Prove the happy path
- Can build CRUD without copy-paste controller logic
- Can map persistence failures to API semantics
- Can verify durable effects
- Can explain why response contracts should not be accidental Prisma types
This is the transfer exercise for Phase 11: Persistent Task CRUD API. The detailed lessons are now closed-book reference material. Your task is to prove that the phase outcome can be reproduced from requirements, repository evidence, and debugging—not by copying a finished implementation.
Target artifact Working /tasks API supporting create/list/read/update/delete against PostgreSQL with consistent error behavior.
Acceptance criteria - Write the behavior and constraints before implementation. - Identify the owning layer and every boundary crossed. - Implement the smallest complete vertical slice. - Verify the happy path from outside the implementation. - Demonstrate at least one expected failure path. - Run the phase-relevant quality checks. - Review the diff for accidental duplication, leaked responsibilities, missing validation/authorization, and hidden environment assumptions.
Evidence packet Save the command/request used, expected result, actual result, one failure reproduction, the fix, and a short explanation of why the final responsibility belongs where it does. This packet is more valuable than a screenshot of a green page because it demonstrates repeatable engineering reasoning.
Stretch Change one requirement after the first implementation. Measure which files must change. If a tiny domain change causes unrelated layers to move, use that evidence to discuss coupling before adding another abstraction.
A guided lesson proves you can follow. A capstone proves you can transfer the model to a requirement with fewer cues.
Define Task create/update/read response shapes before implementation.
Implement create through the service and verify both HTTP response and database row.
Implement list/read with deterministic ordering and missing-record behavior.
Implement partial update without overwriting omitted fields accidentally.
Implement delete semantics and decide whether the API returns the resource, metadata, or no content.
Run a manual CRUD script from empty database to cleanup and save it as a repeatable smoke test.
Run the phase mastery checklist without looking at the provided implementation.
Perform a short architecture review and document one trade-off you consciously accepted.
Requirement -> implementation diff -> verification -> controlled failure -> diagnosis -> final proofDo 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 mental model and acceptance criteria. Rebuild one smaller slice from first principles before reopening the source.
Choose an external observer: HTTP client, browser, database query, test runner, health endpoint, or deployment log, and capture deterministic evidence.
Extend the phase artifact with one requirement not used in the guided example while preserving the same ownership rules and verification strategy.
Implement create through the service and verify both HTTP response and database row.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.PATCH treats omitted values as null/empty
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.