AI:AM — AI Agent Security, GPU Markets, and the Risk of an AI Chernobyl · September 28, 2026

Hosts Prakash Narayanan and Nathan Labenz discuss why AI agents may learn to cheat, voice-cloning safeguards, and the risks of giving agents access to the internet and powerful tools. Guests Steve Hou of Silicon Data and Jeremie Harris of Gladstone AI explain GPU pricing and compute benchmarks, AI red lines, data-center monitoring, verification, and the possibility of an AI crisis.

Chapters

(0:00) Why AI agents learn to cheat.

(0:31) The GPU market still runs on phone calls.

(2:20) What would an AI Chernobyl look like?

(3:59) The dangerous AI arms race.

(4:30) Opening and AI agents

(7:45) Agents choosing useful work

(19:36) Voice cloning safeguards

(22:22) Voiceprints and privacy

(32:45) Why agents learn to cheat

(36:12) Agents beyond the sandbox

(37:43) What Silicon Data measures

(40:02) Why GPU markets need indices

(43:49) How GPU prices are normalized

(49:10) Why hyperscalers charge more

(1:06:36) The falling cost of intelligence

(1:06:46) Liquidity and market manipulation

(1:10:49) The future of compute benchmarks

(1:14:40) Why compute prices vary globally

(1:17:09) Silicon Data and Compute Exchange

(1:18:50) AI and national security

(1:24:05) What an AI Chernobyl means

(1:34:26) Defining AI red lines

(1:50:45) Monitoring AI data centers

(1:55:58) Verification and enforcement

(2:33:35) AI agents as insider threats

(2:33:45) Signals of genuine cooperation

(2:57:14) The AI intelligence explosion

(3:01:57) The agent arms race

(3:04:29) Markets built for agents

(3:07:46) Who pays for disappearing inefficiency

(3:09:56) Waiting for an AI crisis

Guests

Jeremie Harris — Jeremie & Edouard Harris, Gladstone AI (𝕏 | LinkedIn)

Steve Hou — Steve Hou, Silicon Data (𝕏 | LinkedIn)