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Troubleshooting8 min readPublished September 19, 2026Updated September 22, 2026

How to troubleshoot an AI-built application

Start from the symptom, not the code. Each visible failure has a short list of plausible causes, and one check that separates them. This page is the routing table; the individual guides handle each destination in depth.

The symptom index

What you seeMost likely causeThe one check
Blank white pageA crash while renderingBrowser console, first red error
Empty list, no errorAccess rules or a filterQuery the table as the owner
Login does nothingRedirect URL or session handlingNetwork tab during the login round trip
401 everywhereNo credential attachedIs the Authorization header sent?
403 on one actionPermission ruleDoes the rule name this user?
Works locally onlyEnvironment configurationCompare variables in both environments
Deploy shows old codeWrong branch or failed buildCheck the latest deployment's commit
429 from an AI providerRate limit or a loopCount requests in ten seconds
Payment taken, nothing changedWebhook not received or not verifiedProvider's webhook delivery log
Emails never arriveUnverified sending domainProvider's delivery log, then spam

How do you tell a front-end problem from a back-end one?

Open the Network tab and trigger the action. If no request is made, the problem is in front-end code — a handler that never ran, a condition that blocked it. If a request is made and fails, the problem is the request, the credential, or the server. If the request succeeds and the page still looks wrong, it is rendering.

What information should you collect before asking for help?

  1. 1The exact steps to reproduce, and who you were signed in as.
  2. 2Whether it fails in production, development, or both.
  3. 3The exact error text, copied not paraphrased.
  4. 4The failing request's URL, status code and response body.
  5. 5What changed most recently — the last commit or the last configuration edit.

That list is also what makes an AI tool useful rather than destructive. Paste those five things and you get a diagnosis; paste 'it is broken' and you get a rewrite.

What did the AI probably do?

  • Added code that assumes a value exists — a column, a variable, a session.
  • Made something work for the owner account without testing another user.
  • Introduced a second way of doing something that already existed, so two paths now disagree.
  • Removed a line it considered redundant that was load-bearing.
  • Reported success after editing rather than after testing.

Checking the most recent diff against this list resolves a surprising share of 'it worked yesterday' reports.

When should you stop and revert?

When the live site is broken for real users, when you have made three changes without improvement, or when you can no longer describe the original failure. Revert to the last known good state, confirm it is genuinely good, and start the method again from a clean base.

Frequently asked questions

Where do I find server logs?
In your hosting platform's dashboard, under the deployment's functions or runtime logs. Browser tools cannot show you server-side errors.
Is it ever the AI provider's fault?
Sometimes — check their status page for a 5xx or a sudden wave of failures. It is worth thirty seconds before an hour of rewriting.
How do I know a fix is real?
You can reproduce the original failure on the old version, cannot reproduce it on the new one, and can explain why in one sentence.

Practice this in MessyDev

Reading it once helps. Doing it once sticks. These are the hands-on parts of MessyDev that cover the same ground.

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