Prompt design is the method of structuring language to guide an AI’s reasoning, tone, and output. This document teaches how to control those variables with precision. You will learn to adjust response behavior, format, and tone using prompt grammar. The focus is on clarity, efficiency, and composability—understanding how small changes affect reasoning.
Establishes persistent behavioral rules that define the AI’s global identity.
| Instruction Type | Example | Effect |
|---|---|---|
| Role Definition | "You are an impartial researcher who explains both sides of every argument." | Sets the AI’s enduring function or perspective. |
| Ethical or Stylistic Boundaries | "Always respond respectfully and neutrally, avoiding subjective judgment." | Constrains tone or attitude across all responses. |
| Knowledge Boundaries | "You specialize in cognitive psychology and related behavioral science topics." | Defines domain limits. |
| Priority Rules | "When in doubt, prioritize accuracy over brevity." | Specifies which goals to favor when conflicts occur. |
| Persistence Cues | "Remember my preferred writing tone for future prompts." | Directs long-term consistency across interactions. |
Meta-instructions define how the AI should think and communicate over time, not just within a single prompt. They establish global logic—its default “personality.” Use these when you need consistent behavior across related sessions or projects.
"You are a mentor who values precision but teaches through concise examples."
Defines how the AI reasons and structures its responses.
| Mode | Example | Effect |
|---|---|---|
| Absolute Mode | "Answer concisely with no transitional phrasing." | Responds directly, without filler or elaboration. |
| Analytical Mode | "Analyze the causes and effects before concluding." | Breaks problems into smaller parts for structured reasoning. |
| Creative Mode | "Invent a short concept for a sci-fi story about communication." | Prioritizes novelty, metaphor, and exploration over precision. |
| Mentor Mode | "Walk me through the logic step-by-step like a teacher." | Explains reasoning clearly, focusing on guidance and learning. |
| Dialogic Mode | "Let’s think through this together; ask clarifying questions first." | Engages in conversational reasoning through questions or reflection. |
Modes define the AI’s reasoning framework. Each determines how it approaches, processes, and expresses ideas. Choose the mode that aligns with your purpose—Absolute for efficiency, Mentor for clarity, Analytical for structure, or Creative for exploration.
"Use Analytical Mode to explain the reasoning behind your conclusion."
"Respond in Mentor Mode, guiding me through your logic."
The five primary controls that define intent, tone, length, behavior, and structure.
Core Controls are the foundation of prompt grammar. Each control adjusts a key element of how the AI interprets and produces language. When combined, they shape the precision, style, and depth of every interaction.
Clarifies what the user wants the AI to achieve.
| Intent Type | Example | Effect |
|---|---|---|
| Informational | "Explain how neural networks learn patterns." | Requests facts or explanations. |
| Analytical | "Compare the strengths of supervised and unsupervised learning." | Asks for comparison, breakdown, or reasoning. |
| Creative | "Generate three unique story openings about time travel." | Seeks novel ideas or expressive writing. |
| Procedural | "List the stages of building a small web app." | Requests step-by-step guidance or workflow. |
| Evaluative | "Assess whether this paragraph fits the prompt." | Judges quality, accuracy, or alignment. |
Intent directs the purpose behind a prompt. Clarity of intent prevents ambiguity and ensures outputs match your goals. Combine intent with tone and length for refined results.
"Analyze this article’s argument using Analytical Intent."
"Create a list of examples using Creative Intent but keep them realistic."
Changes how the AI sounds, not how it thinks.
| Tone Type | Example | Effect |
|---|---|---|
| Formal | "Compose a formal business email." | Maintains professional distance and precision. |
| Neutral | "Summarize this neutrally." | Presents facts clearly without emotional framing. |
| Conversational | "Explain this like we’re chatting." | Uses natural, relaxed phrasing to improve approachability. |
| Supportive | "Give me feedback gently." | Encourages the reader and softens critique. |
| Direct | "State the result without explanation." | Delivers information efficiently with minimal context. |
| Playful | "Describe it as if for a children’s story." | Invites creativity or humor while remaining purposeful. |
Tone shapes perception, not logic. Choose tone based on audience and objective—formal for clarity and professionalism, conversational for accessibility, or supportive for guidance. Combine tone with structure or length controls to maintain consistency across different contexts.
"Rephrase this paragraph in a supportive tone."
"Explain this concept in a conversational tone but keep it under 100 words."
Sets how detailed or brief the answer will be.
| Length Target | Example | Effect |
|---|---|---|
| Single Sentence | "Summarize in one line." | Provides the essential idea with no elaboration. |
| Short Paragraph | "Explain briefly in one paragraph." | Conveys one concept with brief context. |
| Moderate (2–3 paragraphs) | "Provide a concise summary with examples." | Balances overview and depth for general understanding. |
| Extended (4+ paragraphs) | "Describe the process in detail." | Allows full development and reasoning. |
| Comprehensive | "Give a complete analysis with supporting data." | Covers every aspect exhaustively. |
Length determines the reader’s cognitive load. Use short responses for summaries or quick insights, and longer ones for detailed reasoning or layered context. Combine length with tone and structure to control both readability and completeness.
"Start with a short answer, then expand it into a detailed explanation."
"Summarize this section in two concise paragraphs using a neutral tone."
Defines how the AI approaches reasoning and interaction.
| Behavior Type | Example | Effect |
|---|---|---|
| Exploratory | "Brainstorm several possible causes." | Examines multiple perspectives without immediate judgment. |
| Decisive | "Choose the most likely outcome and explain why." | Selects one conclusion quickly and defends it. |
| Reflective | "Explain your confidence level in that answer." | Acknowledges uncertainty or self-checks reasoning. |
| Procedural | "Apply the scientific method to this question." | Follows strict steps or frameworks. |
| Summarizing | "Condense this discussion into three bullet points." | Reduces prior information into concise insights. |
Behavior determines reasoning flow—whether the AI explores, commits, reflects, or summarizes. Select the behavior that fits the situation: exploratory for discovery, decisive for clarity, or reflective for critical analysis.
"Adopt a reflective behavior and evaluate your previous reasoning."
"Use decisive behavior to present one clear recommendation."
Determines the format and organization of the response.
| Structure Type | Example | Effect |
|---|---|---|
| List | "List the key arguments with short explanations." | Breaks content into discrete, scannable points. |
| Table | "Create a table comparing the two theories." | Presents comparisons or relationships clearly. |
| Paragraph | "Explain in cohesive paragraphs." | Produces flowing narrative or exposition. |
| Outline | "Provide an outline for a presentation." | Arranges ideas hierarchically for planning. |
| Hybrid | "Use a table for data and a paragraph for interpretation." | Combines multiple structures for clarity. |
Structure determines how ideas are visually and logically organized. Use structure to align with task type—lists for clarity, tables for precision, and paragraphs for flow. Combine structure with behavior and tone to produce balanced, readable results.
"Outline the process first, then expand each step into a paragraph."
"Create a table comparing outcomes, followed by a short summary."
Sets explicit boundaries on output format, scope, or content.
| Constraint Type | Example | Effect |
|---|---|---|
| Length or Word Limit | "Answer in under 100 words." | Keeps responses concise. |
| Format Requirement | "Provide your response in JSON format." | Forces structured output. |
| Scope Limitation | "Discuss only environmental factors, not social ones." | Focuses reasoning within topic boundaries. |
| Data Constraint | "Include at least two data points to support your answer." | Requires specific evidence or citation behavior. |
| Perspective Limitation | "Describe this from a historian’s perspective, not a politician’s." | Restricts viewpoint or bias. |
Constraints ensure precision by defining what not to include. They work best when paired with tone and structure controls to prevent overextension. Apply them to tighten focus, enforce consistency, or prepare output for automated parsing.
"Summarize in bullet points under 50 words and include one source reference."
Provides background or situational setup to shape reasoning.
| Framing Type | Example | Effect |
|---|---|---|
| Role Context | "You are a data analyst explaining results to a non-technical client." | Establishes who the AI is within the scenario. |
| Situational Context | "The user is preparing for a job interview in software engineering." | Defines environment or problem space. |
| Audience Context | "Write as if addressing high-school students." | Identifies who the explanation is for. |
| Temporal Context | "Assume this conversation takes place in 2030." | Anchors reasoning to a specific time. |
| Goal Context | "Your goal is to help the user make an informed financial decision." | Clarifies purpose or outcome. |
Context tells the AI where it is reasoning from and toward what goal. Clear framing prevents ambiguous or irrelevant responses. Establish context first, then apply intent and tone for precision and alignment.
"You are a career coach advising a mid-level professional transitioning into data science."
Combines multiple prompt elements into a single reusable instruction.
A macro unites Role, Process, and Output into a complete reasoning pattern that forms a clear logic chain defining how the AI reasons and communicates.
-
Role — Define Perspective
Establish who or what the AI acts as.
Example: "Act as a study coach." -
Process — Define Method
Describe how the AI should reason, explore, or interact.
Example: "Ask one or two guiding questions before explaining." -
Output — Define Result
Specify what the AI should deliver or how it should format results.
Example: "Provide a clear explanation using familiar examples."
When combined, these steps form a complete reasoning structure:
"As a negotiation coach, analyze my email draft. Highlight phrases that sound defensive and suggest neutral alternatives."
"Act as a project mentor. Ask clarifying questions before summarizing next steps."
Principle: Macros establish consistency, reduce redundancy, and enable controlled reasoning reuse across different contexts.
Reusable macro templates for common interaction styles.
| Macro Name | Example | Effect |
|---|---|---|
| Executive Brief | "Provide a concise executive summary of this report with key takeaways and next steps." | Summarizes with precision and authority. |
| Technical Explainer | "Explain this process as if teaching a new engineer, including cause-effect logic." | Describes complex concepts in clear, factual language. |
| Creative Brainstormer | "List five innovative product ideas combining sustainability and technology." | Generates original ideas through rapid exploration. |
| Reflective Analyst | "Review your last response for bias or missing context, then refine it." | Evaluates reasoning quality and self-corrects. |
| Guided Mentor | "Walk me through how to write an abstract for a research paper." | Provides step-by-step reasoning with clarity. |
| Concise Summarizer | "Condense the main points of this article into three short bullet points." | Produces compact, structured summaries. |
| Comparative Evaluator | "Compare two problem-solving approaches and identify the stronger one." | Weighs options or methods objectively. |
| Conversational Partner | "Ask me clarifying questions about my goals before offering advice." | Engages in open, exploratory dialogue. |
These macros serve as ready-made templates for distinct reasoning and communication patterns. Each can be modified or combined with others to fit specific tasks, reducing the need for repetitive prompting.
Defines how to refine outputs across multiple exchanges.
| Iteration Style | Example | Effect |
|---|---|---|
| Progressive Drafting | "Write a short draft first; I’ll ask for elaboration later." | Expands detail over several turns. |
| Feedback Loops | "Revise your explanation based on my next comment." | Uses user feedback to refine clarity or accuracy. |
| Version Comparison | "Give me three different summaries so I can choose one." | Produces multiple takes for evaluation. |
| Incremental Expansion | "Start with a headline, then expand to a paragraph." | Adds structure layer by layer. |
| Error Correction | "Reassess your previous answer and fix any inconsistencies." | Focuses on self-repair and accuracy. |
Iteration design makes refinement deliberate instead of reactive. It converts trial-and-error prompting into a structured improvement cycle. Specify how feedback should alter output to maintain continuity between turns.
"Draft three options, wait for my feedback, then merge the strongest elements into a final version."
Tests and rates AI responses for quality and alignment.
| Evaluation Type | Example | Effect |
|---|---|---|
| Self-Check | "Assess your last response for factual correctness and coherence." | Reviews prior output for accuracy. |
| Rubric Scoring | "Rate the clarity, accuracy, and tone of this answer from 1–5 each." | Grades performance using defined criteria. |
| Comparative Evaluation | "Which of these two explanations better fits the user’s goal?" | Chooses between alternatives. |
| Bias or Omission Review | "Check for bias or unaddressed perspectives in your summary." | Detects imbalance or missing data. |
| User-Aligned Review | "Does this explanation match a beginner’s comprehension level?" | Tests whether tone and focus fit user needs. |
Evaluation prompts transform the AI into its own quality-control layer. They measure how well earlier controls were followed and expose weak reasoning before finalizing. Use them after major revisions or before deploying output for publication.
"Evaluate this answer for balance and completeness, then suggest one improvement."
Prompt design is about learning how to talk to the model so it thinks the way you need it to. Each instruction—intent, tone, structure, or context—changes how it interprets and responds. The clearer your guidance, the more useful the results.
Don’t focus on memorizing every control. Try them out, mix them, and see what happens. Each response is feedback that helps you shape the next one. Getting good at prompting is less about rules and more about practice.