Learning / Applied practice
Learn it. Build it. Explain it.
This is a record of meaningful technical growth. Topics appear here when they connect to practice, working systems, or a lesson worth carrying forward.
Track 01 / Current focus
Python
PracticingUsed in projects
Foundations → Automation → APIs → AI tooling
The current focus is writing small, understandable programs that accept information, make decisions, manage state, and return useful results.
- Variables and core data types
- Comparisons and conditional logic
- Functions, parameters, arguments, and return values
- Reusable service-health evaluation
Recent milestoneTurned a lesson about functions and state into a reusable service-monitoring project.
Open the Python Service Monitor case study →
Track 02 / Used daily
Infrastructure & Linux
PracticingOperating
Understand the system before changing it
Hands-on operation of virtual machines, containers, storage, networking, reverse proxies, monitoring, backups, and recovery checks.
- Linux service and process inspection
- Container lifecycle and persistent data
- Backup configuration and verification
- Documentation-driven troubleshooting
Recent milestoneBuilt a structured, evidence-based inventory of the homelab and documented service relationships without exposing operational secrets.
Open the Homelab case study →
Track 03 / Exploring
AI Engineering
ExperimentalUsed in projects
Private inference, retrieval, and agents
The focus is understanding how local models, embeddings, vector search, retrieval, tools, and agent workflows fit into useful human-controlled systems.
- Local model runtime and resource behavior
- Embedding and vector collection design
- Retrieval-augmented generation
- Agent workflows and safe operational boundaries
Recent milestoneVerified a private vector-search service and traced how monitoring outputs feed a public read-only dashboard.
Open the Qdrant / RAG case study →
Track 04 / Improving
Security
PracticingOperational
Reduce exposure without breaking the system
Security work is approached as a practical operating discipline: identify what is public, preserve recoverability, restrict services intentionally, and verify the result.
- Public exposure review
- Secret and configuration hygiene
- Authentication boundaries
- Safe publication and documentation
PrincipleNo percentage scores and no inflated claims—only practiced skills connected to evidence.