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ai-first-engineering
Engineering operating model for teams where AI agents generate a large share of implementation output.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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Engineering operating model for teams where AI agents generate a large share of implementation output.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Verification loop for Laravel projects: env checks, linting, static analysis, tests with coverage, security scans, and deployment readiness.
Measure browser, API, and build performance baselines and compare regressions before or after changes.
Run browser-based smoke, interaction, visual regression, and accessibility checks against live pages before or after deploys.
Monitor deployed pages and APIs for post-deploy regressions in availability, console errors, and performance thresholds.
Generate or audit design systems, tokens, and visual consistency issues for product UIs.
Pressure-test feature ideas, user journeys, and prioritization decisions before committing to implementation.
| name | ai-first-engineering |
| description | Engineering operating model for teams where AI agents generate a large share of implementation output. |
Use this skill when designing process, reviews, and architecture for teams shipping with AI-assisted code generation.
Prefer architectures that are agent-friendly:
Avoid implicit behavior spread across hidden conventions.
Review for:
Minimize time spent on style issues already covered by automation.
Strong AI-first engineers:
Raise testing bar for generated code: