+ Replays the draft as it would be saved against the session's stored events. Nothing is saved. Test a session where + the rule should fire and one where it should stay silent. +
+ {error &&{error}
} + {outcome &&Explanation preview
+{formatInlineMarkdown(explanation)}
+No analyze rule flagged this failure.
+ {mcpAccess ? ( + <> +The evidence is still here. Investigate it with your AI assistant:
+debug-session for session
+
+ {sessionId}
+
+ + {"Not connected yet? "} + + Set up your AI assistant + + . +
+ > + ) : ( +Check the event timeline for the first error and what led up to it.
+ )} + {canReport && ( ++ Something the product should detect on its own? Send it to the maintainers with Report Session. +
+ )} +Close the loop
++ When your assistant finds a cause that no rule knows yet, it can write the rule. It checks the draft against + the rule schema and dry-runs it against real sessions of your tenant: it should fire on the failed one and + stay silent on a healthy one. Nothing is saved until a Tenant Admin creates the rule in the portal. +
++ {line.text} +
+ ))} +Structured from the start
- The agent turns each enrollment into typed events while it runs. Your assistant queries them through dedicated - tools, so its answers rest on data instead of guesswork. + The agent turns each enrollment into typed events while it runs. Your assistant starts there, so its answers + rest on data instead of guesswork. When the facts run out, clients that work with files can fetch the + session's diagnostics package and read the original log lines.
+ get_session_diagnostics + {" — back to the original line, for clients that work with files"} +
+ ++ + {index + 1} · {station.title} + + {station.tag} +
+{station.text}
+Evidence first
++ Every enrollment is recorded while it runs, so the evidence is still there after someone resets the + device. Known problems are flagged by analyze rules. Unknown ones you investigate with your AI + assistant — and what you find becomes a rule that catches the next one. +
++ The first failure becomes evidence. The next one is a known problem. +
+ + How the AI digs in +- Real-time monitoring, automated root-cause analysis, and on-demand diagnostics for - Windows Autopilot — deployed once via Intune, live minutes later. + Real-time monitoring, automated root-cause analysis, and evidence that survives a + device reset — deployed once via Intune, live minutes later.
- Your AI assistant reads the whole session for you — and finds the root cause a human - would dig for all afternoon. This analysis is real. + Your AI assistant reads the whole session for you, finds the root cause a human would dig + for all afternoon, and writes the rule that catches it next time. This analysis is real.