What would make an AI-enabled attack on critical infrastructure less dangerous—and how should organizations prepare for risks they cannot fully predict? Evan Miyazono, founder and CEO of Atlas Ignota, discusses emergency supplies as a bridge to help, privacy-preserving agent identity, software verification and the commitments needed to put safeguards into use.
Then Edward Hu, who leads model training research at Mercor, explains how real business apps and records can support more meaningful tests of workplace agents. The conversation examines the gap between completing a bounded assignment and holding a job, why evaluation rubrics need to be reliable, and how enterprises can test prompts, tools and skills before customizing models.
Show Notes
Atlas Ignota founder Evan Miyazono explains how emergency supplies, privacy-preserving agent identity, software verification and adoption commitments fit into a strategy for reducing AI-assisted cyber risks. Mercor model-training research lead Edward Hu describes workplace agent benchmarks built from real business records, why task scores do not prove job readiness, and how enterprises can test tools and workflows before training models.
Chapters
(0:00) Grid outages and AI job tests
(1:22) An AI agent played the instruments in Reaper
(3:49) OpenAI’s model broke a math barrier overnight
(4:53) Are data centers pushing bond yields toward 6%?
(7:54) Meet Evan Miyazono of Atlas Ignota
(8:56) A grid blackout nobody is positioned to fix
(10:43) Why Atlas stopped building and started recruiting
(12:37) Experts have ideas; adoption is the hard part
(14:03) Was that AI attack an accident?
(15:22) Agent identity without exposing refugees and journalists
(19:08) Why Evan keeps some of his agents private
(20:24) AI could make software proofs radically cheaper
(23:08) Why two weeks of food and water
(24:42) Who can make a guardrail universal?
(27:01) Meet Edward Hu from Mercor
(27:51) APEX gives agents assignments, not jobs
(31:09) Mercor bought real companies for their data
(33:47) Company records expose the task-to-role gap
(35:22) Why math fell before customer service
(38:29) Fix the harness before you train the model
(41:05) Most enterprises will distill, not run RL
(42:01) Agent swarms buy speed, not compute efficiency
(43:34) One rubric rewarded a dozen incompatible answers
(46:49) Perfect accounting scores do not replace accountants
(48:55) Clear verifiers let AI surpass human experts
(51:18) Recording every work trace carries social costs
(53:43) AI coworkers need better organizational tests
(55:15) Factory know-how still lives outside software
(56:43) Agents now need far less project management
(59:25) Is the $200 plan a loss leader?
(1:01:18) Permission fatigue is an unsolved problem
(1:03:02) Anthropic’s API is still too slow for production
Guests:
Edward Hu — Head of AI Modeling, Mercor (𝕏 | LinkedIn)
Evan Miyazono — Founder & CEO, Atlas Ignota (𝕏 | LinkedIn)
