Define AI Usage by Principles, Not Tips
The article discusses principles for using AI responsibly in teams, rather than focusing on tips and techniques. It outlines a 5-phase framework for AI collaboration and provides principles to preserve human judgment and responsibility.
Why it matters
These principles provide a framework for teams to use AI responsibly and preserve human judgment, rather than relying on fragile tips and techniques.
Key Points
- 1Tips and techniques are fragile and context-dependent, so the article proposes a framework of principles instead
- 2The 5 phases are: Request, Consult, Plan, Execute, and Verify - each with its own principles
- 3Overarching principles include protecting context, accepting uncertainty, and letting AI generate deliverables for human review
Details
The article argues that the current conversation around AI usage often focuses on techniques like 'the perfect prompt' or 'how to ask effectively', but these tips are fragile and can fail in real-world projects. Instead, the author outlines a framework of 5 distinct phases for AI collaboration: Request, Consult, Plan, Execute, and Verify. Each phase has its own principles to preserve human responsibility and judgment. For example, in the Request phase, the goal should be defined but not the solution. In the Consult phase, humans should explore multiple paths and introduce divergent perspectives. The Planning phase requires using language the human truly understands. Execution involves managing alignment, not just delegating. Verification checks if the original intent was satisfied. Overarching principles include protecting the context, accepting uncertainty, and letting AI generate deliverables for human review and editing. The author states these principles remain valid even as models and tools evolve, satisfying technical, design, and operational requirements simultaneously.
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