How to talk to AIs: Advanced Prompt Engineering

Few-shot prompting refers to presenting a model with a task or question along with a few examples of the desired output.

• Example 1: “Task: Convert temperatures from Celsius to Fahrenheit. Example: 0°C = 32°F, 100°C = 212°F. Convert 25°C to Fahrenheit.”
• Example 2: “Task: Summarize a news article. Example: ‘A new study shows that eating chocolate can improve memory. Researchers found that people who ate chocolate daily performed better on memory tests.’ Summary: ‘Eating chocolate can improve memory, according to a new study.’ Summarize this article: ‘A recent report states that global warming is causing sea levels to rise at an alarming rate. Coastal cities are at risk of flooding if action is not taken to reduce carbon emissions.’”

Pros:

• Can be used to train the model to perform specific tasks with minimal training data.
• Can be used to generate more accurate and consistent outputs.

Cons:

• May require fine-tuning or experimentation to find effective prompts and examples.
• May not be as flexible as zero-shot prompting in generating novel outputs.

Use-cases:

• Training the model to perform specific tasks such as classification, translation, or summarization.
• Improving the accuracy and consistency of the model’s outputs.

Pros:

• Enhances clarity and structure in responses by breaking down complex tasks into manageable steps.
• Improves problem-solving skills by guiding users through a logical sequence of thoughts.
• Facilitates deeper understanding and learning by explicitly showcasing reasoning processes.

Cons:

• May require more detailed and specific prompts to guide the model effectively.
• Can be time-consuming to construct and refine CoT prompts for optimal results.
• Might generate overly verbose responses, which could be less efficient for quick information retrieval.

Use-Cases:

• Ideal for educational purposes, such as teaching students how to approach complex problems step-by-step.
• Useful in research and analysis, where breaking down a topic into its constituent parts is necessary.
• Effective in programming and technical fields for debugging or explaining code logic.

Pros:

• Ensures coherence and consistency in multi-part or ongoing tasks.
• Reduces contradictions and errors in longer or more complex outputs.
• Enhances reliability of information in sequential or related queries.

Cons:

• May struggle with maintaining consistency in highly complex or nuanced topics.
• Requires careful prompt design to ensure previous responses are accurately incorporated.
• Potentially less flexible in adapting to new or contradictory information.

Use-Cases:

• Suitable for legal, medical, or technical writing where consistency in argument or explanation is crucial.
• Beneficial for creating comprehensive reports or documents that build on previous sections.
• Ideal for developing training materials or educational content that requires consistent messaging.

Pros:

• Broad applicability across various domains and subjects.
• Quick and efficient for straightforward information retrieval or basic question-answering.
• Requires minimal prompt engineering, making it accessible for general users.

Cons:

• May not delve deeply into specialized or niche topics.
• Less effective for complex problem-solving or creative tasks.
• Risk of generating generic or surface-level responses without specific guidance.

Use-Cases:

• Great for general trivia, basic educational queries, and common knowledge questions.
• Useful in journalism or content creation for quick fact-checking or background information.
• Appropriate for casual users seeking immediate answers to general questions.

Pros:

• Encourages interactive and engaging content creation.
• Enhances learning and retention through active participation and response.
• Ideal for creating dynamic scenarios, such as role-plays or simulations.

Cons:

• Requires careful crafting of scenarios and questions to be effective.
• May not be suitable for all types of content or subject matter.
• Relies on user engagement and participation for full effectiveness.

Use-Cases:

• Excellent for educational tools, such as interactive quizzes or study guides.
• Useful in training programs for role-playing scenarios or decision-making exercises.
• Appropriate for creating engaging content in marketing or entertainment.

Pros:

• Streamlines the process of prompt creation, saving time and effort.
• Generates a variety of prompts, offering diverse perspectives or approaches.
• Can enhance creativity and ideation in brainstorming or project planning.

Cons:

• May produce prompts that are not fully aligned with specific user needs or contexts.
• Relies on the quality of input data to generate relevant and effective prompts.
• Could limit learning opportunities in prompt crafting for users.

Use-Cases:

• Ideal for content creators needing inspiration or a starting point for their work.
• Useful in academic or research settings for generating thesis statements or research questions.
• Beneficial for business brainstorming sessions or strategy development.

Pros:

• Provides targeted guidance towards achieving specific output goals.
• Enhances the accuracy and relevance of responses for complex tasks.
• Facilitates a more controlled and directed interaction with the model.

Cons:

• Requires more effort and skill in prompt formulation.
• May not be as flexible in accommodating unexpected user inputs or directions.
• Could lead to overly narrow or constrained responses if not carefully managed.

Use-Cases:

• Suitable for specialized tasks in fields like law, medicine, or engineering where precision is key.
• Helpful in training environments where specific learning outcomes are desired.
• Effective for project management or planning tasks requiring detailed and directed outputs.

Pros:

• Guides the model towards specific areas of focus or perspectives.
• Enhances the relevance and specificity of responses to complex queries.
• Useful for exploring specific angles or dimensions of a broader topic.

Cons:

• May require significant expertise or knowledge to craft effective prompts.
• Risk of overlooking alternative perspectives or relevant information outside the directed focus.
• Could lead to biased or one-sided responses if not balanced with diverse stimuli.

Use-Cases:

• Ideal for in-depth research or analysis in academic or professional settings.
• Useful in creative fields for exploring specific themes or concepts in depth.
• Beneficial for strategic planning or decision-making processes focusing on particular aspects.

Pros:

• Integrates various forms of media for a richer, more engaging response.
• Enhances understanding by presenting information in diverse formats (text, images, audio).
• Ideal for creating comprehensive and multi-faceted educational or training materials.

Cons:

• More complex to design and implement effectively.
• Requires access to and familiarity with different media formats.
• Potentially more resource-intensive in terms of time and technology.

Use-Cases:

• Great for educational content that benefits from visual or auditory reinforcement.
• Useful in marketing or advertising to create impactful multimedia presentations.
• Appropriate for instructional design, especially in e-learning environments.

Pros:

• Facilitates the organization and visualization of complex information.
• Enhances understanding of relationships and connections within data.
• Ideal for tasks requiring analysis of networks, systems, or hierarchical structures.

Cons:

• Requires understanding of graph theory and related concepts.
• Potentially less intuitive for users unfamiliar with graphical representations.
• May be limited by the complexity of the graph that can be effectively processed.

Use-Cases:

• Suitable for data analysis in fields like sociology, economics, or biology.
• Helpful in project management for mapping tasks, dependencies, and workflows.
• Effective in educational settings for teaching concepts involving systems or networks.

BUSINESS SCHOOL PROMPT EXAMPLES

Zero-Shot Prompting: Business students could use zero-shot prompting to generate innovative business strategies or marketing plans. For example, a prompt could be “Develop a market entry strategy for a new tech startup in the European market” or “Create a marketing plan for an eco-friendly clothing line.”

Few-Shot Prompting: Business students could use few-shot prompting for specific business-related tasks, such as financial analysis or business plan development. For instance, a prompt could be “Task: Conduct a financial analysis. Example: Company financials, market data, analysis report. Conduct a financial analysis for XYZ Corporation” or “Task: Develop a business plan. Example: Business concept, market analysis, financial projections. Develop a business plan for a mobile health app startup.”

Chain of Thought (CoT) Prompting: Students could use CoT prompting to guide the model through a series of steps for more complex business outputs, like case study analyses or detailed project proposals. A prompt might be “Task: Analyze a business case study. Step 1: Summarize the business situation and challenges. Step 2: Identify key strategic options. Step 3: Recommend a course of action with justifications” or “Task: Write a project proposal for a new product launch. Step 1: Define the product concept and target market. Step 2: Outline the marketing and distribution strategy. Step 3: Project the financials and ROI.”

Self Consistency: Business students could use self consistency to generate coherent and consistent business outputs, such as multi-part business plans or dialogues between team members. For example, “Task: Develop a multi-part business plan for a startup. Previous response: ‘The startup will focus on sustainable fashion.’ Continue the plan, ensuring consistency in market approach and financial planning” or “Task: Write a dialogue between team members discussing a project. Member A: ‘Our market research shows a high demand in the 18-24 age group.’ Member B: ‘That's great. We should tailor our advertising to resonate with this demographic.’”

General Knowledge Prompting: Business students could use general knowledge prompting for accurate and informative outputs, like answering exam questions or explaining business concepts. For example, “Task: Answer an exam question on organizational behavior. Question: ‘What are the key factors influencing organizational culture?’” or “Task: Explain the concept of 'blue ocean strategy' in business.”

ReAct: Students could use ReAct for dynamic and engaging business outputs, such as interactive case studies or role-play scenarios. For instance, “Task: Create an interactive case study on business ethics. Information provided: ‘A company faces a dilemma between profit and environmental responsibility.’ Question: ‘What ethical considerations should the company evaluate?’” or “Task: Write a role-play scenario for a negotiation exercise. Scenario: ‘You are negotiating a merger between two competing firms.’”

Automatic Prompt Engineer: Business students could use an automatic prompt engineer for effective prompts for complex tasks or large-scale projects, like developing a comprehensive marketing campaign or preparing for a business pitch competition. For example, “Develop a pitch for a venture capital firm for your new fintech startup” or “Create a comprehensive risk management plan for an international expansion project.”

Active-Prompt: Business students could use active-prompting for accurate and consistent outputs that actively guide them in complex tasks like strategic planning or market analysis.

Directional Stimulus Prompting: Students could use directional stimulus prompting to guide them towards generating accurate and consistent business outputs for tasks like developing business models or crafting leadership strategies.

Multimodal CoT: Business students could use multimodal CoT prompting to incorporate multiple modalities (e.g., text, graphs, videos) in their CoT prompts when creating more engaging and interactive outputs like business presentations or investor pitches.

Graph Prompting: Business students could use graph prompting to generate structured and informative business outputs by using graph-based representations of knowledge for tasks like mapping industry trends or analyzing competitive landscapes.

LAW SCHOOL PROMPT EXAMPLES

1. Zero-Shot prompting: A law school student could use zero-shot prompting to generate creative arguments or legal theories. For example, a student could prompt the model with “Write a legal argument in favor of the defendant in a criminal case” or “Generate a legal theory on the intersection of contract law and environmental law.”
    
2. Few-Shot prompting: A law school student could use few-shot prompting to train the model to perform specific legal tasks, such as drafting contracts or writing case briefs. For example, a student could prompt the model with “Task: Write a case brief. Example: Case name, citation, facts, issue, holding, reasoning. Write a case brief for Marbury v. Madison” or “Task: Draft a contract. Example: Parties, recitals, terms and conditions, signatures. Draft a contract for the sale of goods.”
    
3. Chain of Thought (CoT) prompting: A law school student could use CoT prompting to guide the model through a series of steps to generate more complex legal outputs, such as legal memos or research papers. For example, a student could prompt the model with “Task: Write a legal memo. Step 1: Identify the issue and relevant facts. Step 2: Research and analyze the applicable law. Step 3: Apply the law to the facts and reach a conclusion” or “Task: Write a research paper on the First Amendment. Step 1: Provide an overview of the First Amendment and its history. Step 2: Discuss relevant case law and legal theories. Step 3: Analyze current issues and controversies related to the First Amendment.”
    
4. Self Consistency: A law school student could use self consistency to generate coherent and consistent legal outputs, such as multi-part legal arguments or dialogues between attorneys. For example, a student could prompt the model with “Task: Write a multi-part legal argument in favor of the plaintiff in a civil case. Previous response: ‘The defendant breached their duty of care by failing to maintain safe premises.’ Continue the argument, making sure to keep the facts and legal theories consistent” or “Task: Write a dialogue between two attorneys discussing a case. Attorney A: ‘I think we have a strong argument for summary judgment.’ Attorney B: ‘I agree, but we need to make sure our evidence is admissible.’ Attorney A: ‘Yes, we should file a motion in limine to exclude any hearsay evidence.’”
    
5. General Knowledge Prompting: A law school student could use general knowledge prompting to generate accurate and informative legal outputs, such as answers to exam questions or explanations of legal concepts. For example, a student could prompt the model with “Task: Answer an exam question on tort law. Question: ‘What are the elements of negligence?’” or “Task: Explain the concept of consideration in contract law.”
    
6. ReAct: A law school student could use ReAct to generate dynamic and engaging legal outputs, such as interactive study materials or mock trials. For example, a student could prompt the model with “Task: Create an interactive study guide on criminal law. Information provided: ‘The elements of murder are unlawful killing with malice aforethought.’ Question: ‘What is malice aforethought?’” or “Task: Write a mock trial script for a civil case. Plaintiff’s attorney: ‘Your honor, we are here today because the defendant breached their contract with my client.’ Defendant’s attorney: ‘Objection, your honor. The contract was unenforceable due to lack of consideration.’”
    
7. Automatic Prompt Engineer: A law school student could use an automatic prompt engineer to generate effective prompts for complex legal tasks or large-scale projects, such as writing a thesis or preparing for oral arguments. For example, an automatic prompt engineer could generate prompts like “Write an introduction for your thesis on international human rights law” or “Prepare an oral argument for an appellate court on the issue of qualified immunity.”
    
8. Active-Prompt: A law school student could use active-prompting to generate accurate and consistent legal outputs that actively guide them towards generating the desired output for complex tasks such as writing legal briefs or preparing for moot court competitions.
    
9. Directional Stimulus Prompting: A law school student could use directional stimulus prompting to provide directional stimuli that guide them towards generating accurate and consistent legal outputs for complex tasks such as writing research papers or preparing for negotiations.
    
10. Multimodal CoT: A law school student could use multimodal CoT prompting to incorporate multiple modalities (e.g., text, images, audio) into their Chain of Thought (CoT) prompts when generating more engaging and interactive legal outputs such as presentations or multimedia study materials.
     
11. Graph Prompting: A law school student could use graph prompting to generate structured and informative legal outputs by using graph-based representations of knowledge when writing research papers or preparing for exams.

HUMANITIES PROMPT EXAMPLES

Zero-Shot Prompting: Humanities students could use zero-shot prompting to generate insights or interpretations on various subjects. For example, a prompt could be “Analyze the themes of power and corruption in Shakespeare's 'Macbeth'” or “Discuss the impact of the Renaissance on modern European art.”

Few-Shot Prompting: Humanities students could use few-shot prompting for specific analytical tasks, such as literary analysis or historical event interpretation. For instance, a prompt could be “Task: Perform a literary analysis. Example: Poem, themes, stylistic devices. Analyze the use of symbolism in Robert Frost's 'The Road Not Taken'” or “Task: Interpret a historical event. Example: Event, historical context, significance. Interpret the significance of the Fall of the Berlin Wall in 1989.”

Chain of Thought (CoT) Prompting: Students could use CoT prompting to guide the model through a series of steps for more complex humanities outputs, like in-depth essays or cultural analyses. A prompt might be “Task: Write an essay on the influence of Greek mythology on modern literature. Step 1: Outline key Greek myths. Step 2: Identify their influences in modern literature. Step 3: Analyze the reasons for their enduring relevance” or “Task: Conduct a cultural analysis of the 1960s American Civil Rights Movement. Step 1: Describe the social and political context. Step 2: Discuss key figures and events. Step 3: Analyze its impact on contemporary society.”

Self Consistency: Humanities students could use self consistency to generate coherent and consistent outputs, such as multi-part analyses or dialogues on philosophical topics. For example, “Task: Develop a multi-part analysis of the concept of freedom in Jean-Paul Sartre's works. Previous response: ‘Sartre's existentialism posits that freedom is intrinsic to human existence.’ Continue the analysis, ensuring consistency in philosophical interpretation” or “Task: Write a dialogue between two philosophers discussing existentialism. Philosopher A: ‘Existentialism emphasizes individual freedom.’ Philosopher B: ‘True, but it also confronts the anxiety that comes with that freedom.’”

General Knowledge Prompting: Humanities students could use general knowledge prompting for accurate and informative outputs, like answering essay questions or explaining historical contexts. For example, “Task: Answer an essay question on World War II. Question: ‘What were the main causes of World War II and its global impact?’” or “Task: Explain the significance of the Harlem Renaissance in American history.”

ReAct: Students could use ReAct for dynamic and engaging humanities outputs, such as interactive study guides or historical scenario analyses. For instance, “Task: Create an interactive study guide on classical philosophy. Information provided: ‘Plato's allegory of the cave.’ Question: ‘What is the allegory's significance in understanding Plato's theory of forms?’” or “Task: Write a scenario analysis for a pivotal historical event. Scenario: ‘The signing of the Magna Carta in 1215.’”

Automatic Prompt Engineer: Humanities students could use an automatic prompt engineer for effective prompts for complex tasks or large-scale projects, like writing a comprehensive thesis on a historical period or preparing for a debate on ethical theories. For example, “Develop a thesis statement for a paper on the cultural impact of the French Revolution” or “Prepare arguments for a debate on the ethics of artificial intelligence.”

Active-Prompt: Humanities students could use active-prompting for accurate and consistent outputs that actively guide them in complex tasks like critical essay writing or philosophical argument development.

Directional Stimulus Prompting: Students could use directional stimulus prompting to guide them towards generating accurate and consistent humanities outputs for tasks like analyzing artistic movements or exploring cultural phenomena.

Multimodal CoT: Humanities students could use multimodal CoT prompting to incorporate multiple modalities (e.g., text, images, audio) in their CoT prompts when creating more engaging and interactive outputs like documentary analyses or multimedia art critiques.

Graph Prompting: Humanities students could use graph prompting to generate structured and informative outputs by using graph-based representations of knowledge for tasks like mapping literary themes or tracing historical timelines.