Writing production-ready Scrapy spiders with opencode

AI-enabled code editors can now conjure scraping code on command. But anyone who has used a generic coding agent to build a spider knows what comes next: a plausible-looking file that falls apart the moment it hits a real website. The selectors are fragile, the error handling is missing, and the structure ignores everything Scrapy actually expects from production code. The problem is not the AI. It's the prompts, the context, and knowing where to let the agent drive and where to stay in control. This article walks through using opencode to build Scrapy spiders that are actually deployable, covering setup, the prompts that work, and the pitfalls that will burn you if you are not careful. Why opencode works well for scraping projects Most AI coding agents are designed around general-purpose software projects. opencode is different in one important way: it is terminal-native, model-agnostic, and designed to operate inside your actual working directory. It reads your project, understands y