Data Scientist · Software Engineer · Aviationeer
Data scientist by training, software engineer by heart, and aviationeer by profession. I have grown into AI engineering where the work requires it—focusing on thoughtful, resource-aware solutions and software that remains clear as it evolves.
AI should solve a real problem, not merely add noise. My work focuses on the tooling, vocabulary, and workflow discipline that make AI systems useful, efficient, and understandable.
| Project | Focus | |
|---|---|---|
| ✨ | PIIA | Personal Information. Intelligent. Anywhere. The independent, closed-source product I am building myself to tackle a difficult problem deliberately. It is not open for contributions. |
| 📚 | Open Agent Glossary | A shared vocabulary for agentic systems—clear concepts before fashionable terms. |
| 🧭 | PI Session Orchestration | Patterns and tooling for structured, observable AI-agent collaboration. Coming soon. |
| 🧰 | Skills | Reusable skills and operating practices for AI-assisted engineering. |
Practical over theatrical. I aim for AI solutions that are proportionate to the problem, deliberate with resources, and designed around the people who will use them. The same standard applies to the code underneath: reusable, clean, tested, and extensible.
Mobile Flutter · BLoC
Backend Python · FastAPI · LangChain
Data & Knowledge Data science · Knowledge graphs · Neo4j · Cypher
AI Systems Pi · Agent orchestration · AI developer tools
Engineering Clean Architecture · SOLID · Testable workflows · Observability
Principle Reusable, clean, tested code—designed to be extended.
Build systems that help people make better decisions.