ndb_hugo: A Knowledge-First Portfolio Architecture
How this portfolio models skills as evidence, not claims — and why that distinction matters for building a trustworthy knowledge system.
Fablab manager, maker community architect, electronics tinkerer. I build things, document what I learn, and let patterns emerge from the evidence.
Documented projects, learnings, and technical deep-dives — each backed by timestamped evidence.
How this portfolio models skills as evidence, not claims — and why that distinction matters for building a trustworthy knowledge system.
A shift in how I approach technical decisions — from intuition-first to evidence-first — and what changed when I started demanding proof before conviction.
What started as networking confusion became a custom bridge plugin. Somewhere in between, I taught it to interns — and teaching is where the real understanding happened.
Extracted from documented work. Each backed by timestamped evidence. Confidence reflects evidence density, not self-assessment.
The Hugo-native workflow for authoring posts, patterns, and timeline moments. Manual precision while the backoffice is being built.
A decade of fablab management, Ostrom's principles tested in practice, working groups and assemblies.
Dormant Docker knowledge activated by a teaching project, then converged with infrastructure skills.
ESP32 projects, PCB design, sensor networks, smart valve controllers — hands-on making as knowledge creation.
Turning points where accumulated experience suddenly made sense — the moments when patterns clicked.
Writing a pattern about the act of writing patterns. The system is eating itself, in the best way.
Maps of Making federation protocol reuses the same convergence-detection patterns from spacecraft telemetry. A decade apart, the problems rhyme.
The Sewer Museum valve controller worked on first deployment. Twelve years of accumulated hardware intuition compressed into a single confident afternoon.
Teaching Docker to interns forced me to explain things I'd only understood intuitively. The teaching didn't follow the learning — it completed it.
Reading Ostrom for the third time, I finally understood why her principles felt familiar — I'd been reinventing half of them through trial and error at the fablab.
Building my first ESP32 sensor network, I kept reaching for patterns from satellite systems I'd worked on seven years earlier. Different scale, identical architecture.