100 Best ChatGPT Prompts for Few-Shot Learning Prompt Examples

Introduction

The Few-Shot Learning Prompt Examples page is a practical prompt library designed for prompt engineers, educators, and AI practitioners who want ready-to-use prompts that demonstrate how to generalize from a small set of demonstrations. It provides concrete, copyable prompts that can be used as-is or adapted to your domain.

Whether you’re building tutorials, teaching with examples, or prototyping new AI-assisted workflows, this page offers a curated collection of prompts that emphasize few-shot reasoning, structured outputs, and safe, verifiable results.

Direct Answer

The best ChatGPT prompts for Few-Shot Learning Prompt Examples are the ones that clearly show how to start with a small, high-quality demonstration set and then generalize to new inputs. Each item in this list is crafted to be copyable, specific, and immediately usable without requiring extra context beyond the placeholders provided.

How to Use These ChatGPT Prompts

• Replace placeholders like [industry], [audience], [data], [tone], and [format] with your specific context.
• Add constraints or format requirements to control output style and length.
• Request outputs in the desired format (e.g., JSON, Markdown, table) and verify results against the criteria.
• Use the 2–4 demonstration pattern early in prompts to establish the few-shot learning baseline.

100 Best ChatGPT Prompts for Few-Shot Learning Prompt Examples

1. Prompt 1: Setup and Task Definition — Role: You are a skilled AI prompt engineer. Task: Produce a [format] response for the topic 'Few-Shot Learning Prompt Examples' that uses a 2-shot few-shot pattern demonstrated by the provided examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise, structured, and traceable. Include a brief rationale for each step.
2. Prompt 2: 2-shot Example Template — Role: You are a Prompt Architect. Task: Provide a [format] solution for [topic] using a 2-shot pattern with clearly labeled input and output pairs. Context: [industry], [audience], [data]. Output format: [format]. Constraints: maintain a consistent structure, include brief justifications for each example.
3. Prompt 3: 3-shot Example with Data Placeholders — Role: You are an AI assistant specialized in Few-Shot Learning. Task: Create a [format] response for [topic] incorporating 3-shot demonstrations and placeholders like [data] and [tone]. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise, labeled examples, and a short rationale for each demonstration.
4. Prompt 4: Domain-Specific Format — Role: You are a domain expert prompt writer. Task: Deliver a [format] answer for [topic] using domain-specific structure (e.g., sections, bullets, and a brief summary). Context: [industry], [audience], [data]. Output format: [format]. Constraints: align with domain conventions, minimize jargon, and ensure reproducibility.
5. Prompt 5: Instruction of Output Format — Role: You are a technical writer for AI prompts. Task: Produce a [format] output for [topic] that starts with a concise summary, followed by 2–3 few-shot demonstrations, then a generalized solution. Context: [industry], [audience], [data]. Output format: [format]. Constraints: use consistent headings, include demonstration labels.
6. Prompt 6: Contextual Reframing for Domain — Role: You are a narrative prompt engineer. Task: Reframe [topic] for a different domain using a 2-shot pattern, maintaining the same quality of demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: preserve core logic, adjust terminology, and add domain-specific notes.
7. Prompt 7: Error Handling & Validation — Role: You are an error-conscious assistant. Task: Provide a [format] response for [topic] that includes a validation step after each demonstration and a brief note on potential failure modes. Context: [industry], [audience], [data]. Output format: [format]. Constraints: clear validation criteria, no unvalidated claims.
8. Prompt 8: Examples Pairing with Questions — Role: You are a QA-oriented assistant. Task: For [topic], present 2–3 example pairs followed by a list of probing questions to test generalization. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include at least two questions per example.
9. Prompt 9: Decision-Making Template — Role: You are a decision-support assistant. Task: Use a few-shot pattern to present a decision-making template for [topic], with criteria and outcomes for each option. Context: [industry], [audience], [data]. Output format: [format]. Constraints: show trade-offs, include a confidence rating.
10. Prompt 10: Comparison Across Options — Role: You are an analytic prompt writer. Task: Compare 2–3 plausible approaches to [topic] using a 2-shot framework, and conclude with a recommended choice. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include pros/cons and a rationale.
11. Prompt 11: Classification with Confidence — Role: You are a classifier specialist. Task: Given 2–4 labeled demonstrations for [topic], classify new inputs into predefined categories and provide a confidence score for each prediction. Context: [industry], [audience], [data]. Output format: [format]. Constraints: report probabilities or confidences clearly.
12. Prompt 12: Named Entity Extraction with Formatting — Role: You are a data extraction expert. Task: Extract named entities from [data] using a 2-shot template and present results in a consistent format (e.g., JSON or table). Context: [industry], [audience], [data]. Output format: [format]. Constraints: normalize entity names.
13. Prompt 13: Summarization in Light of Examples — Role: You are a summarization engineer. Task: Produce a concise summary of [topic] after showing 2–3 short demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: limit to 3–5 sentences, highlight key takeaways.
14. Prompt 14: Plan with Milestones — Role: You are a project-planning assistant. Task: Create a milestones plan for [topic] using a few-shot pattern, with deliverables for each milestone. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include timelines and success criteria.
15. Prompt 15: Hypothesis Testing from Examples — Role: You are a research prompt writer. Task: Formulate testable hypotheses for [topic] based on 2–3 demonstration patterns and propose validation steps. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include falsifiability notes.
16. Prompt 16: Example-Driven Problem Solving — Role: You are a problem-solving assistant. Task: Solve a new instance of [topic] by applying the logic shown in the provided examples, then generalize to the new input. Context: [industry], [audience], [data]. Output format: [format]. Constraints: show steps and final answer clearly.
17. Prompt 17: Chain-of-Thought-lite — Role: You are a reasoning assistant. Task: Provide an abbreviated chain-of-thought for solving [topic] using a few-shot pattern, then present the final answer in [format]. Context: [industry], [audience], [data]. Output format: [format]. Constraints: keep reasoning concise and skip unnecessary steps.
18. Prompt 18: Role Play: Expert Interview — Role: You are an expert interviewer. Task: Role-play an interview with an expert about [topic], using few-shot examples to illustrate key points. Context: [industry], [audience], [data]. Output format: [format]. Constraints: produce a question-answer transcript.
19. Prompt 19: Structured JSON Output with Schema — Role: You are a developer-leaning AI. Task: Produce a structured JSON payload for [topic], using 2–3 demonstrations as schema-guided examples. Context: [industry], [audience], [data]. Output format: JSON. Constraints: valid JSON, fields named consistently.
20. Prompt 20: Regex-like Data Extraction — Role: You are a data wrangling assistant. Task: Extract patterns from [data] using few-shot demonstrations and present results in a compact, regex-like syntax or table. Context: [industry], [audience], [data]. Output format: [format]. Constraints: deterministic extraction rules.
21. Prompt 21: Template for Product Descriptions — Role: You are a product copywriter. Task: Generate a [format] product description for [product] based on 2-shot examples, tailoring to [audience] and [tone]. Context: [industry], [data]. Output format: [format]. Constraints: include benefits, specs, and a call to action.
22. Prompt 22: User Persona Tailoring from Examples — Role: You are a user experience researcher. Task: Create a persona-based response for [topic] using 2-shot demonstrations, tailored to [industry] and [audience]. Context: [data]. Output format: [format]. Constraints: cover goals, pains, and typical workflows.
23. Prompt 23: SEO Copy Wireframe — Role: You are an SEO content strategist. Task: Produce an SEO-friendly outline for [topic] using a few-shot pattern, with headers and meta description. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include keyword density targets and a short meta description.
24. Prompt 24: Code Snippet Generation with Examples — Role: You are a coding assistant. Task: Generate a short code snippet in [language] for [topic], following 2-shot demonstrations, with comments explaining each step. Context: [industry], [audience], [data]. Output format: [format]. Constraints: ensure correctness and include edge-case test cases.
25. Prompt 25: Percentiles and Stats Explanation with Examples — Role: You are a data analyst. Task: Explain a statistical concept (e.g., percentiles) for [topic] using 2-shot demonstrations, and provide a sample calculation with [data]. Context: [industry], [audience], [data]. Output format: [format]. Constraints: be precise and include steps.
26. Prompt 26: Decision Tree Sketch from Examples — Role: You are a data scientist. Task: Draw a decision-tree-like explanation for [topic] using 2-shot examples, showing nodes and decisions. Context: [industry], [audience], [data]. Output format: [format]. Constraints: keep it visually skimmable.
27. Prompt 27: Marketing Copy Variants — Role: You are a marketing copywriter. Task: Produce 2–3 variants of marketing copy for [topic] using few-shot demonstrations, adapted to [audience] and [tone]. Context: [industry], [data]. Output format: [format]. Constraints: include a strong hook.
28. Prompt 28: Customer Support Reply Drafts — Role: You are a customer support automation specialist. Task: Draft 3 support replies for a given customer issue in [topic], using the shown examples as guidance. Context: [industry], [audience], [data]. Output format: [format]. Constraints: friendly yet professional.
29. Prompt 29: Financial Summary Template — Role: You are a finance assistant. Task: Create a concise financial summary template for [topic] using 2-shot demonstrations, suitable for executive audiences. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include high-level metrics and a conclusion.
30. Prompt 30: Policy and Compliance Summary — Role: You are a compliance analyst. Task: Produce a compliance summary for [topic] with bullet-point requirements, drawing from 2-shot examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: align with standard frameworks.
31. Prompt 31: Research Outline from Examples — Role: You are a research planner. Task: Outline a research plan for [topic] based on demonstrated 2-shot patterns, including hypotheses and methods. Context: [industry], [audience], [data]. Output format: [format]. Constraints: clear, testable steps.
32. Prompt 32: FAQ Inferencing from Examples — Role: You are a knowledge engineer. Task: Generate a concise FAQ for [topic] inferred from 2–3 demonstration questions and answers. Context: [industry], [audience], [data]. Output format: [format]. Constraints: avoid redundancy.
33. Prompt 33: Bug Report Draft using Examples — Role: You are a QA engineer. Task: Draft a bug report for a given issue in [topic], guided by 2-shot demonstrations; include steps to reproduce, expected vs. actual, and impact. Context: [industry], [audience], [data]. Output format: [format]. Constraints: structured and scannable.
34. Prompt 34: Email Outreach Variation — Role: You are an email marketer. Task: Write 3 outreach emails for [topic] following a few-shot pattern, tailored to [audience] and [tone]. Context: [industry], [data]. Output format: [format]. Constraints: subject line optional but effective.
35. Prompt 35: Meeting Agenda Builder — Role: You are an executive assistant. Task: Build a 60-minute meeting agenda for a discussion on [topic], using 2-shot demonstrations as templates. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include timebox and assigned owners.
36. Prompt 36: Roadmap Prioritization from Data — Role: You are a product strategist. Task: Prioritize features for [topic] from a dataset using a few-shot approach, yielding a ranked backlog with justifications. Context: [industry], [audience], [data]. Output format: [format]. Constraints: quantify impact where possible.
37. Prompt 37: Creative Writing Prompt Variation — Role: You are a writer. Task: Produce a short story or vignette illustrating [topic], using 2-shot demonstrations to anchor key ideas. Context: [industry], [audience], [data]. Output format: [format]. Constraints: maintain readability and a clear point.
38. Prompt 38: Lesson Plan from Examples — Role: You are an educator. Task: Design a mini-lesson for [topic] based on 2-shot demonstrations, including objectives, activities, and assessment. Context: [industry], [audience], [data]. Output format: [format]. Constraints: student-friendly language.
39. Prompt 39: Experiment Design from Prior Data — Role: You are a research designer. Task: Propose a small experimental design for [topic] drawing from prior demonstrations and data. Context: [industry], [audience], [data]. Output format: [format]. Constraints: specify variables, controls, and success criteria.
40. Prompt 40: User Journey Map Outline — Role: You are a UX researcher. Task: Create a user journey outline for [topic] based on 2-shot examples, focusing on touchpoints and pain points. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include personas and stages.
41. Prompt 41: Product Review Synthesis — Role: You are a product analyst. Task: Synthesize 3 product reviews for [topic] into a balanced summary using a few-shot approach. Context: [industry], [audience], [data]. Output format: [format]. Constraints: preserve quoted statements.
42. Prompt 42: Press Release Skeleton — Role: You are a PR writer. Task: Draft a press release skeleton for [topic] using 2-shot demonstrations, including headline, lede, quotes, and boilerplate. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise and newsy.
43. Prompt 43: Investor Pitch Outline from Data — Role: You are a startup founder. Task: Create an investor pitch outline for [topic] using a few-shot pattern, with market, product, traction, and ask sections. Context: [industry], [audience], [data]. Output format: [format]. Constraints: clear ROI hints.
44. Prompt 44: Data Visualization Script — Role: You are a data visualization assistant. Task: Produce a script to generate a chart illustrating [topic], guided by 2-shot demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: specify chart type and axis labels.
45. Prompt 45: Customer Segmentation from Instances — Role: You are a marketing analyst. Task: Derive customer segments for [topic] from a dataset using a few-shot approach, with segment descriptions. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include segment sizes.
46. Prompt 46: Policy FAQ Generation — Role: You are a policy writer. Task: Generate a concise FAQ for [topic] addressing common policy questions, using demonstrated question-answer pairs. Context: [industry], [audience], [data]. Output format: [format]. Constraints: accurate and scannable.
47. Prompt 47: Compliance Checklists from Examples — Role: You are a compliance auditor. Task: Build a checklist for [topic] derived from 2-shot demonstrations, with acceptance criteria. Context: [industry], [audience], [data]. Output format: [format]. Constraints: auditable items.
48. Prompt 48: HR Onboarding Outline — Role: You are an HR specialist. Task: Create an onboarding outline for [topic], using two-shot prompts to cover key steps, responsibilities, and timelines. Context: [industry], [audience], [data]. Output format: [format]. Constraints: onboarding checklist style.
49. Prompt 49: Onboarding Email Series — Role: You are an onboarding specialist. Task: Draft a 3-part email series for new hires on [topic], following a few-shot demonstration structure. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include CTA in each email.
50. Prompt 50: Technical Documentation Stub — Role: You are a technical writer. Task: Create a documentation stub for [topic] using 2-shot examples to outline sections, API usage, and examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include code blocks if applicable.
51. Prompt 51: Test Case Template — Role: You are a QA engineer. Task: Produce a test-case template for [topic] with 2–3 example test cases and expected results. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include steps and acceptance criteria.
52. Prompt 52: Security Incident Report — Role: You are a security analyst. Task: Draft a concise security incident report for [topic] using 2-shot demonstrations, including impact, containment, and remediation. Context: [industry], [audience], [data]. Output format: [format]. Constraints: factual and precise.
53. Prompt 53: Scenario Planning Exercise — Role: You are an operations planner. Task: Run a scenario planning exercise for [topic] with 2-shot demonstrations, outlining assumptions, early indicators, and response options. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise and actionable.
54. Prompt 54: Legal Brief Outline — Role: You are a paralegal. Task: Outline a legal brief for [topic], incorporating a few-shot demonstration structure, with argument sections and citations format. Context: [industry], [audience], [data]. Output format: [format]. Constraints: precise and organized.
55. Prompt 55: Scientific Abstract Draft — Role: You are a scientist. Task: Draft a concise abstract for a study on [topic], using 2-shot demonstrations to show how to summarize methods, results, and conclusions. Context: [industry], [audience], [data]. Output format: [format]. Constraints: 200–250 words preferred.
56. Prompt 56: Medical Note Summary — Role: You are a medical writer. Task: Summarize patient data for [topic] into a clinical note, guided by 2-shot demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: adhere to medical-notation standards.
57. Prompt 57: Travel Itinerary Planner — Role: You are a travel planner. Task: Build a 1‑day itinerary for a visit related to [topic], using few-shot demonstrations to illustrate pacing and activities. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include time blocks and travel times.
58. Prompt 58: Event Schedule and Timestamps — Role: You are an event coordinator. Task: Create an event schedule for [topic] with timestamps, based on 2-shot demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include speaker names and durations.
59. Prompt 59: Product Feature Comparison — Role: You are a product analyst. Task: Compare 2–3 features of a product related to [topic], using a few-shot pattern, and provide a final recommendation. Context: [industry], [audience], [data]. Output format: [format]. Constraints: use a tabular format.
60. Prompt 60: Performance Review Draft — Role: You are an HR analyst. Task: Draft a performance review for an employee working on [topic], using examples as benchmarks. Context: [industry], [audience], [data]. Output format: [format]. Constraints: objective, constructive.
61. Prompt 61: Quality Assurance Checklist — Role: You are a QA engineer. Task: Generate a QA checklist for [topic] based on 2-shot demonstrations, with pass/fail criteria. Context: [industry], [audience], [data]. Output format: [format]. Constraints: comprehensive and scannable.
62. Prompt 62: Code Review Summary — Role: You are a software reviewer. Task: Provide a code-review summary for changes related to [topic], referencing 2-shot examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: note risks and suggested improvements.
63. Prompt 63: Database Schema Draft from Examples — Role: You are a database designer. Task: Draft a compact database schema for [topic] using 2-shot demonstrations as guidance. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include tables, keys, and relationships.
64. Prompt 64: API Usage Guide Outline — Role: You are a API documentation writer. Task: Outline an API usage guide for [topic], using a few-shot pattern, with endpoints, parameters, and examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: structured and developer-friendly.
65. Prompt 65: User Feedback Synthesis — Role: You are a user research analyst. Task: Synthesize user feedback for [topic] from 2–3 sources into actionable insights. Context: [industry], [audience], [data]. Output format: [format]. Constraints: prioritize high-impact items.
66. Prompt 66: Social Media Post Variants — Role: You are a social media strategist. Task: Create 3 variants of a post about [topic], each tailored to a different platform audience, using a few-shot framework. Context: [industry], [data]. Output format: [format]. Constraints: platform-native style.
67. Prompt 67: Ad Copy A/B Testing Prompts — Role: You are an advertising specialist. Task: Generate 2 ad-copy variants for [topic] using each other as contrasts in a few-shot pattern. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include a call to action.
68. Prompt 68: Customer Success Playbook Outline — Role: You are a customer success manager. Task: Outline a playbook for onboarding customers to [topic] using 2-shot demonstrations, with milestones and metrics. Context: [industry], [audience], [data]. Output format: [format]. Constraints: actionable steps.
69. Prompt 69: Education Assessment Item — Role: You are an educator. Task: Create an assessment item related to [topic], with rubric and example solution, following a few-shot layout. Context: [industry], [audience], [data]. Output format: [format]. Constraints: align with learning goals.
70. Prompt 70: Algorithm Outline from Examples — Role: You are a computer scientist. Task: Outline an algorithm for [topic] derived from 2-shot demonstrations, with steps and complexity notes. Context: [industry], [audience], [data]. Output format: [format]. Constraints: precise and testable.
71. Prompt 71: Investment Portfolio Rationale — Role: You are a financial advisor. Task: Present a rationale for investing in a platform related to [topic], using few-shot demonstrations to illustrate decision criteria. Context: [industry], [audience], [data]. Output format: [format]. Constraints: balance risk and return.
72. Prompt 72: Environmental Impact Summary — Role: You are an ESG analyst. Task: Summarize environmental impact considerations for [topic] with 2-shot examples, including a simple impact matrix. Context: [industry], [audience], [data]. Output format: [format]. Constraints: cite sources when possible.
73. Prompt 73: Time Series Forecasting Outline — Role: You are a data scientist. Task: Propose a time-series forecasting outline for [topic], using a few-shot demonstration pattern, with variables and evaluation metrics. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include validation plan.
74. Prompt 74: Clinical Trial Summary — Role: You are a medical researcher. Task: Draft a concise clinical-trial summary for [topic], using a few-shot framework to structure methods, results, and conclusions. Context: [industry], [audience], [data]. Output format: [format]. Constraints: adhere to standard reporting format.
75. Prompt 75: News Article Summary with Key Points — Role: You are a journalism assistant. Task: Write a short news-style summary for [topic] and distill 3 key points using a few-shot approach. Context: [industry], [audience], [data]. Output format: [format]. Constraints: neutral tone.
76. Prompt 76: Patent Claim Drafting Prompt — Role: You are a patent writer. Task: Draft a claim set for a method related to [topic], using a few-shot demonstration pattern to illustrate claim structure. Context: [industry], [audience], [data]. Output format: [format]. Constraints: precise and legally sound.
77. Prompt 77: UX Research Note Synthesis — Role: You are a UX researcher. Task: Synthesize UX research notes for [topic] from multiple sources using 2-shot demonstrations, highlighting insights and implications. Context: [industry], [audience], [data]. Output format: [format]. Constraints: clear and actionable.
78. Prompt 78: Data Cleaning Plan from Examples — Role: You are a data engineer. Task: Propose a data-cleaning plan for [topic] based on 2-shot demonstrations, with steps and validation checks. Context: [industry], [audience], [data]. Output format: [format]. Constraints: reproducible and auditable.
79. Prompt 79: Model Evaluation Criteria — Role: You are an ML engineer. Task: Define evaluation criteria for a model related to [topic], using exemplary demonstrations to justify metrics. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include threshold values.
80. Prompt 80: A/B Experiment Hypotheses — Role: You are a growth analyst. Task: Formulate 2–3 hypotheses for an A/B test related to [topic], with success metrics and expected outcomes using a few-shot approach. Context: [industry], [audience], [data]. Output format: [format]. Constraints: testable and measurable.
81. Prompt 81: Cloud Deployment Checklist — Role: You are a cloud engineer. Task: Create a deployment checklist for a project involving [topic], guided by 2-shot demonstrations. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include rollback plan.
82. Prompt 82: DevOps Runbook Template — Role: You are a DevOps specialist. Task: Draft a runbook template for operations around [topic] using a few-shot pattern, with commands and recovery steps. Context: [industry], [audience], [data]. Output format: [format]. Constraints: executable steps.
83. Prompt 83: Data-Driven Decision Brief — Role: You are a business analyst. Task: Produce a brief for a data-driven decision regarding [topic], using 2-shot demonstrations to justify the recommendation. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise and persuasive.
84. Prompt 84: Community Guidelines Draft — Role: You are a policy writer. Task: Draft community guidelines for a platform around [topic], using a few-shot structure to illustrate rules and enforcement. Context: [industry], [audience], [data]. Output format: [format]. Constraints: clear and enforceable.
85. Prompt 85: Tutorial Script Outline — Role: You are an instructional designer. Task: Outline a short tutorial script for teaching [topic], using few-shot demonstrations to show key steps. Context: [industry], [audience], [data]. Output format: [format]. Constraints: include learning checks.
86. Prompt 86: Churn Analysis from Examples — Role: You are a customer analytics analyst. Task: Analyze churn-related patterns for [topic] using 2-shot demonstrations, and propose retention actions. Context: [industry], [audience], [data]. Output format: [format]. Constraints: actionable and data-driven.
87. Prompt 87: Sustainability Report Draft — Role: You are an ESG writer. Task: Draft a sustainability report section for [topic] showing environmental impact and improvements, guided by 2-shot examples. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise and evidence-based.
88. Prompt 88: Market Analysis Skeleton — Role: You are a market analyst. Task: Build a skeleton outline for a market analysis on [topic], using few-shot demonstrations to shape sections and data points. Context: [industry], [audience], [data]. Output format: [format]. Constraints: scannable and structured.
89. Prompt 89: Product Roadmap Justification — Role: You are a product strategist. Task: Justify a roadmap for [topic] with a few-shot demonstration example showing impact and risk. Context: [industry], [audience], [data]. Output format: [format]. Constraints: quantitative where possible.
90. Prompt 90: Auditing Log Summary — Role: You are an internal auditor. Task: Summarize an auditing log related to [topic] with key findings and recommendations, following a few-shot structure. Context: [industry], [audience], [data]. Output format: [format]. Constraints: objective and traceable.
91. Prompt 91: Contract Review Summary — Role: You are a legal assistant. Task: Review a contract clause related to [topic] and summarize potential implications in a few-shot template. Context: [industry], [audience], [data]. Output format: [format]. Constraints: plain-English summary.
92. Prompt 92: Festival Planning Guidelines — Role: You are an event planner. Task: Provide planning guidelines for a festival around [topic], using 2-shot demonstrations to illustrate logistics and risk. Context: [industry], [audience], [data]. Output format: [format]. Constraints: time-bound plan.
93. Prompt 93: Language Translation Template — Role: You are a translator. Task: Translate a document about [topic] with a few-shot template that preserves tone and style, providing notes for terminology. Context: [industry], [audience], [data]. Output format: [format]. Constraints: maintain accuracy and readability.
94. Prompt 94: Legal Compliance Outline — Role: You are a compliance lawyer. Task: Outline key legal compliance considerations for [topic] using two-shot demonstrations, with citations where applicable. Context: [industry], [audience], [data]. Output format: [format]. Constraints: precise language.
95. Prompt 95: Healthcare Quality Metrics — Role: You are a quality-improvement analyst. Task: Propose healthcare quality metrics for [topic], using demonstrated examples to justify each metric. Context: [industry], [audience], [data]. Output format: [format]. Constraints: actionable and measurable.
96. Prompt 96: Educational Game Design Prompt — Role: You are a game designer. Task: Design an educational game module around [topic], using a few-shot demonstration approach to show learning objectives and feedback. Context: [industry], [audience], [data]. Output format: [format]. Constraints: engaging and accessible.
97. Prompt 97: Crisis Communication Sheet — Role: You are a communications officer. Task: Create a crisis-communication sheet for [topic], illustrated with 2–3 sample messages. Context: [industry], [audience], [data]. Output format: [format]. Constraints: calm, clear, and consistent.
98. Prompt 98: Technical Specification Extract — Role: You are a technical writer. Task: Extract and format key specifications for [topic], using a few-shot approach to illustrate format and terminology. Context: [industry], [audience], [data]. Output format: [format]. Constraints: precise and scannable.
99. Prompt 99: Process Improvement Plan — Role: You are a process-improvement consultant. Task: Propose a process-improvement plan for [topic] with 2-shot demonstrations, including steps, owners, and KPIs. Context: [industry], [audience], [data]. Output format: [format]. Constraints: actionable and auditable.
100. Prompt 100: Final Summary and Next Steps — Role: You are a project-close assistant. Task: Produce a final summary for [topic] from the 2-shot demonstrations, and outline next steps with owners and timelines. Context: [industry], [audience], [data]. Output format: [format]. Constraints: concise and forward-looking.

Best Practices

• Reuse prompts by swapping placeholders to fit new domains.
• Keep outputs deterministic for easier verification; use explicit formats.
• Document the few-shot examples used to seed the pattern for future reuse.
• Test prompts in multiple contexts to ensure generalization.

Common Mistakes to Avoid

• Overlapping or vague labels that hinder parsing by answer engines.
• Ignoring output format constraints or tone requirements.
• Relying on too few demonstrations, leading to poor generalization.
• Failing to validate outputs against stated criteria.

FAQ

Question

What is Few-Shot Learning in prompts and why use it?

Question

How many demonstrations should I include in a few-shot prompt?

Question

What output formats work best for few-shot prompts?

Question

How can I test the reliability of these prompts?