Engineering Principles

Readability is a correctness property, not a style preference.

Clever code is a liability the moment its author isn't the one reading it. I optimize for the engineer six months from now with no context — which usually means fewer abstractions, more explicit naming, and functions that do one thing at a call site you can read top to bottom. TypeScript's strict mode isn't there to catch typos; it's there to make illegal states unrepresentable, so entire categories of runtime bugs simply can't compile.

Organize by feature and dependency direction, not by technical layer.

A folder structure of controllers/, services/, models/ tells you nothing about what the product does and encourages every feature to reach into every layer. I organize by feature boundary instead — each feature owns its components, hooks, and data access — with a strict rule that shared primitives never import from a feature, only the reverse. That one-way dependency rule is what actually keeps a codebase untangleable as it grows, far more than any folder-naming convention.

Performance budgets belong in CI, not in a quarterly audit.

Performance regressions are cheapest to fix in the same PR that introduced them and most expensive to fix six months later when three other features depend on the slow path. I treat Core Web Vitals and API latency budgets as build-breaking checks, not dashboards someone checks occasionally. The goal is that a regression is a failed CI check with a clear diff, not a support ticket three weeks later.

Accessible by default beats accessible by audit.

Retrofitting accessibility after a feature ships means relearning every interaction pattern under time pressure. I default to semantic HTML and native interactive elements first, reach for ARIA only when no native element expresses the semantics I need, and treat keyboard navigation as a first-class interaction mode I test myself — not something QA checks with a screen reader once before launch.

Most scaling problems are team and ownership problems wearing an infrastructure costume.

Before reaching for microservices or horizontal sharding, I ask what's actually failing to scale: is it request throughput, or is it that three teams can't deploy without coordinating? Splitting a system before that distinction is clear usually just moves the coordination problem into network calls and adds operational overhead. I scale the parts that are provably the bottleneck, and keep everything else boring.

Abstract on the third repetition, not the first.

The fastest way to a brittle component library is abstracting after one use case, guessing at what 'configurable' means before a second real requirement exists. I let real duplication accumulate to two, sometimes three instances before extracting a shared component — by then the actual variance is visible, and the abstraction fits reality instead of a guess. Components are designed around capabilities ('supports async validation') rather than specific call sites, which is what makes them survive contact with the fourth use case.

Tokens are a contract between design and code, not a color palette.

A design system that only ships color and spacing values misses the point — the parts that actually keep a product feeling coherent as it grows are the ones nobody notices: consistent focus rings, consistent easing curves, consistent elevation logic for what's 'above' what. I treat motion tokens and interaction states as first-class citizens of the system, defined once and referenced everywhere, so a product doesn't slowly accrete twelve slightly different button hover animations.

Let contract violations fail at compile time, not in production logs.

The right API shape depends on the boundary: standard CRUD operations belong on a stable, versioned REST contract, while anything that needs to push updates to the client — live collaboration, status changes, notifications — belongs on a persistent real-time channel like SignalR rather than being forced through polling. I pick the transport based on whether the client or the server needs to initiate the update, not out of habit.

Server state, module-scoped state, and shared entity state are three different problems.

The bugs I've spent the most time debugging all trace back to treating server data, module-specific UI state, and state shared across modules as one undifferentiated blob in a single store. In practice, with Redux Toolkit, that means each feature module gets its own slice for its own concerns, while entities multiple modules need — a contract, a device, a user — live in a shared slice everyone reads from, so no module quietly holds a stale copy of something another module just changed.

Motion should explain a state change, not decorate one.

Every animation I ship has to answer 'what is this movement telling the user?' — that an item was removed, that this panel is now in focus, that an action succeeded. Motion that doesn't communicate causality or hierarchy is just latency with extra steps. I keep a small, shared set of easing and duration tokens across a whole product specifically so animations feel like one coherent system rather than a pile of individually-tuned effects.

Feedback loop speed compounds into shipping velocity more than almost anything else.

The single highest-leverage investment on most teams I've been on wasn't a feature — it was cutting the time between writing a line of code and knowing whether it's correct. Fast type-checking, fast local builds, and a preview deployment on every PR mean an engineer stays in flow instead of context-switching while CI runs. I treat DX tooling as product infrastructure, not a nice-to-have side project.