Chain of Thought: From Descartes to Machine Minds Hosted by Nathan Rigoni

In this episode we travel from the candle‑lit study of 17th‑century Descartes, who stripped away every belief to find the one certainty “I think, therefore I am,” to today’s glowing screens where large language models generate their own inner monologue. How does the age‑old philosophical quest for self‑knowledge map onto a model that writes “Let’s think step‑by‑step” and then follows its own reasoning chain? Can a machine’s recursive self‑talk be considered true thought, or is it merely sophisticated pattern matching? Join us as we untangle the threads of doubt, recursion, and chain‑of‑thought prompting to ask whether AI can ever achieve a genuine inner voice.

What you will learn

• The origins of chain‑of‑thought prompting and its connection to the REACT framework.
• How “system 1” fast intuition and “system 2” slow deliberation map onto LLM reasoning processes.
• The mechanics of recursive prompting: scratch‑pad tags, tool calls, observations, and how models iterate toward a final answer.
• Key philosophical questions about self‑awareness, consciousness, and the “I think, therefore I am” argument applied to artificial agents.
• Practical prompt‑engineering techniques to make LLMs reason more reliably in real‑world tasks.

Resources mentioned

• “Chain of Thought Prompting Improves Reasoning in Large Language Models,” 2022 (arXiv).
• “ReAct: Synergizing Reasoning and Acting in Language Models.”
• Daniel Kahneman, Thinking, Fast and Slow.
• Thomas Metzinger, Being No One.
• OpenAI function‑calling guide and examples of tool‑use in REACT‑style agents.

Why this episode matters
Understanding how LLMs construct and follow a chain of thought bridges the gap between classic epistemology and modern AI. Grasping these recursive reasoning patterns not only improves model performance on complex tasks, but also forces us to confront deeper questions about consciousness, agency, and what it truly means to “think.” As AI systems become partners in decision‑making, having a clear picture of their inner processes is essential for responsible deployment, ethical design, and informed public discourse.

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Keywords: chain of thought, recursion, REACT framework, large language models, prompt engineering, AI self‑awareness, consciousness, René Descartes, “I think therefore I am”, system 1 system 2, philosophical AI, artificial intelligence reasoning.