By assigning roles like a contrarian, an expansionist, and a first-principles thinker to a single LLM, founders can get multi-faceted feedback on critical questions. The model debates itself and provides a synthesized recommendation, revealing blind spots that a single-prompt approach would miss.

Create distinct AI agents representing key executives (e.g., CEO, CMO, CSO). By posing strategic questions to each, you can simulate how different departments might react, identify potential misalignments in priorities, and refine proposals before presenting them to real stakeholders.

Instead of relying on a single AI, use different models (e.g., ChatGPT for internal context, Claude for an objective view) for the same problem. This multi-model approach generates diverse perspectives and higher-quality strategic outputs.

Move beyond simple prompts by designing detailed interactions with specific AI personas, like a "critic" or a "big thinker." This allows teams to debate concepts back and forth, transforming AI from a task automator into a true thought partner that amplifies rigor.

Power dynamics often prevent leaders from receiving truly honest feedback. By implementing AI "coaching bots" in meetings, executives can get objective critiques of their performance. The AI acts as an "infinitely patient coach," providing valuable insights that colleagues might be hesitant to share directly.

Leverage AI to gain external perspectives without meetings. Prompt it to act as a specific persona—like a skeptical CEO, an enthusiastic user, or a New York Times reviewer—to critique your work. This reveals blind spots and strengthens your idea before sharing it.

Amol Avasare uses Claude to generate weekly feedback from the perspective of his manager. He instructs the AI to analyze his manager's public writing and internal communications to create a model of her priorities and style, then asks it to evaluate his week's work and provide feedback as if it were her.

Define different agents (e.g., Designer, Engineer, Executive) with unique instructions and perspectives, then task them with reviewing a document in parallel. This generates diverse, structured feedback that mimics a real-world team review, surfacing potential issues from multiple viewpoints simultaneously.

By creating AI agents with distinct roles (CEO, CFO, Sales), individuals can simulate an executive team meeting. These agents argue from their perspectives, stress-test ideas, and collaboratively develop a robust business strategy that a single person might miss. This moves beyond simple content generation to complex strategic planning.