Engineering teams should not normalize waiting.
We diagnose and improve the systems between a code change and a trustworthy result: builds, tests, CI, build architecture, releases, and mobile runtime performance.
Four connected performance systems.
A slow feedback loop rarely belongs to one tool. We follow the change through the whole system, identify the constraint that governs it, and choose the smallest intervention that produces a durable result.
Build Performance
Recover the inner loop by improving invalidation, compiler work, scripts, linking, caching, and IDE behavior.
→ VerifyCI and Test Reliability
Reduce queue and execution time while making failures actionable enough that engineers trust the pipeline.
→ ScaleBuild-System Transformation
Evaluate and deliver modularization, Bazel, caching, remote execution, hermeticity, and monorepo changes.
→ ShipMobile Application Performance
Improve binary size, launch, memory, and responsiveness across iOS and Android—and keep them within budget.
→Start at the scale of the evidence.
The first engagement is intentionally bounded. Its output should be useful whether it leads to a focused repair, a larger transformation, or no further work at all.
Establish the constraint
Baseline representative workflows, locate the critical path, and produce a ranked improvement plan.
Prove an improvement
Implement a narrow set of high-confidence changes and compare the result with the baseline.
Change the system
Deliver staged architecture or infrastructure work with migration controls, ownership, and rollout metrics.
Prevent regression
Review trends, investigate new bottlenecks, and keep performance budgets and reliability signals current.
No migration by default.
Bazel, a monorepo, more runners, or a larger modularization effort can be right. They are not substitutes for diagnosis. We recommend them only when the current constraint and expected return justify their adoption and operating cost.
Evidence
Profiles, traces, pipeline histories, failure taxonomies, dependency graphs, and field performance—not anecdotes alone.
Economics
Engineer time, infrastructure spend, incident risk, delivery delay, and the ongoing cost of maintaining the solution.
Fit
Team topology, platform constraints, release requirements, ownership, and the ability to sustain the change.
Verification
A baseline, an expected movement, a measurement window, and a way to detect regression after handoff.
Understand the problem before buying the solution.
Each guide explains why the system matters, what unhealthy behavior looks like, which measurements expose it, and the main improvement paths.
Build performance
Clean, incremental, and no-op builds; invalidation; compiler work; scripts; caching; indexing.
Read the guide → 02 · VerifyCI and test reliability
Queue time, execution graphs, flakiness, retries, test selection, runner economics, and ownership.
Read the guide → 03 · ScaleBuild-system transformation
Modularization, Bazel, remote caching and execution, hermeticity, monorepos, and release engineering.
Read the guide → 04 · ShipMobile application performance
Binary size, launch, responsiveness, memory, production signals, and regression budgets.
Read the guide →