Daniel Miessler is a cybersecurity and AI engineer turned founder, based in the San Francisco Bay Area. He shares insights on cybersecurity, artificial intelligence, technology, and human behavior through essays, tutorials, and technical content on his blog.
161 articles from this blog
Analysis of Anthropic and OpenAI IPOs, viewing AI as a massive opportunity for decision support and the elimination of gaps between current and ideal states.
Analyzes how AI will create new jobs but only for the top 1-5% of the population, leading to societal inequality.
Analysis of how suddenly-great open source AI could pose an economic threat to the US by disrupting major tech companies.
Explores why AI lacks true human creativity due to absence of intrinsic drives and subjective experience, and what it would mean to give AI real feelings.
A philosophical argument for keeping Markdown over HTML as the primary format for AI use-cases, valuing text as a pure form of thought.
Analysis of why most companies struggle with AI adoption due to unclear goals and lack of organizational readiness.
Announcing PAI 5.0, an open-source Life Operating System for personal AI infrastructure, featuring a new algorithm, memory system, and digital assistant.
Explores how AI is not the villain in job displacement; companies have always sought to automate work, and the real issue is reliance on corporate jobs.
Analysis of AI layoffs: companies replace mediocre employees with AI tools for top performers, not replace top talent.
A voice transcript conversation about David Deutsch's knowledge theory and the PAI algorithm for personal AI infrastructure.
Explains why AI models optimized for coding improve at all tasks, treating coding as a meta-skill for structured problem-solving.
Analysis of weak vs. strong enterprise AI rollouts, highlighting the importance of solid guidance and practical examples over vague mandates.
Explores how AI enables replacing SaaS tools with custom-built solutions, forcing companies to rethink their value and defensibility.
Analysis of Jensen Huang's interview with Dwarkesh Patel on China chips, highlighting risks of supplying advanced tech to adversaries.
A reflection on the Mythos AI model, arguing it's just the next step in rapid AI evolution, not a shocking breakthrough.
Explores the future of personal AI, arguing we're moving toward a single digital assistant with full context about our lives.
Explains good vs bad harness engineering for AI, emphasizing context over prescriptive instructions.
Argues that AI doesn't need to be perfect to disrupt business and cybersecurity, as most current systems are mediocre (3/10) and AI at 5/10 can still dominate.
Analysis of Mythos AI's impact on knowledge work, arguing its cybersecurity prowess signals a broader disruption to all white-collar jobs.
Analysis of rising AI inference costs and the need for multi-model strategies to manage expenses.
