{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Chain of Thought | AI Agents, Infrastructure & Engineering","title":"How Cisco Secures Personal AI Assistants for 90,000 Employees | DJ Sampath","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/16e31515\"></iframe>","width":"100%","height":180,"duration":2631,"description":"Cisco is giving each of its 90,000 employees a personal AI agent. Some of those same employees are already connecting agents from outside the security boundary without asking IT. DJ Sampath, SVP and GM of AI Software and Platform at Cisco, walks through what had to be in place before the rollout: scanning every prompt, sandboxing each agent, keeping agents multi-tenant, scanning the skills and tools people bring in, and settling which identities an agent may act as.\nNew episodes, the ideas behind them and Conor's essays land in the Chain of Thought newsletter first. Subscribe: https://newsletter.chainofthought.show/\nWe recorded at Cisco's San Francisco office, a block or two from OpenAI, where Cisco was an early Codex design partner. DJ explains how engineers rework their skills files with each model generation, how per-engineer PR bots review agent-written code, and why defenders now have to move at agent speed when an exploit can show up within minutes of a CVE going public.\nWe cover:\nWhat Cisco's IT team required before rolling out MyAgent to 90,000+ employees\nPrompt injection by email, and why the first integration everyone makes is the riskiest\nCisco's AI security taxonomy, DefenseClaw, and Project Quarry, a new open source language for describing agent behavior and policy\nHow the agents are actually used: daily briefs, meeting actions, live dashboards, 2 trillion tokens in a single week\nWhy skills files need refactoring every model generation\nDiscovering and governing shadow agents with zero trust access\nMulti-model code review, spec drift, and evals built from pull request traces\nHow Cisco Cloud Control was built in about eight months with agentic coding\nChapters:\n(0:00) Guardrails tested inside Fortune 100 companies\n(0:21) Securing 90,000 employee AI agents\n(8:04) Cisco's open source agent security stack\n(12:01) Project Quarry: a policy language for agents\n(17:07) Personal agent use cases at Cisco\n(19:08) Early design partner on Codex\n(23:15) Reassessing...","thumbnail_url":"https://img.transistorcdn.com/KnEL-9mfZGF096BNQ33xaE_zVyhLvBNV8rHifHuvYgc/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hYWM2/NmYwMjc4MmJiYTYw/ZTI5NGZhNzRhNmZh/NTU0OC5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}