Engineering notes, written slowly
I build applications, write about AI, APIs and system design - the silent bugs, the wiring, and the boring parts that quietly hold everything up.
The demo is the test
A feature that passes every test can still be broken in ways the test suite is structurally unable to see. Four kinds of blindness that only surfaced once real stakeholders started using an AI booking assistant in a room.
Codebase health is a lagging indicator
A tooling migration, some dependency bumps and a telemetry schema. None of it reaches a roadmap, and all of it decides whether a codebase is pleasant to work in three years from now.
Designing a logging system for an AI service
Building a standardised logging system for an AI assistant service: making consistent structured logging the path of least resistance, and thinking carefully about what an AI service should and shouldn't persist.
From merged pull requests to a performance review
Merged pull requests already record what you did. Turning them into a work log with an LLM is easy; the hard part is the defensive rules that stop it corrupting the vault.
On console warnings and the things we don't remove
Removing unused documentation tooling and fixing prop type warnings: small changes that don't ship features but make the codebase a bit more honest.
Two kinds of correctness: currency bugs and ghost feature flags
A currency display bug in the exchange flow and a feature flag referencing something that never existed in production. Two different kinds of silent incorrectness.