Writing
Notes on shipping production backend & AI systems — LLM evaluation, correctness-critical logic, and turning regulation into testable code.
Articles
Control plane, data plane, durable storage: structuring a managed search engine in RustHow I split one search engine into three systems in Rust: Postgres for metadata, tantivy for the index, object storage for durability. The ordering a create request takes, and the quota race it avoids.10 min
Shipping LLM features that survive productionMost LLM features work in the demo and break in the real world. Here is the evaluation layer that keeps them honest — and how to measure 'correct' before you ship.7 min
Turning a regulation into testable codeHow to take a dense statute from primary source to an audit-ready detector — separating literal text from enforcement practice, and deriving tests from the regulation itself.8 min
Building a GDPR-compliant backend: an engineer's checklistGDPR is usually treated as a legal checkbox bolted on at the end. The decisions that actually carry legal weight are architectural — and they are cheap early, expensive late.9 min
The EU AI Act for software engineers: what you actually have to buildThe EU AI Act is written for legal teams. Here is the translation into system requirements — risk tiers, the obligations that touch your code, and what to build before the deadlines bite.9 min
Implementing the FATF Travel Rule: an engineer's viewThe FATF Travel Rule reads simply and implements anything but. The places literal text and enforcement practice diverge — and how to build a transmission layer that survives an audit.8 min
Property-based testing for compliance logicWhen you can't see the reference corpus, you derive the tests from the regulation itself. How property-based testing makes a rules engine trustworthy on inputs you never hand-wrote.7 min