Reasoning, intent, and collaboration

Humans and AI

Follow human thinking into AI reasoning, task interpretation, tool use, and shared feedback, with recommendation as an applied case.

6 essays2 reading paths
Thinking, intent, and action4 essays

Connect human understanding, model processing, intent inference, and feedback.

  1. Human Thinking: Representation, Reasoning, and Action

    Thinking is more than inner speech or formal logic. It uses concepts, images, memory, emotion, bodily states, and external tools to build judgments, imagine possibilities, and guide action.

    14 min read
  2. AI Reasoning and Action: From Model Generation to Agent Execution

    A functional account of language-model reasoning, the limits of visible chains of thought, and the architecture that turns a model into an agent acting through tools.

    13 min read
  3. User Intent in AI: Inference Under Uncertainty

    What AI systems mean by user intent, how prompts support competing interpretations, and why confirmation improves action without revealing a private mental fact.

    11 min read
  4. The Human-AI Action Loop: Interpretation, Coordination, and Feedback

    People express partial intentions, AI systems construct revisable task models, and action plus feedback lets both sides correct goals, plans, and evidence.

    12 min read
Prediction and recommendation2 essays

Move from uncertain inference to a recommendation-system case pinned to a source version.

  1. Logic and Probability: Deduction, Uncertainty, and Evidence

    Logic constrains what follows from premises; probability represents uncertainty and evidential support. This essay separates truth, validity, credence, conditional probability, Bayes, causation, and AI generation.

    15 min read
  2. How X Ranks a Post: Predictions, Weights, and Filters

    A source-level guide to X's Phoenix ranking pipeline at commit b089ce64—and why published weights are not an exchange rate for likes, replies, or shares.

    9 min read

All essays