What would make you trust AI-generated web scraper code?

We're launching AI Scraper Builder by ScrapeOps on Product Hunt, and we'd love feedback from developers, data teams, AI builders, and anyone who has dealt with web scraping in production.

Most AI scraping tools focus on no-code extraction, browser plugins, or instant data output.

We're exploring a slightly different angle:

What if AI generated real scraper code that developers could inspect, edit, and run in their own stack?

With AI Scraper Builder, you provide a few sample URLs from the same domain and generate scraper code for Python or Node.js. It supports common scraping tools and frameworks like Scrapy, Playwright, Selenium, BeautifulSoup, Requests, Puppeteer, Cheerio, and Axios.

The goal is to reduce the repetitive first-pass work:

• Inspecting HTML

• Writing selectors

• Handling JavaScript-rendered pages

• Mapping data into structured JSON

• Creating scraper boilerplate

• Preparing code that can later connect into proxy, monitoring, and scheduling workflows

We're trying to make AI useful for real scraping work, not just a demo that extracts data once.

So we'd love to ask:

What would make you trust AI-generated scraper code enough to use it in a real project?

Would it be:

• More accurate selectors?

• Clear validation messages?

• Self-healing suggestions when extraction fails?

• Support for your favorite framework?

• Proxy and anti-bot integration?

• Clean schema-based JSON output?

• Monitoring and alerting after deployment?

• The ability to export and fully own the code?

Curious how others think about this. Is code-first AI scraping more useful than no-code extraction for your workflow?