Fix Google AI Studio Deployment Cache
Budget: $15 – $25 USD
I deployed a site generated in Google AI Studio and pointed it to my live domain on a cloud host (AWS / Google Cloud). Inside the admin dashboard I can add icons, edit notifications, and update copy, but those edits only show while I’m logged in—they never reach the public version, even after clearing browser cache, cookies, or using incognito windows.
Something in the live stack—likely a cache layer, build-time configuration, or an incorrect database / environment variable—is preventing changes from persisting. I haven’t investigated any server-side or CDN caching yet, so you’ll have full freedom to audit that first.
What I need from you
• Trace why edits save for the admin session but not for anonymous visitors.
• Disable, purge, or correctly configure any cache/CDN layers so updates propagate instantly.
• Verify build pipeline and environment variables so the live instance points to the right database and storage buckets.
• Deliver a concise hand-off note summarizing what you changed and where to manage future updates.
You should be comfortable with Google AI Studio projects, static-to-dynamic builds, serverless or container deployments on AWS or Google Cloud, and typical cache layers (CloudFront, Cloud CDN, Cloudflare, Varnish, etc.). If this sounds routine to you, let’s get the site reflecting real-time changes today.
Something in the live stack—likely a cache layer, build-time configuration, or an incorrect database / environment variable—is preventing changes from persisting. I haven’t investigated any server-side or CDN caching yet, so you’ll have full freedom to audit that first.
What I need from you
• Trace why edits save for the admin session but not for anonymous visitors.
• Disable, purge, or correctly configure any cache/CDN layers so updates propagate instantly.
• Verify build pipeline and environment variables so the live instance points to the right database and storage buckets.
• Deliver a concise hand-off note summarizing what you changed and where to manage future updates.
You should be comfortable with Google AI Studio projects, static-to-dynamic builds, serverless or container deployments on AWS or Google Cloud, and typical cache layers (CloudFront, Cloud CDN, Cloudflare, Varnish, etc.). If this sounds routine to you, let’s get the site reflecting real-time changes today.
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