AICAD: Artificial Intelligence Capabilities For Attack & Defense

Unsupervised Learning

AI is changing cybersecurity at a fundamental level—but how do we decide what to build, and when? In this episode, I outline a structured way to think about AI for security: from foundational ideas to a future-proof system that can scale with emerging threats.

• Rethinking Human Workflows as Intelligence Pipelines
By mapping tasks into visual workflows, we can pinpoint exactly where human intelligence is still required—and where AI agents are most likely to replace or enhance us.

• Using AI to Understand and Manage Organizational State
I introduce the concept of AI state management: building systems that track your current and desired security posture in real time, and using AI to bridge the gap—automating insights, decisions, and even actions across your environment.

• Building a Cyber Defense Program Inspired by Attacker Playbooks
Instead of waiting for threats, I propose a new framework based on attacker capabilities—what they wish they could do now and in the near future—and how to proactively prepare by building a continuously adapting AI-powered defense system.

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Chapters:
00:00 - Framing the Future: Two Key Questions on AI and Cybersecurity
01:28 - Intelligence Pipelines: Visualizing Human Work as Replaceable Workflow
06:10 - Theory of Constraints: How Attackers Are Bottlenecked by Human Labor
10:42 - Defining Agents: What Makes AI Different From Traditional Automation
12:08 - AI State Management: The Universal Use Case for Automated Intelligence
16:53 - Real-World Demo: Unified Context AI for Security Program Management
26:30 - Advanced Uses: Reassigning Projects, Updating KPIs, and Security Reports
34:58 - Automating Security Questionnaires With AI Context Awareness
38:43 - ACAD Framework: Predicting and Preparing for Future Attacker Capabilities
47:40 - Defender Response: Building AI-Driven Red Teams and Internal UCCs
52:25 - Final Answers: How Software and Security Change With AI Agents
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