## Custom logs

Use [custom logs](/content/docs/custom-logs/index.html) to log parameters such as temperature, max token length, context window size, or any custom settings you need. **How it helps.** Spot configuration changes like temperature shifts or new system prompts that cause unexpected behavior. Every bug report includes version numbers, system prompts, and configuration settings.

### Instant Replay

Use [Instant Replay](/content/docs/instant-replay/index.html) to catch unpredictable bugs when a model returns incorrect responses or hallucinations. **How it helps:**

- **Context drift.** AI apps lose track of earlier context, producing inconsistent or irrelevant outputs. Use Instant Replay to show engineers where the conversation drifted.
- **Error and exception details.** AI bots sometimes fail silently or return a generic error. With Instant Replay you capture the bug the moment it happens. No reproduction required.

_Bonus: with [Jam AI](/content/docs/jam-ai/index.html) you get automatic repro steps, and engineers always get a useful ticket._

### DevTools

Engineers see full stack traces and console logs in [DevTools](/content/docs/devtools/index.html) to spot issues in your AI app. **How it helps. Output variability and latency.** When an AI app returns inconsistent responses, console and network logs reveal unexpected API responses or token limits.

### Backend logs

Capture server-side errors with the [Sentry](/content/docs/sentry/index.html) integration so engineers can diagnose rate limits and misconfigured API endpoints. **How it helps. Backend diagnostics.** When your AI backend fails (HTTP 503 errors, LLM API timeouts), errors log automatically and attach to the bug report.

### Screen recording

Use [video screen recording](/content/docs/video/index.html) to capture the intermediate steps the AI takes while reasoning. **How it helps. Chain-of-thought debugging.** When answers are incorrect or incomplete, capture the reasoning state so engineers can review the steps the model took.