AI for Non-Technical Problem Solving Notes
This repository explores a simple idea:
AI can help more people approach problems with the habits of developers and researchers, even if they do not have those job titles.
That means more people can:
- break problems into steps
- test ideas quickly
- compare options
- work with information more effectively
- document findings
- improve outputs through iteration
Why this matters
The value of AI is not only in generating answers.
It is also in helping people think more clearly, investigate more systematically, and make better decisions.
For non-technical professionals, this can mean using AI to support:
- analysis
- synthesis
- decision-making
- structured problem-solving
- workflow improvement
What this repo is for
This repo is a place for notes, frameworks, and examples that make this idea practical.
It is intended to help show how AI can be useful for:
- business teams
- operators
- strategy and innovation professionals
- consultants and advisors
- non-technical users who want to work with more rigor
Core perspective
The old model was simple:
- researchers discover
- developers build
- business users consume
The new model is different:
- more people can investigate with the support of AI
- more people can prototype with the support of AI
- more people can move from passive users to active problem-solvers
Focus areas
This repo will explore topics such as:
- using AI to break down complex problems
- using AI to compare approaches and options
- using AI to turn messy information into usable structure
- using AI to support clearer workflows and decisions
- making AI more accessible to non-technical teams
Goal
The goal is to make AI more understandable, more practical, and more useful for people working on real problems in real-world settings.
