think-first

To surface initial thinking before AI responds, instruct the AI to prompt you for your preliminary reasoning on strategic decisions. This ensures your assumptions and context are evaluated first, allowing the AI to identify logical gaps and biases before providing feedback.

The best way to prompt AI for critique on architecture decisions is to use an on-demand challenge approach. Frame your request to ask for genuine pushback, which helps surface missing context and potential biases constructively rather than simply validating your initial plan.

Yes, you can use cognitive prompting to find logical gaps in project planning. By actively scanning your initial thinking for assumptions, missing context, and constraints, the AI highlights vulnerabilities in your strategy before you commit to a specific execution path.

Coach framing helps reframe challenges as development tasks by treating strategic obstacles as learning opportunities. This method shifts the focus from immediate problem-solving to long-term growth, guiding you to view critiques and gaps in your thinking as actionable steps for improvement.

You need to surface initial thinking for high-stakes questions when facing complex architecture decisions, project planning, or critique requests. This process prevents premature conclusions by ensuring assumptions and missing context are addressed before generating a strategic response.

A limitation of think-first prompting is that it requires you to actively provide your preliminary reasoning before the AI responds. If your initial input lacks sufficient detail or context, the AI's ability to find assumptions and provide effective strategic pushback is constrained.