AI Could Have Done My Job in 1986
Four things to write down before you hand a job to an AI agent: what comes in, the rules, the action, and how you will check the work.
AI Primers
Introductory deep-dives into AI concepts
30 posts
There's No Such Thing as "AI Ethics"
A large language model only ever produces text. Treating that text as a novel ethical category, rather than as speech, is where the argument goes wrong.
Indistinguishable From Memory
LLMs are stateless. Every fact you give the model is re-fed as text each turn, then forgotten — the same weights answer a stranger's steak question a millisecond later.
John McCarthy's Mistake
The man who coined 'artificial intelligence' invented the most elegant language ever designed for it. It was the wrong tool — because it was the wrong category.
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.
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.
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.