Run a team of migration agents that inventories the work, transforms each slice in isolation, verifies it, and merges under strict discipline.
Operate an error budget so reliability decisions follow a written policy instead of an argument: burn-rate alerts, feature freezes, and a clear escalation path.
Make payment operations safe to retry so a network timeout never charges a customer twice. Use when calling a payment API, processing webhooks, or building any money-moving…
Profile native code with perf and flamegraphs, then read cache, syscall, and allocation behavior to find the real bottleneck.
Sort and compare text using locale collation rather than byte order, so lists read correctly in every language.
Treat any serialized bytes from outside the program as hostile, parsing them through schema-validated formats instead of native object reconstructors.
Test localisation readiness with generated pseudo-translations that expand, accent, and bracket text, before any real translation exists.
Choose the level of abstraction a platform exposes so it hides complexity without hiding what teams need to control.
Design the empty, loading, error, and edge states that most designs skip but users constantly hit. Use when designing any screen that can be empty, loading, or fail, which is…
Choose and size a JVM garbage collector from latency goals and allocation behavior, and read GC logs before tuning flags.
Keep agent usage within budget through context discipline, model selection, and caching, without degrading results. Use when agent costs are rising or long sessions are expensive.
Use leases with fencing tokens for mutual exclusion across machines, or restructure to need no lock at all.
Return errors an agent can act on, distinguishing retryable failures from permanent ones and never leaking internals. Use when building MCP tools that will fail in production.
Construct test objects through builders and factories with valid defaults so each test states only the fields it cares about.
Scale collaborative sessions across instances with room routing, shared state, and controlled fan-out. Use when one server can no longer hold all active sessions.
Run an on-call rotation that is sustainable, with alert hygiene, fair distribution, and follow-through on what caused the pages.
Choose the structure whose operations match how the data will actually be used, rather than defaulting to a list or a map.
Build repeatable data transformations that refresh on demand, replacing manual cleaning steps with a recorded pipeline.
Help users design effective organizational structures. Use when someone is thinking about team structure, deciding between functional vs.
Issue, install, renew, and debug TLS certificates so connections stay encrypted and trusted without surprise expiry.
Cascade OKRs so team and individual goals ladder up to company strategy without sandbagged targets or scoring that rewards easy wins.
Translate between an external service's data model and your own, handling mismatches, nulls, and enum drift explicitly.
Migrate workloads to the cloud with honest 6R triage, dependency mapping, and rehearsed cutovers with rollback.
Support the recurring people function with agents that maintain onboarding paths, keep policy documents current, prepare review inputs, and flag gaps, while every human decision…
Decide where a web app keeps tokens and state by reasoning about the XSS blast radius of each store, not by convenience.
Use agents to triage contracts and policies, extract obligations, flag unusual terms, and prepare a lawyer's review rather than replace it.
Coordinate agents through a shared written workspace they each read and update, instead of passing messages.
Write a Google-style design doc that argues a decision through context, goals, and rejected alternatives before code is written.
Keep card data out of your systems so compliance obligations stay minimal, and know what remains in scope when it cannot.
Model UI as explicit finite states so impossible combinations cannot render. Use when a component juggles interacting booleans, shows contradictory states, or a flow has grown too…
Decide between one repository and many by tooling readiness, coupling, and team autonomy, and plan the migration.
Quiz and coach the user for the Anthropic Claude certification exams using this repository's blueprints and official exam guides.
Compose async JavaScript with promises and async/await correctly, propagating errors and cancelling with AbortController.
Translate company objectives into desk-level goals and weekly work, keeping the line from a task to the objective visible.
Review translated text for accuracy, register, and fit in context, with a rubric rather than an impression.
Size worker pools, queue depths, and batch widths against the real bottleneck so parallelism adds throughput instead of contention.
Use ORMs for their productivity while avoiding N+1 queries and knowing when to drop to raw SQL. Use when working with an ORM or debugging the performance problems ORMs quietly…
Generate several independent attempts, score them against explicit criteria, and select or combine the winner, instead of iterating one attempt.
Run a public forum where users help each other, with seeding, moderation, and staff presence that keeps answers accurate.
Pin every fixed bug with a test that fails before the fix and passes after, kept beside the code it guards.
Protect a mobile app by storing secrets in the platform keystore, pinning certificates only where rotation is controlled, and treating obfuscation as delay rather than defense.
Assemble a promotion packet that proves sustained impact at the next level, with calibrated scope claims and evidence a committee can verify.
Run a team of growth agents that designs an experiment, builds the variant, analyzes the result, and passes an ethics gate before anything ships.
Handle angry, distressed, or unreasonable customers without escalating the conflict or capitulating on things you cannot give.
Pass App Store and Play review on the first attempt and recover fast from rejections. Use when preparing a mobile submission, writing store metadata, or responding to a review…
Place human approval at the points where being wrong is expensive or irreversible, with enough context to decide quickly. Use when agents perform work that has real consequences.
Design alerts that fire on the symptoms users feel, using error-budget burn rate, a page-worthiness test, and a runbook link on every rule.
Back-of-envelope calculations for system design. Use when estimating QPS, storage, bandwidth, or latency for capacity planning.
Correct or forgive misspelled queries without turning precise searches into fuzzy guesses. Use when users mistype and get nothing, or when fuzzy matching returns irrelevant…
Route each request to the agent best suited to it, with a fallback and an explicit unknown path, instead of one generalist handling everything.
Version and share seed datasets so they stay small, realistic, and reproducible across a team. Use when tests or local environments depend on fixture data that is drifting,…
Operate as an engineering manager who grows people, protects delivery health, hires deliberately, and shields the team from noise.
Flatten nested conditionals into early returns that handle edge cases up front and keep the main path unindented. Use when logic marches rightward into deep nesting.
Scale training from one GPU to many by moving through data parallel and sharded FSDP modes, overlapping communication with compute, and reading the efficiency curve to find the…
Find why threads are stuck forever by dumping their state and building the wait-for graph that reveals the lock cycle.
Stop UI redress attacks by declaring who may frame your pages, using frame-ancestors as the primary control and X-Frame-Options as the fallback.
Retire API surface with sunset headers, usage tracking, migration guides, and enforced timelines. Use when removing an endpoint, field, or version that consumers depend on.
Decide per operation what happens during a network partition, and design degraded modes that fail safe. Use when planning multi-node or multi-region behavior under network failure.
Detect and reverse the point where users stop reading, by measuring engagement decay and cutting volume before they mute. Use when open rates are falling or mute rates are rising.
Observe external dependencies so their degradation is visible before users report it and attributable when it happens. Use when your service depends on APIs you do not control.