My main programming language is Python. Rather than treating it only as a scripting or data-analysis language, I'm particularly interested in understanding Python as an engineering tool — its data model, typing system, concurrency model, web ecosystem, database tooling, and the design patterns behind production applications.

On the backend side, I mainly work with FastAPI, SQLAlchemy and relational databases. I care about API design, validation, dependency injection, authentication, database modeling, service layering, and keeping projects maintainable as they grow.

I'm also actively exploring the AI application ecosystem. My current interests include LLM agents, tool calling, LangChain, LangGraph, RAG, structured output, multimodal models, and how AI systems can be integrated into practical software instead of remaining isolated demos.

Outside application code, I also spend time on the surrounding engineering stack: Docker, Linux servers, Git workflows, networking, deployment, monitoring, frontend integration, and developer tooling. I like understanding how the entire system works rather than focusing on only one layer.

Most of my learning is project-driven. I've worked on small production and order-management systems, large-file data platforms, server monitoring tools, hardware-oriented monitoring interfaces, and experiments around AI agents and automation.

These projects are where I test architectural ideas, database models, API conventions, concurrency strategies, deployment workflows and UI decisions. I prefer learning a concept deeply enough to use it in an actual system.

This site is my long-term technical notebook and personal space on the web. I use it to organize what I learn, document problems I've solved, record project decisions, and turn fragmented notes into knowledge that I can revisit later.

You'll mostly find posts about Python, backend engineering, FastAPI, databases, AI agents, developer tools, Linux, networking, and whatever I'm currently building or trying to understand.