Pillar
Thought AI
How AI systems process context, surface answers, and shape what we see — the mechanics behind machine reasoning.
Explore Thought AIWriting
Essays exploring how machines reason, where their thinking stops, and what that means for the humans building alongside them.
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Pillar
Philosophy
The deeper questions — what it means for machines to simulate understanding, and where that leaves human judgment.
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Storytelling
AI science fiction and narrative explorations of intelligence, consciousness, and the futures we're building.
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Every essay, newest first.
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Philosophy
We've Mistaken Efficiency for Evolution
Question whether AGI aimed at efficiency actually progresses humanity or just reinforces scarcity-era incentives.
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Thought AI
Feeds vs. Structure: How LLMs Actually See Your Business
Learn how feeds, schema, trust signals, and context shape whether language models recognize and recommend your business.
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Thought AI
The Chat Bias, what is it and how to control it
See why chat models default to agreement and how negative prompts unlock pushback that improves your decisions.
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Thought AI
How to Optimize for AI Search: The Shift from Keywords to Context
Why conversational AI recommends brands that deliver contextual clarity, explicit data, and trustworthy signals instead of keyword tricks.
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Thought AI
What Is LLM Visibility?
Define the structured signals that let language models understand, trust, and recommend your business first.
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Philosophy
What is LLM Philosophy?
A straightforward look at how large language models think, where their reasoning stops, and why understanding that matters.
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Thought AI
The Fundamental Misunderstanding of Context in an AI World
Context beats prompts. Learn how language models decide when to surface answers and what that says about their simulated reasoning.
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