LLM features
Model call with no timeout or fallback
A slow or failing provider leaves the user on a spinner and may retry without bound.
TermsLLM feature (a product feature that calls a large language model, such as an assistant or a summariser) · golden set (a fixed list of model inputs with recorded expectations, re-run on every model or prompt change) · fault injection (making a dependency fail on purpose in staging to see what the user and the logs show)
mediumseverity if found in a releasesources verified 2026-09-21
Why AI-assisted code produces it
CodeRabbit found error-handling gaps nearly twice as common in AI-co-authored pull requests; model calls are the slowest and least reliable dependency most apps have.
In the same 470-pull-request sample, cross-site scripting issues were up to 2.74 times more frequent in AI-co-authored pull requests; error-handling gaps were nearly 2 times more common and logic and correctness issues 75% more common.
Source: CodeRabbit, 2025-12-17 · verified 2026-09-21
How we detect it
Inject provider errors, rate limits and long delays.
Most associated with
Tools: Cursor, GitHub Copilot, Claude Code, Windsurf, Lovable, Bolt
Stacks: Next.js, React Native, Expo
Checklist items that catch it
Model call failures and timeouts degrade gracefully
automated Inject provider errors, rate limits and 30-second delays.
The user sees a message within the agreed timeout, the request is not retried without bound, and the failure is logged.
Dots: Starter, Growth, Scale. The item runs on every release for the plans marked.
More in LLM features
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