01

How this failure appears in Claude Code

Claude Code is often used for repository-level feature work, refactors, tests, and command-line development. With AI repair loops, the builder may show a healthy preview while the published domain, another user role, a refreshed session, or a connected service reveals the real failure.

02

Why the obvious AI fix may miss it

broad autonomous changes can expose hidden assumptions, leave partial migrations, or satisfy tests that do not represent production behavior. For this symptom, the investigation also considers lost context, duplicate implementation, no regression tests, unclear architecture. Editing the visible component again will not help if that component is only reporting a failed request or policy decision.

03

The evidence that narrows the diagnosis

Useful first evidence includes identify the canonical file; write a short reproduction; save a known-good commit. For Claude Code, also identify whether the behavior differs between editor preview, shared preview, exported code, and the real production URL.

04

Safe access for a Claude Code repair

A useful access plan may include repository and branch, command output, tests, change history, and reproducible production differences. Start with names, URLs, logs, and screenshots. Do not put passwords, recovery codes, private API keys, or service-role credentials in the initial request.

05

What not to do before a repair

Do not paste the entire project into repeated chats or accept multi-file rewrites without review. Preserve the last known-good Claude Code version or export and avoid several broad prompt changes at once. That keeps the failure reproducible.

06

Repair inside Claude Code or outside it?

Keep the repair in Claude Code when its settings, workflows, code surface, and test tools expose the responsible layer. Export, source-code work, or a bounded migration becomes appropriate when the builder hides the cause, cannot support a safe implementation, or prevents repeatable production testing.