLI:

🔍 Analyzed nginx error logs
🎯 Identified the root cause (Docker named volumes vs bind mounts)
🔧 Provided the exact fix (updated docker-compose.yaml)
✅ Created diagnostic and fix scripts
📝 Explained the entire issue clearly

5. Context Awareness

The most powerful feature was context retention:

Remembered all previous changes across the session
Understood when to update existing files vs create new ones
Made minimal, surgical changes to fix issues
Never broke existing functionality

📊 Development Metrics

Time Saved: Estimated 20-30 hours of development time

What Would Have Taken Days:

✅ Docker configuration: 4-6 hours → 15 minutes
✅ Nginx setup with SSL: 3-4 hours → 10 minutes
✅ SEO implementation: 6-8 hours → 20 minutes
✅ Multi-image gallery: 2-3 hours → 10 minutes
✅ Production debugging: 4-5 hours → 30 minutes

🎓 Learning Experience

GitHub Copilot CLI didn't just write code—it taught me:

Best Practices: Every generated file followed Django and Docker best practices
Security: Proper CSRF configuration, environment variables, SECRET_KEY management
Performance: WhiteNoise for static files, Gunicorn workers, nginx caching
DevOps: Proper Docker volume mapping, nginx proxy configuration
SEO: Modern SEO techniques I didn't even know existed

💬 Conversation-Driven Development

The natural language interface was game-changing:

Me: "Remove all unnecessary files"
Copilot: *Creates cleanup.bat targeting exactly the right files*

Me: "Admin panel styles not loading"
Copilot: *Analyzes logs, diagnoses volume mapping issue, provides fix*

Me: "Add multi-image support"
Copilot: *Updates models, migrations, admin, templates, views*

No Stack Overflow. No documentation hunting. Just ask and build.

🚀 What I Loved Most

Zero Configuration: Worked immediately, no setup required
Full Context Understanding: Remembered every change across the entire session
Production-Ready Code: Not just "it works" but "it's deployable"
Educational: Learned while building through clear explanations
Error Recovery: When things failed, it debugged and fixed intelligently

🎯 Final Thoughts

GitHub Copilot CLI transformed how I build web applications. It's like having a senior developer pair-programming with you 24/7—one who:

Never gets tired
Remembers everything
Knows best practices
Writes clean, documented code
Debugs with superhuman speed

This project went from concept to production deployment in record time, and the code quality is better than what I would have written alone.

Would I use it again? Absolutely. It's now an essential part of my development workflow.

🔗 Project Links

Live Site: https://laptopxplorer.ayubsoft-inc.systems
GitHub Repository: https://github.com/ayubsoft254/laptopXplorer
Documentation: See README.md, SEO_GUIDE.md, UBUNTU_DEPLOY.md in repo

📚 Project Structure

laptopXplorer/
├── src/
│   ├── laptops/        # Main app (models, views, sitemaps, SEO)
│   ├── home/           # Landing page
│   ├── core/           # Article system
│   ├── accounts/       # User authentication
│   ├── config/         # Django settings
│   └── templates/      # Futuristic UI templates
├── docker-compose.yaml # Production container config
├── Dockerfile          # Container definition
├── nginx.conf          # Nginx configuration
├── deploy-production.sh # Deployment automation
└── requirements.txt    # Python dependencies

Built with ❤️ using GitHub Copilot CLI

GitHubCopilotCLI #Django #Docker #WebDevelopment #AI #DevOps

Forem: Ayub Henry