CORE COMPONENTS FOR DECISION-GRADE OUTPUTS
EXPERTISE (E)
Expertise prompts frame the AI’s role as an informed analyst, defining the professional context and expected standards. This creates a structured, expert dialogue—ensuring domain accuracy, meaningful business language, and responses that align with stakeholder needs.
CONTEXT (C)
Context gives the AI background, business constraints, regulatory scope and strategic aims—ensuring outputs are grounded in operational reality and support compliance from the outset.
HOW (H)
How provides a logical route to solve the problem—encouraging multi-step, transparent reasoning that decomposes tasks and imposes quality checks at every stage.
OUTPUT (O)
Output clarifies the required deliverable, ensuring consistency, traceable metadata, audit readiness and compliance documentation as standard.
WHAT YOU GET
PERFORMANCE GAINS
Greater accuracy, consistency, and regulatory assurance—while developing human skills that won’t become obsolete as AI evolves, just as spreadsheet and email skills remain essential.
RISK CONTROLS
These controls remain relevant as AI systems grow in autonomy, ensuring leaders maintain effective oversight and avoid risks from excessive automation.
BEST-PRACTICE DESIGN
Multi-model checks, domain-specific language and stepwise improvement underpin robust, audience-relevant results every time.