Production incidents span code, metrics, cloud configs, and live clusters yet traditional vendors force you to copy all that telemetry into their store, charging a massive ingestion tax for an agent that remains blind outside its own silo. Join Techstrong and NeuBird AI to learn why the future of production-ops AI isn't another data store, but a virtualized context layer. Discover how querying live tools in place delivers accurate root cause analysis in minutes without data movement or security risks.

Key Takeaways:

- Rethinking the Agent Silo: Why single-vendor AI agents struggle with modern incident triage, and how cross-silo context changes how engineering teams collaborate during outages.

- Lessons from Data Architecture: How applying data virtualization principles (querying in place) to observability offers an alternative to endless telemetry duplication and rising ingestion bills.

- Shift-Left Triage: Exploring how unified analysis across live cluster state, code, and metrics can help teams detect early signal degradation before it turns into a major incident.

- Balancing Autonomy & Control: What an enterprise-ready AI architecture looks like when prioritizing zero-data footprint, zero storage, and human-in-the-loop governance.