Unsupervised Learning

A longer form discussion on exactly how and why AI will replace knowledge workers.Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

I think the future is cheaper and Open Source SOTA models combined with context, not custom, narrow models.Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

A troubling thought about what we will think about high-quality content in the future. Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

There are a bunch of different transitions happening right now—all at the same time, all (I think) heading in the same direction. Here is a long-form exploration of the various pieces.Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

A welcome back and early entry into 2026.  Sponsored by: Knocknoc!Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

How we can use an output-based system to judge whether or not different kinds of technology achieve understanding or intelligence. Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

How humans and AI models both share the weakness of deterioration without novel inputs. Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

Karpathy is confusing LLM limitations with AI system limitations, and that makes all the difference. Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

How going from exploration to exploitation can help you as both a consumer and creator of everything.Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

Some thoughts on how novelty and attention magnify the time that we have. Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

➡ Stay Ahead of Cyber Threats with AI-Driven Vulnerability Management with Maze:https://mazehq.com/ In this conversation, I speak with Harry about how AI is transforming vulnerability management and application security. We explore how modern approaches can move beyond endless reports and generic fixes, toward real context-aware workflows that actually empower developers and security teams. We talk about: The Real Problem in Vulnerability ManagementWhy remediation—not just prioritization—remains the toughest challenge, and how AI can help bridge the gap between vulnerabilities and the developers who need to fix them. Context, Ownership, and VelocityHow linking vulnerabilities to the right applications and teams inside their daily tools (like GitHub) reduces friction, speeds up patching, and improves security without slowing developers down. AI Agents and the Future of SecurityWhy we should think of AI agents as “extra eyes and hands,” and how they’re reshaping everything from threat detection to system design, phishing campaigns, and organizational defense models. Attackers Move FirstHow attackers are already building unified world models of their targets using AI, and why defenders need to match (or exceed) this intelligence to stay ahead. From Days to MinutesWhy the tolerance for vulnerability windows is shrinking fast, and how automation and AI are pushing us toward a future where hours—or even minutes—make the difference. Subscribe to the newsletter at:https://danielmiessler.com/subscribe Join the UL community at:https://danielmiessler.com/upgrade Follow on X:https://x.com/danielmiessler Follow on LinkedIn:https://www.linkedin.com/in/danielmiessler Chapters: 00:00 – Welcome and Harry’s Background01:07 – The Real Problem: Remediation vs. Prioritization04:31 – Breaking Down Vulnerability Context and Threat Intel05:46 – Connecting Vulnerabilities to Developers and Workflows08:01 – Why Traditional Vulnerability Management Fails10:29 – Startup Lessons and The State of AI Agents13:26 – DARPA’s AI Cybersecurity Competition14:29 – System Design: Deterministic Code vs. AI16:05 – How the Product Works and Data Sources18:01 – AI as “Extra Eyes and Hands” in Security20:20 – Breaking Barriers: Rethinking Scale with AI23:22 – Building World Models for Defense (and Attack)25:22 – Attackers Move Faster: Why Context Matters27:04 – Phishing at Scale with AI Agents31:24 – Shrinking Windows of Vulnerability: From Days to Minutes32:47 – What’s Next for Harry’s Work34:13 – Closing ThoughtsBecome a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.