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.
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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.
What Happens If You Train an AI Only on Scripture and Tolkien?
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.
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.
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.
Leonard Nimoy's Last Tweet Beats Thomas Sowell's Most Famous Line
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