---
id: "concept-chain-of-reasoning"
type: "concept"
source_timestamps: ["§ Transforming Moats"]
tags: ["ai-capabilities", "reasoning", "llm-architecture"]
related: ["concept-recursive-algorithmic-development", "entity-openai-gpt-o1"]
definition: "An AI technique where models simulate multi-step reasoning through intermediate steps to reach a conclusion, vastly improving reliability over simple next-word prediction."
speakers: ["Toby E. Stuart"]
sources: ["futures"]
sourceVaultSlug: "hbr-seg-futures"
originDay: 2
articleStem: "hbr-nm-99-genai-end-incumbent-advantage"
sourceUrl: "https://hbr.org/2024/11/could-gen-ai-end-incumbent-firms-competitive-advantage"
sourceTitle: "Could Gen AI End Incumbent Firms’ Competitive Advantage?"
---
# Chain of Reasoning (Chain of Thought)

Simplistically, **chain of thought** (or chain of reasoning) refers to a technique where AI models generate responses by explicitly reasoning through intermediate steps before arriving at a final answer, rather than relying solely on next-word prediction. By simulating a multi-step reasoning process akin to human problem-solving, these models achieve vastly improved capability and reliability on complex cognitive tasks. The approach requires significantly greater compute, but it represents a fundamental shift from stochastic parroting to goal-directed, logical execution — previewed by models like [[entity-openai-gpt-o1|OpenAI's GPT-o1]]. It compounds with [[concept-recursive-algorithmic-development|recursive algorithmic development]] to push capability past the [[concept-agi-automation-threshold|task-automation threshold]].

**Enrichment / Validation.** Well supported by both academic work and model documentation: multi-step reasoning is a recognized capability that materially enhances performance on math, logic, and multi-step tasks (at greater compute cost). GPT-o1 specifically is not documented in the enrichment search set; treating it as a *reasoning-focused preview model* is reasonable but should be marked as extrapolation from the broader 2023–2024 trend toward explicit planning and step-by-step solutions.