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ai-first-engineering — Claude Code skill: process and review

Sets team process, review gates and architecture rules for codebases where AI agents produce most of the implementation.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓ 
npx skills add affaan-m/ECC --skill ai-first-engineering -a claude-code
Open on GitHub

What ai-first-engineering does

This skill lays out an operating model for teams that ship with heavy AI-assisted code generation. It does not write code for you. It sets the frame: planning quality beats typing speed, eval coverage beats anecdotal confidence, and review shifts from syntax to system behavior.

Inside are architecture requirements and a testing standard. Agent-friendly architecture means explicit boundaries, stable contracts, typed interfaces and deterministic tests. Behavior hidden behind implicit conventions is treated as a liability. Reviewers look at behavior regressions, security assumptions, data integrity, failure handling and rollout safety, while style issues already covered by automation get less time.

There is a hiring section too. A strong AI-first engineer decomposes ambiguous work cleanly, defines measurable acceptance criteria and holds risk controls under delivery pressure. Worth installing if you already have a stream of agent-generated code and need shared review and test rules. If agents touch a couple of files a month, the process will just add overhead.

What it helps with

  • agree on what to review in agent-generated code
  • raise the testing bar for generated code
  • set architecture requirements that agents can follow
  • define measurable acceptance criteria for ambiguous work
  • evaluate engineers on signal instead of typing speed

Example prompts for the agent

  • Help me set up a review process for a team where agents write most of the code
  • What regression coverage should we require for this generated module?
  • Review our architecture: where are the boundaries too implicit for agents?

How to install ai-first-engineering

1Skills CLI (Vercel)

npx skills add affaan-m/ECC --skill ai-first-engineering -a claude-code

2Manually: put the files in place

~/.claude/skills/ai-first-engineering/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/ai-first-engineering/

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Questions about ai-first-engineering

How do I install ai-first-engineering in Claude Code?

Run npx skills add affaan-m/ECC --skill ai-first-engineering -a claude-code. The skill lands in ~/.claude/skills/ai-first-engineering/SKILL.md.

What does ai-first-engineering do?

It describes process, review focus and architecture requirements for teams where agents generate a large share of implementation output. Useful for agreeing on acceptance criteria and test coverage.

Which platforms does the skill support?

Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI and OpenCode. Copilot uses a different command: gh skill install affaan-m/ECC ai-first-engineering.

Source text

SKILL.md · MIT 
---
name: ai-first-engineering
description: Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
metadata:
  origin: ECC
---

# AI-First Engineering

Use this skill when designing process, reviews, and architecture for teams shipping with AI-assisted code generation.

## Process Shifts

1. Planning quality matters more than typing speed.
2. Eval coverage matters more than anecdotal confidence.
3. Review focus shifts from syntax to system behavior.

## Architecture Requirements

Prefer architectures that are agent-friendly:
- explicit boundaries
- stable contracts
- typed interfaces
- deterministic tests

Avoid implicit behavior spread across hidden conventions.

## Code Review in AI-First Teams

Review for:
- behavior regressions
- security assumptions
- data integrity
- failure handling
- rollout safety

Minimize time spent on style issues already covered by automation.

## Hiring and Evaluation Signals

Strong AI-first engineers:
- decompose ambiguous work cleanly
- define measurable acceptance criteria
- produce high-signal prompts and evals
- enforce risk controls under delivery pressure

## Testing Standard

Raise testing bar for generated code:
- required regression coverage for touched domains
- explicit edge-case assertions
- integration checks for interface boundaries

© affaan-m · MIT · affaan-m/ECC

See also

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