Typed end to end, tested where it matters.

The demo was fast.
Production was not.

Rendering strategy, state management, data fetching and boundaries — written down with the options rejected, so nobody relitigates them in six months.

One schema source generating client types, server validation and database access, so drift becomes a compile error instead of an incident.

A skeleton in production in week one, behind a flag. The pipeline is proven when it is cheap to fix rather than the week before launch.

Bundle size, Core Web Vitals and interaction latency measured on every pull request, with the build failing on regression.

Semantic structure, focus management and keyboard paths handled as the components are written, verified to WCAG 2.2 AA rather than audited later.

Error tracking, tracing and the dashboards your on-call rotation will actually use, wired up before the first real user arrives.

Portals and self-service applications where speed, accessibility and reliability are all commercially visible.

The screens a team lives in all day, where density and keyboard speed matter more than visual novelty.

Where two or three user types share surfaces and the permission model is most of the complexity.

Data-heavy interfaces that have to stay responsive as accounts grow past the demo dataset.

Replacing an ageing interface incrementally, without a flag-day rewrite and without retraining every user.

Streaming output, editable results and cost controls, built as product rather than as a prompt box.

The same build,roughly a third fewer hours.

Days back per sprint

Components, types, fixtures and API clients generated from the schema rather than typed by hand. The saving compounds across every feature, and it is the least interesting code in the build.

Coverage without the cost

Edge cases enumerated from type signatures and component states, so the null, the empty array and the four-thousand-row list get tested. Previously this was the coverage teams skipped when the sprint got tight.

A week down to an afternoon

Framework upgrades and codemods applied uniformly across hundreds of files. Work that used to be deferred for quarters because nobody could justify the hours becomes routine maintenance.

Faster, at the same standard.

The efficiency is real because the review is not skipped. Every line goes through the same pipeline, the same tests and the same named owner, which is what stops speed turning into a maintenance bill later.

When we would
not start here

Most legacy pain is a handful of specific problems. Replacing everything to fix three of them rarely survives contact with the timeline.

Engineering a flow nobody has validated means building the wrong thing efficiently. Two weeks of research is cheaper than a quarter of build.

For internal CRUD at low volume, an off-the-shelf tool ships faster and costs less to run. We will say so.

An application with no maintainer becomes a liability at the first dependency vulnerability. That role has to exist before build.

Real-user LCP, INP and CLS on the pages that matter commercially, tracked per release rather than sampled once.

How often you can ship and how long a change takes to reach production. Both are proxies for how safe the pipeline feels.

Share of deploys needing a fix or rollback. Rising numbers mean the tests are not covering what they should.

Not overall coverage, which is easy to game, but coverage of the flows that cost money when they break.

Tracked per pull request. Performance decays gradually, so it has to be measured continuously to be held.

Automated checks in CI plus a manual pass per release, reported rather than accumulated silently.

What a web build
usually needs beside it