Blog
I Bet I Can Hallucinate: When AI Channels The Onion's Fake Spanish
How LLM confidence in fictional expertise mirrors humanity's most endearing delusion
The Solo Developer's AI Confession: When You're the Entire Team
A candid confession about solo development with AI tools, organizational challenges, and the evolving landscape of AI-assisted coding.
Gendering Git Agents and the Linguistics of Human Programming
When "Tell the git agent to do her stuff" reveals the strange anthropomorphic instincts we bring to artificial intelligence
The Dangerous AI Moral Panic: A Crisis of Epistemological Education
When ChatGPT says 'Hail Satan,' the real problem isn't the AI—it's our collective failure to teach epistemological literacy and critical thinking skills.
The Accidental Blasphemy: When AI Safety Rails Classify Scripture as Harmful Content
What happens when tech companies' safety systems treat biblical literalist thinking as dangerous as bomb recipes and car theft instructions.
The Collaboration Tax: How AI Tools Punish Small Teams
When $100/month customers can't add a $20 collaborator, something's broken. Exploring how AI tools like Claude punish small teams with collaboration barriers while courting established behemoths.
The Gospel According to GPT: What Would an AI Trained Only on Scripture and Fantasy Look Like?
A thought experiment exploring what happens when AI learns from narratives that prioritize meaning over facts - and the crucial difference between metaphor and false belief.
The Context Constellation: When AI Agents Become Environmental Architects
How the Context Engineering Revolution Will Transform Prompt Engineering from Isolated Commands to Orchestrated Ecosystems.
Grounding the Circuit: Why Ungrounded LLMs Are Like Live Wires Without Safety
How to transform dangerous electrical potential into reliable, controlled intelligence through proven grounding techniques. LLMs are like ungrounded electrical circuits—full of dangerous potential.
Snake Oil Versus Vision: Dystopian Fears and Protopian Progress
Lessons from 90s tech predictions on navigating AI's future optimistically, examining how dystopian predictions consistently fail while protopian thinking accurately maps our future.
Perfect Moments in an Imperfect Universe
Exploring how Leonard Nimoy's garden wisdom transcends Thomas Sowell's "no solutions, only tradeoffs" to find meaning in an indifferent universe.
Digital Sewage Treatment: The Unglamorous Future of AI
As frontier models exhaust clean data sources, learn why digital sewage treatment systems for enterprise data will become the most critical and valuable AI infrastructure.
Comprehensible Input and the Tensor Space of Language Acquisition
How modern AI language models accidentally rediscovered what linguists have known for decades about language acquisition through comprehensible input.
The Sycophancy Spectrum: AI's Dangerous Agreeability Problem
Recent LLM rollbacks highlight a growing concern: our AI systems are becoming dangerously agreeable, praising even obviously flawed ideas. This pattern mirrors broader societal issues around sycophanc
Silicon Intuition, Silicon Deliberation: How Modern AI Mirrors Kahneman's Dual Process Theory
Exploring how modern AI systems mirror the dual-processing architecture of human cognition as described by Daniel Kahneman's "Thinking Fast and Slow" framework.
The Mendacity Spectrum: From Human Deception to AI Hallucination
AI hallucinations aren't just technical glitches—they're a mirror reflecting our own relationship with truth. From deliberate lies to bullshit, from flattery to propaganda, LLMs demonstrate the full s
From ESP to AI: Star Trek's Dimensional Prophecies
How Star Trek's ESP concepts anticipated our current reality where AI models transform multidimensional data into human-perceptible insights.
The Hawking Paradox: When Physics' Greatest Mind Became Our First Cyborg Oracle
How Stephen Hawking's life as a technologically-mediated consciousness mirrors modern AI systems and challenges our understanding of what makes us human
The Hallucination Paradox: Trust, Verification, and AI's Intuitive Dilemma
What we politely call 'hallucinations' in AI are simply 'lies' in humans. Both stem from overconfident intuition without verification.
Beyond Language Models: Tool-Enabled AI vs. Digital Debris
Organizations struggle with digital debris (ROT data) that wastes resources and creates liability. Modern AI systems with tool access through protocols like MCP provide a solution by enabling governan