AI Debugging Assistant
Overview
The AI Debugging Assistant is an intelligent analysis tool, one of the Resolve Agent capabilities. It transforms mobile crash debugging from a manual process into a structured path to resolution.
Rather than requiring developers to sift through opaque stack traces and fragmented logs, the Assistant consolidates telemetry data and applies AI-driven analysis to surface the root cause, reproduction steps, and pattern insights for every mobile crash.
Key Capabilities
Root Cause Analysis : Plain-English explanations of failures with evidence-based context linking to specific code and network calls.
Common Reproduction Steps : Sequential user-action reconstructions that eliminate the “cannot reproduce” loop.
Pattern Insights : Multi-factor correlation analysis that identifies whether a crash is a global issue or a localized edge case.
Where to Find It
When viewing any crash report, the Assistant panel is available in the right sidebar. All three capabilities (Root Cause, Reproduction, Patterns) are accessible from a single interface with no context-switching required.
Root Cause Analysis
Root Cause Analysis goes beyond the stack trace to provide a complete understanding of why a crash occurred. It is especially useful for opaque crashes such as OOMs or ANR crashes that lack a clear trail.
Executive Summary : A plain-English explanation of the failure written for quick comprehension. The summary describes what happened, what component was affected, and the likely trigger.
Evidence-Based Context : Direct links to the specific lines of code or network calls that were active at the moment of impact.
Contributing Factors: Supplementary insights into conditions that may have contributed to the crash. These can include memory pressure or leaks, elevated backend latency, specific OS or device configurations, and thread contention or deadlocks.
Common Reproduction Steps
The most time-consuming part of fixing a bug is proving it exists on your own machine. The Automated Reproduction Steps feature reconstructs the sequential user actions leading to a crash, eliminating guesswork and reducing the “cannot reproduce” cycle.
How It Works
The Assistant analyzes session telemetry, including screen navigation events and user interactions (taps, scrolls, input) to build a chronological timeline of what the user did before the crash.
You need to enable the user repro steps feature to be able to get this capability.
Pattern Insights
Pattern Insights answer the critical triage question: is this a global catastrophe or a localized edge case? The feature correlates data points across your entire crash footprint to surface the common thread behind an issue.
Multi-Factor Correlations
Pattern Insights can identify compound conditions where a crash requires two or more factors to occur simultaneously. For example, the Assistant might report that a crash happens specifically when the Login V2 feature flag is enabled on iOS 26, combining both a feature flag and an OS version dimension into a single insight.
Workflow Guide: Choose Your Own Flow
The AI Debugging Assistant is designed around flexibility. While we recommend a default sequence, every developer has a different mental model for solving problems. The interface supports starting from any capability.
Recommended Flow
1
Root Cause Analysis
Understand what happened and why
2
Reproduction Steps
Confirm how to trigger the issue locally
3
Pattern Insights
Determine the scope and impact of the issue
Alternative Flows
Suspect a feature flag issue? Start with Pattern Insights to quickly confirm whether a specific flag correlates with the crash, then move to Root Cause for the technical details.
Visual learner? Start with Reproduction Steps to see the user journey, then review Root Cause for the underlying technical explanation.
Triaging for severity? Start with Pattern Insights to assess scope (global vs. localized), then use Root Cause only if the issue warrants deeper investigation.
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