Engineer in Los Angeles. I write here about the things I build and the statistics, infrastructure, and design decisions behind them.
Posts
- One A/B testing product, two very different worlds: building for Shopify and the open web
What it actually takes to run one A/B testing product on both Shopify and arbitrary HTML sites — auth, event ingestion, available data, and why a half-dozen switch statements beat the interface I almost wrote.
- Three boring Claude features inside a stats app — and the patterns that made them ship
LLM features that sit quietly inside a SaaS product: a pre-launch reviewer, an async anomaly detector that returns strict JSON, and a cached post-experiment analyzer. The wrapper is 100 lines.
- Bayesian A/B testing in 200 lines of Go: what 5,000 samples actually buys you
A walkthrough of a production Bayesian A/B testing engine: Beta-Binomial for conversion, Normal for revenue, Monte Carlo sampling, and the LiftDistribution trick that makes credible intervals on dollars interpretable.