{
  "id": 14368972,
  "title": "AI Made Me Faster at Coding. So Why Did I Feel Like a Worse Developer?",
  "url": "https://urgent.news/2026/10/14/ai-made-me-faster-at-coding-so-why-did-i-feel-like-a-worse-developer",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-14T04:37:42.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/sanikbajrachary/ai-made-me-faster-at-coding-so-why-did-i-feel-like-a-worse-developer-4gj9"
  },
  "original_language": "en",
  "account": "A developer, accustomed to working with React, Node.js, and Python, decided to experiment with new technologies like Svelte and Go. Inspired by AI's potential to accelerate development, they crafted a dashboard for tracking Jira tickets, pull requests, code coverage, build status, and meetings. Utilizing AI assistance through Copilot, they built the dashboard incrementally, testing the UI and requesting documentation for each feature.\n\nHowever, upon reviewing their own code, the developer realized they had a superficial understanding of Svelte and Go. While they knew the overall architecture, the intricacies of the codebase were unclear. Debugging a bug or implementing a small feature became a daunting task, as the developer found themselves having to unravel the entire codebase, which was a stark contrast to their previous learning experience. They missed the satisfaction of grappling with a problem, hitting roadblocks, and ultimately resolving them. The current approach left them feeling less engaged, as the AI handled most of the challenging aspects, and they were concerned about relinquishing valuable learning opportunities.\n\nTo address these concerns, the developer implemented several changes to their AI-assisted coding workflow. Firstly, they focused on understanding what they were shipping. Instead of rushing to complete a feature, they broke it down into smaller, manageable tickets and asked AI to split the work accordingly. Before diving into coding, the developer engaged in a conversational process using AI's \"plan mode,\" asking clarifying questions and challenging suggestions that didn't make sense. When faced with unfamiliar concepts like circuit breakers, they took the initiative to learn about them independently.\n\nThe developer then followed an \"implement, then review\" approach, utilizing a more cost-effective AI model for implementation while reserving more powerful models for code review. By reading and testing the code themselves, they ensured a deeper comprehension of how things worked, even when faced with complex tasks. This newfound diligence allowed them to commit changes with greater confidence and move on to the next ticket. While this process took longer than relying solely on AI, it was still quicker than the developer's previous method, and it helped them maintain a sense of ownership over the code they were producing. Ultimately, the developer aimed to strike a balance between leveraging AI's efficiency and retaining their own understanding and expertise, as they recognized that if the code broke in production, they would be held accountable.",
  "summary": "I’ve been working with React, Node.js BFFs, and Python for years. We use them at work, so there hasn’t been much reason to pick up something new. But with AI making it easier to get started, I figured, why not try Svelte and Go? I watched a few YouTube videos, learned the basics, and started building a dashboard for myself. Nothing too fancy. Just my Jira tickets, pull requests, code coverage,…",
  "key_points": [
    "Developer experimented with AI tools like Copilot for Svelte and Go coding",
    "Found superficial understanding of new technologies despite AI assistance",
    "Implemented changes to AI-assisted workflow, focusing on comprehension over speed"
  ],
  "editors_take": "Relying too heavily on automated code generation risks eroding fundamental technical expertise and the deep comprehension necessary to troubleshoot complex production issues effectively.",
  "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."
}