Mission Rebuild the capability of Phase 22 without following the exact code line-by-line. The goal is transfer: can you use the ideas when the variable names, UI, or route shape changes?
Required outcome Use TanStack Query as the owner of asynchronous server state with deliberate query keys, freshness, invalidation, mutations, and pagination behavior.
Required artifact TaskFlow query/mutation layer with stable keys, list/detail caching, invalidation, filters, and debugging via devtools/logs.
Constraints • Start from the previous phase checkpoint or a fresh branch. • Use the course architecture boundaries, but do not copy the reference implementation until after your first attempt. • Keep changes scoped to the capability. • Preserve validation, authorization, error handling, and observability expectations already earned in earlier phases. • Record any design decision where more than one implementation is reasonable.
Acceptance criteria • Can explain cache freshness vs garbage collection. • Can design stable keys. • Can reconcile mutations. • Can debug stale/wrong cache entries.
Independent build sequence 1. Install/configure one QueryClient at the correct client boundary. 2. Define a query-key factory that includes every parameter affecting the result. 3. Move task-list fetching into query options and observe loading/error/success/cache states. 4. Add task detail query and prove list/detail caches are distinct. 5. Implement create/update mutations and choose between invalidation and direct cache updates deliberately. 6. Add pagination/filter URL state and inspect how query keys prevent cross-filter cache corruption.
Self-review Compare your implementation to the reference only after the acceptance criteria pass. Differences are not automatically mistakes. For each difference, ask: does it preserve the same contract, security boundary, correctness, maintainability, and operational behavior? Keep the alternative when you can justify it with evidence.
Stretch challenge Change one assumption: more users, a second tenant, a slow network, an expired session, a concurrent mutation, a deployment restart, or a failed dependency. Predict whether your design still behaves correctly. If not, document the next architectural improvement rather than adding complexity blindly.
Phase exit Run the relevant checks, inspect Git diff, and write a three-sentence summary: what the system can do now, which boundary owns the new responsibility, and which failure you now know how to diagnose. Only then mark the phase complete.
TanStack Query is a server-state synchronization system, not merely a fetch helper. Cache identity, freshness, invalidation, and mutation semantics are the core model.
Restate the goal of “Phase Synthesis & Independent Challenge” as one observable behavior. Write the success signal before touching code.
Trace the boundary map: component → query key → cache state → fetch/mutation → reconciliation. Mark the one boundary this lesson changes.
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
Connect the slice to TaskFlow’s phase artifact: TaskFlow query/mutation layer with stable keys, list/detail caching, invalidation, filters, and debugging via devtools/logs.. Verify behavior from the outside as a user or API client would.
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
export const taskKeys = {
all: ["tasks"] as const,
list: (filters: TaskFilters) => ["tasks", "list", filters] as const,
detail: (id: string) => ["tasks", "detail", id] as const,
};Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.
Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.
Without copying the final source, create a second small scenario that applies “Phase Synthesis & Independent Challenge” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Move task-list fetching into query options and observe loading/error/success/cache states.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Invalidating too broadly or not at all
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.