I'm a software enthusiast based in Maputo, Mozambique, passionate about open source and data science. I'm constantly learning and exploring how to solve problems through code, with a particular interest in low-level programming and understanding how systems work.

Currently diving deeper into DevOps and data engineering, I'm building projects to learn and practice these concepts while contributing back to the open source community.

• Learning through building: Each project is an opportunity to understand something new and share what I discover
• Open source contribution: Giving back to the community while learning from others' code and feedback
• System curiosity: Always asking "how does this work underneath?" and diving into the details
• Practical problem-solving: Building tools that solve real problems I encounter in my learning journey

A Python-based command-line tool that converts structured data files (CSV, Excel, JSON, XML) into SQL INSERT statements. Solving the everyday problem of data migration and database population with elegance and efficiency.

• Tech Stack: Python
• Key Features: Multi-format support, CLI interface, Batch processing
• Also available in Go: brokolisql-go

Cross-Language Learning: I'm exploring the same problems in different languages (Python → Go with BrokoliSQL) to understand how language choice affects implementation and performance. Each rewrite teaches me something new.

Building for the AI Era: Projects like promptweaver are my way of learning how traditional development workflows might evolve. I'm still figuring out the best patterns, but it's exciting to explore.

End-to-End Understanding: I'm trying to build projects across the full stack - from data processing to deployment - because I believe understanding the whole picture makes you better at any individual piece.

Learning in Public: Every project here represents something I'm learning or have learned. Some work better than others, but they all teach me something valuable.

• Advanced Go patterns and concurrency
• Cloud-native architectures and their trade-offs
• Kubernetes and container orchestration
• Real-time data processing pipelines
• AI integration patterns in development workflows

• Location: Maputo, Mozambique
• Focus: Learning DevOps & Data Engineering
• Open to: Feedback, collaboration, and learning from others

Learning in public, one commit at a time