Data Architecture · Quantitative Systems · Analytics
Building systems that turn data into decisions
Long-form essays on the architecture decisions that age well, paired with the production systems that test them. Written and operated by an independent senior practitioner.
Every proprietary dependency is a future rewrite. Why open source first is an infrastructure decision, not an ideology — and why exit cost is the system property nobody designs but everyone eventually pays for.
Engineering labor has migrated from writing code to specifying what code must be. Why context, not prompting, is the discipline that bounds AI-assisted development.
Cloud platform commitment is the largest architectural decision most teams make, and the one most often made invisibly. Why "best service for the job" produces a system whose exit cost the vendor sets.
PCA is a linear algebra operation, not a magic wand. It finds directions of maximum variance — but variance isn't signal. When financial data violates every assumption PCA makes, "90% explained variance" might mean you've captured 90% of the noise.
AI makes custom tooling accessible to anyone who understands the underlying systems. The value of knowing how things work keeps going up, not down.