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Speed and Scale: How Today's AI Datacenters Are Operating Through Hypergrowth

12 snips
Feb 3, 2026
Kris Beevers, CEO and co-founder of NetBox Labs and veteran network engineer with a Ph.D., discusses how modern AI datacenters handle hypergrowth. He talks about modeling infrastructure as a single system of record, tackling power and procurement bottlenecks, and using programmatic blueprints and digital twins to speed builds. He highlights rapid iteration, robotics in racking, and the need for vendor data standards for automation.
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INSIGHT

NetBox As The System Of Record

  • AI datacenter builds are an enormous, chaotic investment spanning power, cooling, racks, cabling, and configs.
  • NetBox acts as the system of record tying physical and logical infrastructure data together to manage that chaos.
INSIGHT

Bottlenecks Constantly Shift

  • Building AI datacenters is a continuous constraint-satisfaction problem where the bottleneck shifts over time.
  • Power, procurement, logistics, and human/robot labor each become the primary limiter at different phases.
ANECDOTE

Turbines In The Parking Lot

  • Some builders are literally buying turbines and putting them in parking lots to get power online quickly.
  • That pragmatic, scrappy approach shows how fast teams must move when the grid can't keep up.
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