As we integrate AI into our workflows, I’m seeing a gap between users who get mediocre results and those who achieve stronger outcomes. The difference isn’t the tool—it’s the mindset.
I operate with three “AI Golden Rules” that reframe the human-AI relationship from a simple transaction to a working collaboration.
1. Treat AI Answers as Hypotheses Never take an AI’s output as gospel. Think of it as a highly capable but context-blind collaborator. It can generate a wonderfully articulate plan, draft a compelling email, or write flawless code that completely misses the strategic point. The output is a hypothesis to be tested, not a conclusion to be accepted. Your job is to be the senior strategist who validates, questions, and applies real-world wisdom.
Rule 2 Iterate Through a Feedback Loop
2. Exercise Human Agency Iteratively The most common mistake — what I call the AI vending machine mistake — is treating AI like a vending machine: one quality AI prompt in, one answer out, with no refinement in between. The best work comes from a feedback loop. Think of it as a conversation: you lead with a prompt, the AI responds, and you refine together., the AI follows with a response, and you refine the steps together. This iterative AI feedback loop sharpens the output with every cycle, aligns it closer to your vision, and ultimately ensures the final product is yours, augmented by the machine.
3. Provide Context, Context, Context The principle of “Output quality tends to reflect input quality — a vague prompt returns a generic answer.” has never been more relevant. If you give a vague prompt, you’ll get a generic, surface-level answer. Mastering AI briefing techniques — structuring your prompts with clear intent and detail — tends to produce far more specific, usable results. at briefing your AI.
- Background: What’s the history of this project?
- Goal: What specific outcome are we driving toward?
- Constraints: What are the non-negotiables, limitations, or style guides?
- Persona: Who is the AI supposed to be, and who is the audience?
The richer the context you provide, the more nuanced and valuable the output will be.
At their core, these rules are a reminder that the thinking applied to the tool determines whether you get ordinary outputs or transformative AI results.. for augmenting human intelligence, not replacing it.
