Decision Architecture Guide

Overview

This agent component helps tailor the output of AI models to align with your unique cognitive process for making decisions. Instead of receiving a generic, one-size-fits-all analysis, this guide forces the AI to structure its recommendations based on how you naturally absorb and evaluate complex information.

By pre-defining your preferred inputs (e.g., needing trade-offs over single answers) and risk tolerance, you ensure that the resulting intelligence is immediately actionable and relevant to your thought process.

Capabilities

• Style Adaptation: Frames options according to specified decision styles (e.g., data-first vs. intuition-led).
• Input Scoping: Ensures all necessary context is provided, explicitly defining what is in scope and out of scope for the decision.
• Trade-off Presentation: Mandates the presentation of 2-3 distinct options with clear articulation of their respective trade-offs.
• Risk Profiling: Adjusts the depth of analysis based on perceived risk (e.g., slowing down for irreversible decisions).

Example Use Cases

When analyzing a new market entry strategy, instead of receiving a single 'Go/No-Go' report, you instruct the agent using this architecture. It will automatically generate three distinct pathways: one conservative path with low downside risk, one moderate path detailing necessary resource allocation, and one aggressive path outlining high potential returns but requiring significant upfront investment.

For technical reviews, it ensures that any proposed solution comes with quantified impact metrics (cost, timeline) rather than just conceptual benefits. This moves the output from 'what' to 'how much' and 'when'.