Online masterclass to cover AI-native observability in 2026

A virtual masterclass titled "Crash Course: AI-native observability" is scheduled to run from August 31 to September 8, 2026, according to its listing on dev.events.

What it covers

The session is billed as a crash course, suggesting a condensed, practical format rather than a multi-track conference. The focus is on observability practices tailored to AI-native systems, the monitoring, tracing, and debugging challenges that arise when applications are built around machine learning models and agentic pipelines rather than traditional deterministic code.

Who it's for

This format typically targets engineers, SREs, and platform teams responsible for keeping AI-driven applications reliable in production. Observability for AI systems differs from conventional application monitoring because it has to account for model drift, non-deterministic outputs, and the added complexity of chained model calls or agent workflows.

Logistics

The event is confirmed as fully virtual, with no physical venue listed. Its status is currently marked as scheduled, and the listing does not yet include a public registration link or the name of the hosting organizer.

Given the roughly week-long window between the start and end dates, the "masterclass" is likely structured as a short series of sessions rather than a single-day webinar, though the source listing does not break down a detailed agenda.

Interested engineers can find the current listing on dev.events under the event page for "Crash Course: AI-native observability." As with many early-stage listings, further details, including speakers, agenda, and a direct sign-up link, are expected to be added closer to the date.