sdlc-implement

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Atualizado25 de junho de 2026 às 13:47

Use during active implementation of a planned, tested feature - once a spec and failing tests exist and it's time to write code. Drives the agent to implement against the spec + tests, reserves your attention for the hard 20% (ambiguity, edge cases, correctness), and reviews code as it appears instead of accepting it blind. Make sure to use this whenever you are coding a feature that already has a spec/tests, or says "now build it", "make the tests pass", "implement the slice". Fourth step of the SDLC loop.

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Jeff-Kazzee

Jeff-Kazzee/sdlc-skills

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Ocupações relacionadasSOC

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Desenvolvedores de softwareInformática e Matemática·SOC 15-1252

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SKILL.md

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name

sdlc-implement

description

sdlc-implement - build to green, own the hard 20%

Fourth beat of the SDLC loop. The agent does the well-specified bulk; you focus your judgment where the model is weak. The goal is the tests from sdlc-test going green without you having shipped code you don't understand.

Why this matters

The 80% problem: agents generate ~80% of a feature fast, but the last 20% - edge cases, error handling, integration points, subtle correctness - needs context they lack, and those failures are dangerous because the code "looks right" and may pass basic tests. The winning posture isn't accepting everything faster; it's spending your attention exactly where AI struggles.

Procedure

Implement against the contract. Point the agent at the spec + failing tests and have it work to green, one slice at a time.
Guard the 20%. Personally scrutinize: ambiguous requirements (ask, don't assume), edge cases from the plan, integration seams, and correctness under the unhappy path. Don't delegate these to the model's confidence.
Review as it appears. Read the code as it's written. Be skeptical of anything clever. Verify imports are real packages (hallucinated deps are a known failure mode). Confirm error handling covers realistic failures, not just the happy path.
Keep slices small and checkable. After each slice, run the tests. Don't let a big unverified blob accumulate.
Pick the mode that fits. Conductor (hands-on, real-time) for tricky/unfamiliar logic; orchestrator (delegate, review output) for well-specified slices against established patterns.

Output

Working code for the slice that passes its tests, that you understand well enough to maintain.

Gate

Tests green + you understand the code -> hand to sdlc-review before it ships. Note any agent miss (hallucinated import, missed edge case) for sdlc-learn.

References

Load these as needed:

references/the-80-percent-problem.md - where to spend your attention vs let the agent run.
references/conductor-vs-orchestrator.md - picking the right working mode for the task.

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Use BEFORE generating implementation code for any feature with verifiable behavior. Writes the tests (and evals, if output quality is judgment-based) FIRST, as the contract that defines "correct," so the agent implements against a real target instead of a vibe check. Make sure to use this whenever you say "implement", "write the code for", "build the function/endpoint/feature" - intercept and do tests first - and also on "write tests" or "add coverage". Third step of the SDLC loop and the single highest-leverage habit.

2026-06-254

name

sdlc-implement

description

sdlc-implement - build to green, own the hard 20%

Why this matters

Procedure

Implement against the contract. Point the agent at the spec + failing tests and have it work to green, one slice at a time.
Guard the 20%. Personally scrutinize: ambiguous requirements (ask, don't assume), edge cases from the plan, integration seams, and correctness under the unhappy path. Don't delegate these to the model's confidence.
Review as it appears. Read the code as it's written. Be skeptical of anything clever. Verify imports are real packages (hallucinated deps are a known failure mode). Confirm error handling covers realistic failures, not just the happy path.
Keep slices small and checkable. After each slice, run the tests. Don't let a big unverified blob accumulate.
Pick the mode that fits. Conductor (hands-on, real-time) for tricky/unfamiliar logic; orchestrator (delegate, review output) for well-specified slices against established patterns.

Output

Working code for the slice that passes its tests, that you understand well enough to maintain.

Gate

Tests green + you understand the code -> hand to sdlc-review before it ships. Note any agent miss (hallucinated import, missed edge case) for sdlc-learn.

References

Load these as needed:

references/the-80-percent-problem.md - where to spend your attention vs let the agent run.
references/conductor-vs-orchestrator.md - picking the right working mode for the task.