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Engineering operating model for teams where AI agents generate a large share of implementation output.
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SOC 職業分類に基づく
| name | ai-first-engineering |
| description | Engineering operating model for teams where AI agents generate a large share of implementation output. |
| compatibility | opencode |
| metadata | {"origin":"ECC"} |
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:
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".
Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.
