Structured Prompt Engineering for Professionals
MOTIVE is the first peer-reviewed, model-agnostic framework that transforms prompt writing from an ad-hoc activity into a systematic, repeatable discipline.
Six Components
Each letter in MOTIVE represents a distinct prompt component that addresses a specific aspect of effective communication with AI systems.
Motivation
- › Why is this task being performed now?
- › What role should the AI assume?
Object
- › What is the concrete deliverable?
- › What format should the output take?
Tool
- › Which domain frameworks or methodologies should be applied?
- › What professional standards govern this work?
Instruction
- › What ordered steps should the AI follow?
- › Are there decision points or conditional branches?
Variables
- › What constraints bound the output (length, tone, format)?
- › What must be included or excluded?
Evaluation
- › What criteria determine whether the output is acceptable?
- › What scoring scale and thresholds apply?
Why MOTIVE?
Current prompt engineering lacks structure, repeatability, and evaluation criteria. MOTIVE addresses this gap with a six-component architecture validated through peer-reviewed research across multiple professional domains.
Three Tiers of Complexity
Not every task needs every component. MOTIVE's tiered architecture lets you scale prompt complexity to match the stakes of your work.
Five Prompt Archetypes
Common professional tasks map to recurring prompt patterns. MOTIVE identifies five baseline archetypes with domain-specific guidance.
Evidence-Based
MOTIVE is grounded in peer-reviewed research, validated through systematic evaluation across multiple domains, and continuously refined through practitioner feedback.