Engineering Hobby Lab
Engineering leadership ideas, explored through hands-on builds
I use small, focused projects to test ideas from platform transformation, engineering governance, and enterprise architecture in working systems.
This is primarily a hobby project lab for personal learning and practice. Production work is explicitly identified where included.
Shared engineering baseline
A reusable product and engineering framework keeps the work consistent from the first idea through architecture, implementation, verification, and operation. It brings the discipline of large-scale engineering into small experiments.
Engineering portfolio intelligence
Combines sprint delivery, code quality, testing, and customer support signals into a working portfolio view for a large organization.
Successfully operating dashboards expose risks and trends across teams and provide a shared evidence base for conversations with team leads.
Public procurement intelligence
Tracks Latvian public procurements and turns fragmented source records, changes, documents, buyers, and suppliers into one view.
Incremental collection and targeted enrichment keep the product useful while respecting real-world source constraints.
Finance console for portfolio tracking, accounting, and automated investor workflows.
Incremental public-channel exporter that creates searchable Markdown archives without the Telegram API.
Private daily focus and weekly reflection system with secure Google sign-in.
Practical relationship-mapping tool for building and exploring structured family trees.
A short Guidelines-driven product loop that moves from a real personal need to a working system exercised in practical scenarios.
01 · Idea
Start with a concrete problem or a technology worth understanding.
02 · Self-validation
Check that the idea solves a real need I experience and would actually use.
03 · Mission
Define what the product exists to change and what stays outside its scope.
04 · Use cases
Turn the mission into concrete user flows, decisions, and success conditions.
05 · AI-assisted architecture
Explore options with AI, challenge assumptions, and choose the smallest viable design.
06 · Build & exercise
Implement the system, run it through real scenarios, and refine it from evidence.
Self-hosted telemetry pipeline for tracing services and n8n workflows across a Docker-based homelab.