Interested in being a guest? Email us at [email protected]

Want proof that better IT experience can be engineered, not wished into existence? From the floor at Gartner, we sit down with Lakeside to explore how a lightweight, 29‑year-old agent design built for scarcity is suddenly perfect for today’s edge. When compute, memory, and network were expensive, the team designed a platform that sips resources, keeps data close to the device, and structures it cleanly. That constraint-driven approach unlocks speed, privacy, and resilience for modern fleets spread across remote and hybrid work.
We dig into how first‑party endpoint telemetry becomes actionable insight: structured SQL tables that AI can query without guesswork, a built-in server that responds to natural language, and clear answers to everyday pain like “Why is Outlook slow?” Instead of sifting through noisy logs or waiting on remote sessions, IT can see patterns, correlate changes, and resolve issues before they cascade. The payoff shows up in the metrics executives care about—lower MTTR, fewer escalations, and help desk costs cut by up to 50 percent. Just as important, employees feel the difference in fewer slowdowns and faster recovery.
There’s a practical path to proactive support: detect drift early, isolate risky cohorts, and push targeted fixes across the fleet. By keeping much of the data local and imposing a consistent structure, Lakeside shortens the path from question to answer while preserving performance on the endpoint. That makes scale manageable and ROI visible, which resonates with the “bosses of the bosses” walking the Gartner halls. If you’re wrestling with sprawl, inconsistent tooling, or elusive root causes, this conversation shows how to turn devices into their own best administrators and turn IT data into durable advantage.
If this resonates, follow the show, share it with a teammate who fights ticket queues, and leave a quick review telling us the one metric you’d improve first.

Support the show

More at https://linktr.ee/EvanKirstel