Matrix42 Device Insights · Sep – Oct 2026
Device Insights: agent-first remediation
A telemetry widget that alarmed people and offered no way out became an app where a service-desk agent sees problems, lets Neo check the device live, approves one fix, and records the outcome.
- Role
- Design and implementation lead across five repositories
- Period
- Sep – Oct 2026
- Stack
- ESM extension (.NET config, flows)Lit + ReactFastViewerMicrosoft IntuneEmpirumCortex tools (Python)constrained PowerShell
- commits in the Insights extension
- pull requests
- repositories and teams
- approved fix at a time
The inherited widget on the self-service home was called AI Actions and Intelligent Insights. It showed critical and warning alerts from device telemetry that refreshed once a day, in raw form, to end users who could do nothing about them. Nobody could say who it was for. In a wartime review before the October release we agreed to replace it rather than polish it.
Service desk first, problems not alerts
- Insights live in the Service Desk, for agents. End users only see something when there is a decision for them to make.
- Problems are grouped into patterns: thirty machines with the same issue is one row, not thirty notifications.
- Root cause is on demand: Neo checks the device live through FastViewer, reads only, and reports what it found.
- Remediation is one proposed fix from an approved set, shown in plain language with what changes and what the user will notice. Nothing runs until the agent approves; Neo checks again afterwards.
- Every outcome is recorded: It's fixed with evidence, Not a problem with a reason, or a ticket carrying the evidence.
Across the endpoint estate
The same pattern carries to unified endpoint management: a missing patch becomes a vulnerability summary, a root cause (not assigned to any patch group) and a three-step plan the admin approves once. These keynote screens were built in HTML from the real product and shown at the customer conference, together with a booth demo running live on a test tenant.
How it was built
The app, data model, importers, flows and cards live in the ESM extension; the device checks and fixes are Cortex tools calling FastViewer, Intune and Empirum with a constrained PowerShell runner; the chat is the shared component. I planned the work as agent-executable slices with a human gate each, built on a real test tenant through esm-devkit, kept the end-to-end test rig and the handbook current with every change, and wrote the engineering overview that handed the app to the product team: architecture, status, the 236 leftover fragments to delete, the P0 gaps and a nine-PR cleanup plan.