Explain errors with AI

We’ve added an AI‑powered explanation layer that gives short, plain‑language descriptions of errors and suggested fixes alongside the original error details. Read the raw error and the AI explanation together so troubleshooting is faster and more approachable for everyone on your team.

What’s new

• AI explanations next to errors — concise, human‑readable summaries and recommended actions appear next to the original error message so you see both context and guidance in one place.
• Where explanations appear — available in three locations:
  • Scenario designer: inside a module’s error details panel.
  • Scenario execution history: on the failed run’s details page; when multiple modules failed you can request an explanation per module.
  • Insights page: in the Failed executions table so triage from Insights is faster.
• Per‑error granularity — request explanations for individual module errors in a run so you can focus on the most critical failures.
• Human‑friendly remediation steps — suggestions include likely root causes, next diagnostic commands or checks, and safe first steps to resolve the issue.
• New‑designer only — the feature is available in the new scenario designer experience to ensure tight integration with the editor’s right panel and Live Trail.

How it works (quick)

1. Open a scenario in the new scenario designer and run it (or view a failed run from the execution history).
2. When a module shows an error, open its error details. Click Explain with AI (or the Explain icon) next to the error.
3. The AI returns a short explanation and suggested next steps that display alongside the original error text and timestamps.
4. On the failed run details page you can click Explain for each failed module to get per‑module guidance.
5. From the Insights page, open a failed execution row and request the AI explanation directly from the Failed executions table for quick triage.

Why this matters

• Faster troubleshooting: get a clear, prioritized description of what likely went wrong and what to try next without translating cryptic logs.
• Lower cognitive load: non‑engineers and new team members can act on failures faster because recommendations are written in plain language.
• Targeted remediation: per‑module explanations mean you can address the root cause rather than chasing symptoms across the scenario.
• Integrated triage: explanations in Insights let operations and SREs begin investigation from high‑level dashboards without repeatedly switching UIs.

Getting started

1. Switch to the new scenario designer (toggle in the upper‑right of the editor) if you haven’t already.
2. Run a scenario that triggers an error, or open a failed execution from the execution history or Insights → Failed executions table.
3. Click Explain with AI next to the error to generate the explanation. Review the suggestion and apply recommended checks or fixes.
4. Use the explanation to create follow‑up tasks, add context to support tickets, or iterate on scenario design to prevent recurrence.

Troubleshooting (quick)

• No Explain button visible: Ensure you are in the new scenario designer and that your organization has an active AI license. If both are true and the control is still missing, contact your admin or open a support ticket.
• Explanation seems irrelevant or incorrect: Explanations are diagnostic suggestions based on available error data. Provide more context by expanding the module error details or including Live Trail entries, then retry Explain. If persistent, capture the run and open a support ticket with the executionId and screenshots.
• Multiple errors in one module: The AI summarizes the visible error context. Expand the raw details (timestamps, request/response) before requesting an explanation for better results.
• Sensitive data concerns: Explanations are generated from the error and the run metadata shown in the UI. If your organization restricts sending certain data to AI services, review your admin AI/data policies before using the feature.

Documentation & support

For full steps and examples, see the Experience League article: Explain a scenario error with AI.

Feedback and support

Tell us how AI explanations help your team or suggest improvements (examples: bulk explain for all failed modules in a run, configurable explanation depth, redact sensitive fields) by:

• Posting in the Experience League Community scenario editor or Insights threads.
• Opening a support ticket via the Admin Console Support portal for organization‑specific issues.

Try Explain with AI to shorten investigation time, reduce guesswork, and empower more team members to triage scenario failures—then tell us what explanation controls you’d like next.