I’m starting this site as a learning diary I can keep consistently—part research notebook, part field notes. I learn best by writing: capturing what I’m studying, what I’m developing, what I’m testing, what surprised me, and how my thinking changes over time.
This will be a place for personal exploration shared in public:
• small lessons that compound
• longer write-ups when an idea deserves more rigor
• stories and experience-based patterns (kept general and anonymized) that help explain how systems and teams behave in real conditions
My recurring interest is the gap between what looks healthy on paper and what holds up under stress—especially as AI tools become part of how we design, build, test, and operate software. Sometimes everything appears stable until one assumption fails, one dependency misbehaves, or one signal gets misread.
I’ll aim for a consistent structure as I write:
• start simple (what the idea is)
• move into mechanisms and examples (how it behaves)
• note uncertainty (what I don’t yet know)
• end with next steps (what I’ll test or read next)
This isn’t a set of instructions for others to follow. It’s documentation of learning—written carefully, revised as I learn more, and shared in case it helps someone else reason more clearly.
If you’re reading along, welcome. I’m glad you’re here.