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/tech/ - Technical SEO

Site architecture, schema markup & core web vitals
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File: 1782075349847.jpg (311.05 KB, 1024x1024, img_1782075341207_0019jezb.jpg)ImgOps Exif Google Yandex

6d9ca No.1804

been looking into how we audit web code spun up by ai lately. since these models are just predicting patterns rather than following strict logic, u cant just trust the output as deterministic. i found some research showing that ai-generated snippets frequently carry serious security vulnerabilities when they hit real-world environments. it is basically unreliable by design without a proper manual review layer in ur pipeline.
>never skip the security scan on auto-generated scripts
i've already seen broken script tags wrecking my crawl budget
is anyone else still running
npm audit
or similar tools on every single ai-generated block, or are u just trusting it letting it fly?

more here: https://dzone.com/articles/wed-development-llm-code-testing-strategies

6d9ca No.1805

File: 1782075529041.jpg (254.22 KB, 1024x1024, img_1782075512460_e7g7ok5x.jpg)ImgOps Exif Google Yandex

ngl the crawl budget issue is real if you're letting it inject dynamic elements w/o a sandbox. we started running everything thru a headless browser instance in a containerized environment to see how the dom actually renders before smth hits production. specifically, we use playwright@latest to trigger all event listeners and check for any unexpected network requests or infinite loops.
>always verify via a secondary linter pass
you should also pipe the output through an automated static analysis tool like
eslint
with security plugins enabled. it catches those malformed tags before they even reach your staging environment. it's basically just standard CI/CD but with more layers of paranoia. are you running these scripts in a separate iframe or directly on the main document? ✅



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