Question 1

Why do some people get 10x better results from the same AI tools?

Accepted Answer

Because the output you get depends as much on how you ask as on the model itself, an MIT study found that roughly half the quality gains from a better AI model came from users learning to communicate with it, not from the model. Power users treat AI like a smart new hire: they give it background, examples, and clear success criteria, then iterate on the answer instead of accepting the first draft. The good news is this is a learnable communication habit, not a technical skill.

Question 2

What are the 5 prompting techniques worth learning (and the ones that are outdated)?

Accepted Answer

The techniques that still pay off: give the AI relevant context and background, show it 1-3 examples of what good output looks like (few-shot), break big tasks into steps, tell it exactly what format you want, and iterate, decompose and refine instead of accepting draft one. Meanwhile, old tricks like elaborate role-play personas ('you are a world-class expert...'), threatening or tipping the model, and manually writing 'think step by step' matter far less with modern reasoning models. In short: clarity, examples, and context beat magic phrases.

Question 3

How do I give AI the right context about my business (projects, custom instructions, memory)?

Accepted Answer

Stop re-explaining your company in every chat: write a one-page brief about your business (what you sell, who your customers are, your tone, your goals) and put it where the AI can always see it. In ChatGPT that means custom instructions plus Projects with your key docs uploaded; in Claude, Projects with a knowledge base works the same way; memory then picks up preferences over time automatically. Once the context lives in the tool instead of in your prompts, every answer starts from 'knows my business' instead of 'generic advice'.

How founders use AI for Prompting