Chain-of-Thought
Chain-of-thought prompting transforms AI from answer machine to reasoning partner by explicitly modeling the problem-solving process within the prompt itself. Born from Google Research's 2022 breakthrough, this technique demonstrates that showing your work isn't just good practice—it fundamentally improves AI performance.
Rather than jumping to conclusions, chain-of-thought breaks complex problems into logical steps, creating a cognitive roadmap the AI can follow and extend. It's the difference between asking for directions and teaching someone to read a map.
Using chain-of-thought:
- Decompose complex queries into sequential reasoning steps
- Include intermediate calculations and logical transitions
- Make implicit thinking explicit through worked examples
The technique's elegance lies in its universality—any process that can be articulated can be enhanced. Organizations that master chain-of-thought prompting aren't just getting better outputs; they're documenting and scaling their collective intelligence.
Related terms:
Gravity Wells
Gravity wells describe economic dynamics where scarce resources flow disproportionately to entities with the greatest ability to pay and deploy, creating self-reinforcing concentrations of power. In the AI economy, they form around critical bottlenecks in compute, power, and talent, determining who captures resources and who scrambles for scraps.
Private-Token Sovereignty
Private-token sovereignty is the strategic imperative for organizations to maintain control over their unique data and institutional knowledge while amplifying it through AI rather than allowing external vendors to train on or control access to proprietary insights. This concept ensures sensitive organizational intelligence remains behind the firewall to prevent competitors from accessing your strategic advantages.
RLHF
Reinforcement Learning from Human Feedback (RLHF) trains a reward model on human preference comparisons and uses reinforcement learning to align language model outputs with those preferences, transforming them from autocomplete engines into useful assistants. First popularized by OpenAI’s InstructGPT in 2022, RLHF enables AI to follow nuanced instructions, refuse harmful content, and match organizational tone.