{
  "id": 5950754,
  "title": "AI Can Write the Code. Your Real Job Is Becoming the Reviewer — Here’s How to Do It Properly",
  "url": "https://urgent.news/2026/09/06/ai-can-write-the-code-your-real-job-is-becoming-the-reviewer-heres",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-06T09:25:26.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/robertadam987_/ai-can-write-the-code-your-real-job-is-becoming-the-reviewer-heres-how-to-do-it-properly-551l"
  },
  "original_language": "en",
  "account": "AI-generated code is becoming increasingly common, but developers must still act as reviewers to ensure the code is correct, secure, maintainable, and worth merging. Here's a review workflow to follow:\n\n1. Begin with the requirement, not the diff. Ask questions about security, expiration dates, and user session handling before diving into the code.\n\n2. Examine the architecture, not just the syntax. Ensure business logic is in the right layer and check whether the agent duplicated existing services or ignored your project structure.\n\n3. Test the happy path and unexpected cases. Try breaking the implementation by simulating API timeouts, duplicate requests, record conflicts, and more.\n\n4. Don't rely solely on AI-generated tests. Encourage AI to find five ways the implementation could fail and review or add critical tests yourself.\n\n5. Be cautious of new dependencies. Check if they are necessary, actively maintained, secure, and don't bring in unnecessary transitive dependencies or incompatible licenses.\n\n6. Pay attention to permissions beyond just the code. Ensure the agent has appropriate access to filesystems, terminals, Git repositories, environment variables, databases, and cloud services.\n\n7. Review both added and removed code in the diff. Developers often focus on added lines but forget to examine what was taken away. Consider why code was deleted and if it caused any regressions.\n\n8. Leverage automation to verify AI-generated changes. Run tools like type checkers, linters, and automated testing suites to catch potential issues that may have been missed during manual review.",
  "summary": "AI can write code now. That part is no longer surprising. You can describe a feature to Copilot, Claude Code, Cursor, Codex, or another coding agent and get a working implementation in minutes. Sometimes it is genuinely impressive. But there is a bigger question: Can you actually trust the code enough to ship it? According to the Stack Overflow 2025 Developer Survey, 84% of developers use or plan…",
  "key_points": [
    "Begin review with requirement analysis, not code diff",
    "Examine architecture and business logic placement",
    "Test happy path and edge cases, don't rely on AI tests"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}