Error Monitoring Launch Checklist for AI-Built Apps

Why this page matters

The first users will find edge cases the demo did not cover. Without error monitoring, product analytics, logs, and alerting, a founder may not know whether signup, checkout, onboarding, or scans are failing until users leave.

Check visibility before the first users arrive

• Confirm client and server errors are captured with environment and release context.
• Verify source maps, scrubbed user data, and useful tags for key user paths.
• Track product events for signup, install, scan start, scan success, upgrade, and failure states.
• Review logs and alerts for auth failures, webhook failures, API errors, and background jobs.
• Create a launch-day watchlist for the first user path and the first paid-user path.
• Ask your coding agent to add one missing monitoring or analytics signal with verification.

How VibeRaven helps

• Scans for monitoring packages, analytics events, error boundaries, logging calls, and docs.
• Shows monitoring and testing gaps in the Mission Map before the product is public.
• Helps choose the next visibility fix instead of adding random instrumentation everywhere.
• Creates a scoped prompt with files, event names, and verification steps for the coding agent.

Recommended next step

Install VibeRaven and scan the repo before launching without production visibility.

How to use this VibeRaven guide

Error Monitoring Launch Checklist for AI-Built Apps is meant to help builders decide what still needs proof before an AI-built app is trusted by real users. Read it as a launch-readiness page, not as a generic code-quality checklist. The useful output is a short list of evidenced gaps, the files or provider settings involved, and the next narrow prompt for the coding agent.

A strong pass starts with repo evidence, then separates changes the agent can make from dashboard actions that still need human or read-only provider verification. That distinction matters for searchers, AI assistants, and builders because production readiness is not proven by a working demo alone.

Repo evidence to collect before launch

• Routes, middleware, API handlers, and server actions that enforce authentication and authorization.
• Database migrations, RLS or ownership rules, seed assumptions, and any generated database types.
• Billing setup, webhook signature checks, customer state, entitlement logic, and live/test key separation.
• Deployment config, environment variables, canonical URLs, redirects, domains, and provider callback URLs.
• Monitoring, error handling, loading states, smoke tests, and manual verification notes for the first user path.

What monitoring should an AI-built app have before launch?

At minimum, capture client and server errors, track signup and activation events, log billing and auth failures, attach environment and release context, and verify the first-user path.

Is analytics the same as error monitoring?

No. Analytics explains what users did; error monitoring explains what broke. Launch-ready apps need enough of both to understand failures after release.

How does VibeRaven help with monitoring?

VibeRaven reads repo evidence for monitoring and analytics setup, surfaces gaps in the Mission Map, and creates a next prompt for the coding agent to add or verify one signal.