Detect Issues Early. Fix Faster. Improve Continuously.
This fast paced, interactive workshop helps you define the diagnostic insight measures and operating approach that make GenAI solution health visible, comparable, and actionable across your business. You’ll leave with a practical diagnostics insights plan to detect defects early, accelerate triage, and close the loop with repeatable fixes—so reliability improves as adoption grows, not after it
breaks.
The Challenge
It can be challenging to keep GenAI solutions healthy in production—because failures can be subtle, fast-moving, and hard to diagnose:
- Health signals aren’t consistently tracked: Teams monitor a few metrics, but miss the diagnostic signals that predict drops in quality, trust, and adoption.
- Issues aren’t routed into operational workflows: Diagnostic insights sit in logs and dashboards instead of flowing into support, escalation, and troubleshooting routines.
- Triage is manual and reactive: Without automation, teams spend time sorting issues instead of fixing the highest-impact problems first.
If diagnostics aren’t operationalized, GenAI reliability becomes a recurring fire drill.
Our Solution
A structured, hands-on workshop that helps you define a targeted GenAI diagnostics insights plan—so you can detect issues early, accelerate response, and improve solution health continuously.
- Explore our GenAI Insights Best Practices catalog: Review proven patterns for solution health monitoring, diagnostics, triage automation, and closed-loop improvement.
- Define your priority diagnostics measures: Select a small set of core indicators that surface defects, latency, usage drops, and quality regressions.
- Define your reporting frequency: Establish a cadence for health and diagnostics reviews that fits production support and release cycles.
- Assign an accountable owner: Clarify ownership for monitoring, triage workflows, escalation, and knowledge capture.
- Define actionable next steps: Identify what to instrument, dashboard, automate, and embed into support operations first.
Area of Focus
- Tracking GenAI solution performance across metrics
- Detecting defects, latency, and usage drops
- Linking diagnostic insights to support workflows
- Automating triage and prioritization of issues
- Closing the loop through resolution and knowledge sharing
Participants Will
- Leave with a defined set of GenAI diagnostics measures spanning reliability, performance, quality, and adoption signals.
- Identify a detection approach for early warning signals (defects, latency spikes, quality drops, usage decline).
- Define a support workflow integration plan so diagnostic insights route into triage, escalation, and troubleshooting.
- Establish an automation plan for prioritization, alerting, and response—so teams focus on highest-impact issues first.
- Produce a closed-loop improvement plan that captures fixes, updates knowledge, and reduces repeat incidents.
Who Should Attend:
Solution Essentials
Format
Virtual or in-person
Duration
2 Hours
Skill Level
Beginner to Advanced (non-technical friendly)
Tools
Optional diagnostics measures worksheet, monitoring-to-support workflow map, triage prioritization rubric, and closed-loop knowledge template