Grab built an automated system called Data Production Issues (DPIs) that detects when certified data products fail their contracts, diagnoses root causes without manual intervention, and fixes common failures automatically. The system keeps data quality issues actionable by filtering noise, assigning problems to the right owner, and closing issues only when the underlying data actually recovers.

• DPIs use a standardized Data Health API with four error categories (upstream, platform, job, data) to route failures to the correct team without requiring platform-specific knowledge, enabling consistent incident management across Grab's heterogeneous data systems.
• The triage phase deduplicates alerts and groups related failures by root cause, preventing responders from drowning in repetitive notifications while ensuring only real contract breaches become operational issues.
• Hugo, Grab's ingestion platform, consolidates signals from multiple sources into a three-layer diagnosis workflow that automatically identifies root causes and recommends fixes, eliminating manual log inspection and shortening remediation time.

Claude Code now generates live, interactive web pages—artifacts—from your session context, codebase, and connected tools. These auto-updating, versioned pages share via a single link for incident reports, PR walkthroughs, dashboards, and more, with org-level access controls and no extra infrastructure.

• Claude Code can now turn a session's context (code, logs, tool connections) into a live, shareable web page instead of a static chat answer.
• Artifacts auto-update and version at the same URL, so an incident report or dashboard stays current without re-sharing links.
• Access is locked to org accounts with role-based permissions, retention policies, and compliance API access—nothing public by default.
• Rolling out in beta to Claude Team/Enterprise via CLI or desktop app, with prebuilt use cases spanning legal, security, FinOps, design, and PM workflows.