Prompts

Before writing a line of code, have the AI interview you about your vision. 50 rapid-fire questions extract design decisions and judgment you didn't know you had — then the model can one-shot a working prototype roughly aligned with the picture in your head.

After you've built something, have the AI tear it apart — not as a code reviewer, but as a product thinker. What assumption is each screen testing? Where does the vision leak? High fidelity can mask the absence of shared understanding.

The prototype works and the concept is validated — now harden it for production. This prompt walks through the unglamorous work of turning a vibe-coded draft into code you'd actually ship.

When you're stuck on what to build or how to approach a problem, ask for five wildly different directions — not variations on a theme. Forces the model out of its clustering tendency and into genuinely divergent territory.

Operating principles for agentic code intelligence — measure twice, cut once.

Why code smells exist, grounded in cognitive science and information theory.

Structured 3-phase audit prompt for identifying and eliminating quality-lowering patterns.

Transform meeting transcriptions into publication-quality documentation with decisions, action items, and reasoning.

After plan mode, force the model to audit its own blind spots. It's silly that it works, but it does — asking the model to reflect on what it missed surfaces real gaps.

Push back on over-engineering by asking for the dumbest possible solution that still achieves the goal. Models tend toward complexity — this resets the bar.

Does capitalizing words for emphasis actually work, or is it placebo? Consensus leans toward: it works. CAPITALIZED words signal priority and weight to the model.