{"id":3701,"date":"2025-08-17T10:53:20","date_gmt":"2025-08-17T10:53:20","guid":{"rendered":"https:\/\/promptbestie.com\/?p=3701"},"modified":"2025-08-17T10:53:23","modified_gmt":"2025-08-17T10:53:23","slug":"prompt-engineering-2025-guide-efficient-smart-prompts","status":"publish","type":"post","link":"https:\/\/promptbestie.com\/es\/prompt-engineering-2025-guide-efficient-smart-prompts\/","title":{"rendered":"Mastering Prompt Engineering in 2025: The Complete Guide to Writing Efficient and Smart Prompts"},"content":{"rendered":"<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">Introduction: The Evolution of Prompt Engineering<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The landscape of artificial intelligence has transformed dramatically since the early days of simple command-line interactions. As we navigate 2025, prompt engineering has evolved from a niche skill to a critical competency that determines the success of AI implementations across industries. Whether you&#8217;re working with large language models (LLMs) like GPT-4 Turbo, Claude Sonnet 4, Gemini Ultra, or specialized domain models, the ability to craft efficient and intelligent prompts has become the difference between mediocre and exceptional AI performance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This comprehensive guide explores the cutting-edge techniques, tools, and strategies that define effective prompt engineering in 2025. We&#8217;ll dive deep into advanced methodologies that can dramatically improve your AI outputs while reducing computational costs and response times.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Current State of Prompt Engineering in 2025<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">The Multi-Model Ecosystem<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Unlike the early days of AI when developers worked primarily with single models, 2025&#8217;s AI landscape is characterized by a diverse ecosystem of specialized models. Each model family\u2014whether it&#8217;s OpenAI&#8217;s GPT series, Anthropic&#8217;s Claude models, Google&#8217;s Gemini, or emerging open-source alternatives\u2014requires nuanced prompting approaches.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Key developments shaping prompt engineering in 2025:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Model-specific optimization<\/strong>: Different models respond better to different prompting styles<\/li>\n\n\n\n<li><strong>Multimodal integration<\/strong>: Prompts now seamlessly combine text, images, audio, and video inputs<\/li>\n\n\n\n<li><strong>Real-time adaptation<\/strong>: Dynamic prompting systems that adjust based on model responses<\/li>\n\n\n\n<li><strong>Enterprise-scale deployment<\/strong>: Prompts designed for high-volume, production environments<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">The Rise of Prompt Operations (PromptOps)<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Just as DevOps revolutionized software development, PromptOps has emerged as a critical discipline in 2025. This approach treats prompts as versioned, tested, and continuously optimized assets within the AI development lifecycle.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example PromptOps Workflow:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># prompt-config.yml\nversion: \"2.1.3\"\nprompt_id: \"customer_support_escalation\"\nmodel: \"claude-sonnet-4-20250514\"\ntemperature: 0.3\nmax_tokens: 500\ntest_cases:\n  - input: \"angry customer complaint\"\n    expected_tone: \"empathetic\"\n    required_elements: &#91;\"acknowledgment\", \"solution\", \"follow_up\"]\ndeployment:\n  environment: \"production\"\n  rollback_trigger: \"success_rate &lt; 85%\"\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Core Principles of Efficient Prompt Design<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Specificity Over Verbosity<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The most common misconception among newcomers to prompt engineering is that longer prompts are inherently better. In 2025, we&#8217;ve learned that <strong>precision trumps length<\/strong>. Efficient prompts are laser-focused on the desired outcome.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example of inefficient prompting:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Please help me write some content for my website. I need something that's engaging and informative. It should be about technology trends, particularly AI and machine learning. Make it interesting for readers who might be interested in this topic. The content should be professional but not too technical.\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Optimized version:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Write a 300-word technology blog introduction about AI automation trends for IT professionals. Focus on practical implications, use conversational tone, include 2-3 specific examples from 2024-2025.\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">2. Context Hierarchy and Information Architecture<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Efficient prompts in 2025 follow a clear information hierarchy:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Role definition<\/strong> (if applicable)<\/li>\n\n\n\n<li><strong>Task specification<\/strong><\/li>\n\n\n\n<li><strong>Context and constraints<\/strong><\/li>\n\n\n\n<li><strong>Output format requirements<\/strong><\/li>\n\n\n\n<li><strong>Quality criteria<\/strong><\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">This structure ensures that the AI model processes information in order of importance, leading to more accurate and relevant outputs.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. Token Optimization Strategies<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">With token costs and context windows remaining important considerations, smart prompt engineers employ several optimization techniques:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Token-Efficient Techniques:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Abbreviation systems<\/strong>: Develop consistent shorthand for repeated concepts<\/li>\n\n\n\n<li><strong>Reference compression<\/strong>: Use numbered references instead of repeating long phrases<\/li>\n\n\n\n<li><strong>Selective detail<\/strong>: Include only information that directly impacts the output<\/li>\n\n\n\n<li><strong>Batch processing<\/strong>: Combine related tasks into single prompts when appropriate<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example of Token Optimization:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Inefficient (127 tokens):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>I need you to analyze the quarterly sales data for our company. Please look at the revenue numbers, the profit margins, the customer acquisition costs, and the customer lifetime value. Then provide insights about the revenue numbers, insights about the profit margins, insights about the customer acquisition costs, and insights about the customer lifetime value.\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Optimized (52 tokens):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Analyze Q3 sales data. For each metric (revenue, profit margins, CAC, CLV), provide:\n1. Key insight\n2. Trend vs Q2\n3. Recommendation\n\nData: &#91;attachment]\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Advanced Token Compression Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># Define abbreviations upfront\nAbbrev: UI=User Interface, UX=User Experience, API=Application Programming Interface\n\nTask: Review the UI design mockups for UX improvements. Focus on API integration points where users interact with external services. Prioritize UI elements that affect UX flow.\n\n# Saves ~30 tokens vs. writing out full terms\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Advanced Prompting Techniques for 2025<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Chain-of-Thought (CoT) 2.0<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The traditional chain-of-thought prompting has evolved significantly. Modern CoT implementations include:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Structured Reasoning Patterns:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Analysis Framework:\n1. Problem decomposition: &#91;Break down the complex task]\n2. Constraint identification: &#91;List limitations and requirements]\n3. Solution exploration: &#91;Consider multiple approaches]\n4. Validation check: &#91;Verify against criteria]\n5. Output synthesis: &#91;Combine findings into final response]\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Few-Shot Learning with Dynamic Examples<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Rather than static examples, 2025&#8217;s best practices involve dynamic example selection based on:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Task complexity<\/li>\n\n\n\n<li>Model capabilities<\/li>\n\n\n\n<li>Domain specificity<\/li>\n\n\n\n<li>User expertise level<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Implementation example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Code review for &#91;LANGUAGE]\nExpertise level: &#91;BEGINNER\/INTERMEDIATE\/ADVANCED]\n\nExamples will be selected based on:\n- Code complexity matching user level\n- Common patterns in the target language\n- Security considerations relevant to the domain\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Dynamic Few-Shot Example for Email Writing:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For Sales Team (Professional tone):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Example 1: \"Thank you for your interest in our enterprise solution. I'd like to schedule a brief call to understand your specific requirements...\"\n\nExample 2: \"Following up on our conversation yesterday, I've prepared a customized proposal that addresses the scalability concerns you mentioned...\"\n\nNow write: &#91;SALES EMAIL TASK]\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For Customer Support (Empathetic tone):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Example 1: \"I understand how frustrating this must be, and I want to make sure we resolve this quickly for you...\"\n\nExample 2: \"Thank you for bringing this to our attention. I've escalated your case to our senior technical team...\"\n\nNow write: &#91;SUPPORT EMAIL TASK]\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Advanced Multi-Domain Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Context: Legal document analysis\nUser expertise: Intermediate paralegal\nDocument type: Contract review\n\nSelected examples:\n1. Contract clause: \"The term 'Material Adverse Effect' shall mean...\" \n   Analysis: \"This definition is overly broad and could...\"\n   \n2. Liability clause: \"Neither party shall be liable for...\"\n   Analysis: \"Standard mutual limitation, but consider adding...\"\n\nYour task: Review the attached employment agreement for potential issues.\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Meta-Prompting and Self-Reflection<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Advanced prompt engineers now use meta-prompting techniques where the AI system evaluates and improves its own outputs:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Primary Task: &#91;Your main request]\n\nSelf-Evaluation Criteria:\n- Accuracy: Rate 1-10 and explain\n- Completeness: Identify any gaps\n- Clarity: Assess readability\n- Actionability: Evaluate practical value\n\nIf any criterion scores below 8, provide an improved version.\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Specialized Prompting Strategies by Use Case<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Technical Documentation and Code Generation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Best practices for development tasks:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Include relevant technology stack information<\/li>\n\n\n\n<li>Specify coding standards and conventions<\/li>\n\n\n\n<li>Define error handling requirements<\/li>\n\n\n\n<li>Request explanatory comments<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Generate a Python function for data validation with these specifications:\n- Input: Dictionary with user registration data\n- Validation rules: Email format, password strength (8+ chars, special chars), age 18+\n- Output: Boolean result + list of specific error messages\n- Style: Follow PEP 8, include type hints and docstrings\n- Error handling: Custom exceptions for each validation type\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Advanced Code Generation Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Create a React component with the following requirements:\n\nTechnical Stack:\n- React 18 with TypeScript\n- Styled-components for CSS\n- React Query for data fetching\n\nComponent Specifications:\n- Name: UserProfileCard\n- Props: userId (string), onEdit (function), isLoading (boolean)\n- Features: Avatar display, editable name field, status indicator\n- Accessibility: ARIA labels, keyboard navigation\n- Testing: Include Jest unit tests with 80%+ coverage\n\nCode Standards:\n- Use functional components with hooks\n- Implement proper error boundaries\n- Follow company ESLint config\n- Include comprehensive PropTypes\/TypeScript interfaces\n\nOutput format:\n1. Component file (.tsx)\n2. Styled components file (.styles.ts)\n3. Test file (.test.tsx)\n4. Usage documentation with examples\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Content Creation and Marketing<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Optimized approach for content generation:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Define target audience personas<\/li>\n\n\n\n<li>Specify brand voice and tone<\/li>\n\n\n\n<li>Include SEO requirements<\/li>\n\n\n\n<li>Set content structure requirements<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Detailed Content Creation Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Create a blog post for our SaaS company's content marketing:\n\nAudience Profile:\n- Role: IT Directors and CTOs at mid-market companies (100-1000 employees)\n- Pain points: Legacy system integration, security compliance, budget constraints\n- Content consumption: Prefers actionable insights, case studies, ROI data\n\nBrand Voice:\n- Tone: Professional but approachable, solution-focused\n- Avoid: Overly technical jargon, fear-mongering, vague promises\n- Include: Specific metrics, real customer examples, implementation timelines\n\nSEO Requirements:\n- Primary keyword: \"enterprise software migration\"\n- Secondary keywords: \"legacy system modernization,\" \"cloud migration ROI\"\n- Target length: 1500-2000 words\n- Include: Meta description, H2\/H3 structure, internal link opportunities\n\nContent Structure:\n1. Hook with relevant industry statistic\n2. Problem definition with specific scenarios\n3. Solution framework (3-4 key steps)\n4. Case study with quantified results\n5. Implementation roadmap\n6. Call-to-action for consultation\n\nDeliverables:\n- Blog post content\n- Social media snippets (LinkedIn, Twitter)\n- Email newsletter version\n- Featured image description for designer\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Email Marketing Sequence Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Create a 5-email onboarding sequence for new trial users:\n\nUser Context:\n- Just signed up for 14-day free trial\n- Role: Marketing managers at B2B companies\n- Goal: Increase trial-to-paid conversion rate\n\nEmail Sequence Structure:\nEmail 1 (Day 0): Welcome + quick setup guide\nEmail 2 (Day 2): Feature spotlight + use case examples\nEmail 3 (Day 5): Customer success story + best practices\nEmail 4 (Day 8): Advanced tips + webinar invitation\nEmail 5 (Day 12): Upgrade offer + objection handling\n\nFor each email, provide:\n- Subject line (A\/B test variants)\n- Preview text\n- Body content with personalization tokens\n- CTA button text and link\n- Success metrics to track\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Data Analysis and Research<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Structured prompts for analytical tasks:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Clearly define data sources and limitations<\/li>\n\n\n\n<li>Specify analysis methodology<\/li>\n\n\n\n<li>Request confidence levels and assumptions<\/li>\n\n\n\n<li>Include visualization requirements<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Comprehensive Data Analysis Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Analyze customer churn patterns for our subscription service:\n\nData Sources:\n- Customer database (demographics, subscription history)\n- Usage logs (feature engagement, login frequency)\n- Support tickets (complaint categories, resolution times)\n- Payment data (billing history, failed transactions)\n\nAnalysis Framework:\n1. Descriptive analysis: Churn rate trends over 24 months\n2. Cohort analysis: Retention by signup month and plan type\n3. Predictive modeling: Identify at-risk customers\n4. Segmentation: Group customers by churn risk factors\n\nMethodology Requirements:\n- Statistical significance testing for all findings\n- Control for seasonal variations\n- Account for data quality issues (missing values, outliers)\n- Include confidence intervals for predictions\n\nOutput Format:\n1. Executive summary (key findings, recommendations)\n2. Detailed analysis with methodology explanation\n3. Interactive dashboard mockup description\n4. Action plan with prioritized initiatives\n5. Success metrics for implementation tracking\n\nVisualization Needs:\n- Churn rate trend charts\n- Customer journey flow diagrams\n- Risk score distribution histograms\n- Correlation heatmaps for feature importance\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Market Research Analysis Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Conduct competitive analysis for our project management software:\n\nResearch Scope:\n- Direct competitors: Asana, Monday.com, ClickUp, Notion\n- Market segment: SMB teams (10-50 employees)\n- Geographic focus: North America and Europe\n- Time period: Current state + 12-month trend analysis\n\nAnalysis Dimensions:\n1. Feature comparison matrix\n2. Pricing strategy analysis\n3. Customer sentiment analysis (reviews, social media)\n4. Market positioning and messaging\n5. Product roadmap predictions\n\nResearch Sources:\n- Public product documentation\n- Customer review platforms (G2, Capterra, TrustRadius)\n- Social media mentions and discussions\n- Industry analyst reports\n- Competitor blog posts and marketing materials\n\nDeliverables:\n1. Competitive landscape overview\n2. SWOT analysis for each competitor\n3. Market gap identification\n4. Positioning recommendations\n5. Feature development priorities\n6. Go-to-market strategy insights\n\nInclude:\n- Confidence levels for each finding\n- Data collection methodology\n- Limitations and assumptions\n- Update schedule for ongoing monitoring\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Tools and Frameworks for Prompt Optimization<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Prompt Testing and Validation Platforms<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Leading tools in 2025:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>PromptLayer<\/strong>: Version control and A\/B testing for prompts<\/li>\n\n\n\n<li><strong>Weights &amp; Biases Prompts<\/strong>: Experiment tracking and optimization<\/li>\n\n\n\n<li><strong>LangChain Hub<\/strong>: Community-driven prompt sharing and testing<\/li>\n\n\n\n<li><strong>PromptBase<\/strong>: Marketplace and testing platform for prompts<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2. Automated Prompt Generation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>AI-powered prompt optimization tools:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>AutoPrompt<\/strong>: Machine learning-based prompt discovery<\/li>\n\n\n\n<li><strong>PromptSource<\/strong>: Template-based prompt generation<\/li>\n\n\n\n<li><strong>GPT-Prompt-Engineer<\/strong>: Recursive prompt improvement systems<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">3. Performance Monitoring and Analytics<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Modern prompt engineering requires continuous monitoring:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Response quality metrics<\/li>\n\n\n\n<li>Token usage optimization<\/li>\n\n\n\n<li>Latency analysis<\/li>\n\n\n\n<li>Cost-effectiveness tracking<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Real-World Implementation Strategies<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Enterprise Deployment Patterns<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Successful enterprise prompt engineering includes:<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Template Libraries<\/strong>: Standardized prompts for common business functions<\/li>\n\n\n\n<li><strong>Approval Workflows<\/strong>: Quality control processes for production prompts<\/li>\n\n\n\n<li><strong>Performance Monitoring<\/strong>: Real-time tracking of prompt effectiveness<\/li>\n\n\n\n<li><strong>Cost Management<\/strong>: Token usage optimization across teams<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Industry-Specific Applications<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Healthcare:<\/strong> HIPAA-compliant prompts with medical terminology precision<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Healthcare Example &#8211; Patient Note Summarization:<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Summarize patient consultation notes\n\nHIPAA Compliance Requirements:\n- Replace all personal identifiers with &#91;PATIENT], &#91;DOCTOR], &#91;FACILITY]\n- Remove specific dates, use relative time (e.g., \"3 days ago\")\n- Exclude exact addresses, phone numbers, insurance details\n- Maintain clinical accuracy while protecting privacy\n\nMedical Context:\n- Patient: 45-year-old presenting with chest pain\n- Setting: Emergency department consultation\n- Required output: Structured clinical summary\n\nOutput Format:\nChief Complaint: &#91;brief description]\nHistory of Present Illness: &#91;relevant timeline and symptoms]\nAssessment: &#91;clinical findings and differential diagnosis]\nPlan: &#91;treatment recommendations and follow-up]\n\nQuality Controls:\n- Verify medical terminology accuracy\n- Ensure no diagnostic speculation beyond provided information\n- Flag any unclear medical abbreviations for clarification\n- Include confidence level for clinical interpretations\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Finance:<\/strong> Risk-aware prompts with regulatory compliance considerations<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Financial Example &#8211; Investment Analysis:<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Analyze investment opportunity for institutional client\n\nRegulatory Framework:\n- Compliance: SEC guidelines for investment recommendations\n- Disclosure: Include all material risks and conflicts of interest\n- Documentation: Provide sources for all financial data and assumptions\n- Suitability: Consider client risk profile and investment objectives\n\nAnalysis Structure:\n1. Company Overview\n   - Business model and competitive position\n   - Management team and governance\n   - Market opportunity and addressable market\n\n2. Financial Analysis\n   - Revenue growth and profitability trends\n   - Balance sheet strength and debt capacity\n   - Cash flow generation and capital allocation\n\n3. Valuation Assessment\n   - Multiple methodologies (DCF, comparable company, precedent transactions)\n   - Sensitivity analysis for key assumptions\n   - Risk-adjusted return expectations\n\n4. Risk Assessment\n   - Business risks (market, competitive, operational)\n   - Financial risks (liquidity, credit, market)\n   - Regulatory and compliance risks\n   - ESG considerations\n\nRequired Disclaimers:\n- Past performance does not guarantee future results\n- All investments carry risk of loss\n- This analysis is for informational purposes only\n- Consult qualified professionals before making investment decisions\n\nConfidence Levels:\n- Rate each major conclusion on 1-10 scale\n- Identify key assumptions and their sensitivity\n- Highlight areas requiring additional due diligence\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Legal:<\/strong> Citation-heavy prompts with accuracy verification requirements<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Legal Example &#8211; Contract Review:<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Review commercial lease agreement for potential issues\n\nLegal Framework:\n- Jurisdiction: &#91;State] commercial law\n- Client type: Small business tenant\n- Lease type: Commercial retail space\n- Review standard: Identify material risks and unfavorable terms\n\nReview Categories:\n1. Financial Terms\n   - Base rent and escalation clauses\n   - Additional charges (CAM, taxes, insurance)\n   - Security deposit and personal guarantees\n   - Default and remedies\n\n2. Operational Provisions\n   - Permitted use restrictions\n   - Modification and improvement rights\n   - Assignment and subletting restrictions\n   - Maintenance and repair obligations\n\n3. Risk Allocation\n   - Insurance requirements and liability\n   - Indemnification provisions\n   - Force majeure and casualty clauses\n   - Early termination rights\n\nCitation Requirements:\n- Reference specific contract sections (e.g., \"Section 4.2\")\n- Cite relevant state statutes when applicable\n- Note industry standard practices vs. unusual provisions\n- Cross-reference related clauses that may conflict\n\nRisk Assessment:\n- High risk: Terms that could cause business disruption\n- Medium risk: Unfavorable but manageable provisions\n- Low risk: Standard terms with minor negotiation opportunities\n\nOutput Format:\n1. Executive Summary: Top 3-5 issues requiring attention\n2. Detailed Analysis: Section-by-section review with recommendations\n3. Negotiation Priorities: Ranked list of proposed changes\n4. Red Flags: Deal-breaker issues requiring immediate attention\n\nQuality Assurance:\n- Double-check all section references\n- Verify legal terminology accuracy\n- Ensure recommendations are actionable\n- Flag areas requiring specialized expertise (tax, environmental, etc.)\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Education:<\/strong> Adaptive prompts that scale with student knowledge levels<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Education Example &#8211; Adaptive Math Tutoring:<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Create personalized math explanation\n\nStudent Profile:\n- Grade level: 8th grade\n- Current topic: Linear equations\n- Learning style: Visual learner with step-by-step preference\n- Struggle areas: Word problems, translating text to equations\n- Strengths: Basic arithmetic, pattern recognition\n\nAdaptive Instruction Framework:\n1. Assessment Check\n   - Quick diagnostic: \"Solve: 2x + 5 = 13\"\n   - Based on response, adjust explanation complexity\n\n2. Concept Introduction\n   - If student struggles with basics: Review fundamental concepts\n   - If student grasps basics: Move to application problems\n   - If student excels: Introduce advanced variations\n\n3. Learning Progression\n   Level 1: Visual models and concrete examples\n   Level 2: Abstract symbols with guided practice\n   Level 3: Independent problem-solving\n   Level 4: Real-world applications\n\nExample Problem Adaptation:\n\n*For struggling students:*\n\"Let's use a visual approach. Imagine you have some boxes (x) and loose marbles. \nIf 2 boxes + 5 loose marbles = 13 total marbles, how many marbles are in each box?\"\n\n*For advanced students:*\n\"A phone plan costs $25 monthly plus $0.10 per text. If your bill is $35, how many texts did you send? \nCreate an equation and solve, then verify your answer.\"\n\nScaffolding Elements:\n- Provide hints before showing solutions\n- Use real-world contexts relevant to student interests\n- Break complex problems into smaller steps\n- Celebrate progress and explain reasoning behind correct answers\n\nAssessment Integration:\n- Track which explanation methods work best\n- Note common error patterns for future prevention\n- Adjust difficulty based on success rate\n- Recommend additional practice areas\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Common Pitfalls and How to Avoid Them<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Over-Engineering Complexity<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Problem:<\/strong> Creating prompts that are unnecessarily complex <strong>Solution:<\/strong> Start simple and add complexity only when needed<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example of Over-Engineering:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># Overly Complex Version (158 tokens)\nYou are an expert senior software engineer with 15+ years of experience in multiple programming languages, frameworks, and architectural patterns. You have deep knowledge of design patterns, SOLID principles, clean code practices, and enterprise software development. Given the following code snippet, please conduct a comprehensive analysis that includes but is not limited to: code quality assessment, security vulnerability identification, performance optimization opportunities, maintainability considerations, scalability implications, and adherence to industry best practices. Please structure your response with clear sections for each area of analysis and provide specific, actionable recommendations with code examples where applicable.\n\nCode to review: &#91;simple 10-line function]\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Simplified Effective Version (31 tokens):<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Review this code for bugs, security issues, and improvements. Provide specific fixes with examples.\n\nCode: &#91;simple 10-line function]\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">2. Model-Agnostic Assumptions<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Problem:<\/strong> Assuming all AI models respond identically to prompts <strong>Solution:<\/strong> Test and optimize prompts for specific model families<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Model-Specific Examples:<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For GPT-4 (prefers structured reasoning):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Step 1: Analyze the problem\nStep 2: Consider alternatives\nStep 3: Implement solution\nStep 4: Validate results\n\nProblem: &#91;your task]\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For Claude (responds well to conversational context):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>I need help with &#91;task]. Here's the context: &#91;background information]. \nWhat approach would you recommend, and can you help me implement it?\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><em>For Gemini (excels with multimodal inputs):<\/em><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Analyze this diagram &#91;image] alongside the following data &#91;text]. \nIdentify patterns and provide insights that combine both visual and textual information.\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">3. Static Prompt Design<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Problem:<\/strong> Using fixed prompts without adaptation <strong>Solution:<\/strong> Implement feedback loops and continuous optimization<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example of Adaptive Prompting:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code># Version 1.0 - Initial prompt\nGenerate a product description for: &#91;product name]\n\n# Version 1.1 - After poor results\nGenerate a compelling product description for &#91;product name]:\n- Target audience: &#91;specific demographic]\n- Key benefits: &#91;list 3 main benefits]\n- Tone: &#91;professional\/casual\/exciting]\n- Length: &#91;word count]\n\n# Version 1.2 - After A\/B testing\nCreate a &#91;tone] product description for &#91;product name] that appeals to &#91;target audience].\n\nFocus on these benefits: &#91;benefits list]\nInclude: &#91;specific elements that tested well]\nAvoid: &#91;elements that tested poorly]\nTarget length: &#91;optimized word count]\n\nTemplate: &#91;proven structure from best performers]\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">4. Insufficient Error Handling<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Problem:<\/strong> Not accounting for edge cases and unexpected outputs <strong>Solution:<\/strong> Include explicit error handling and fallback instructions<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Example of Robust Error Handling:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Task: Extract key information from customer feedback\n\nPrimary Instructions:\n1. Identify sentiment (positive\/negative\/neutral)\n2. Extract main complaint or praise\n3. Categorize issue type (product, service, billing, etc.)\n4. Rate urgency (low\/medium\/high)\n\nError Handling:\n- If text is unclear\/ambiguous: Mark as \"requires_human_review\"\n- If multiple languages detected: Note \"multilingual_content\" \n- If no clear sentiment: Default to \"neutral\" and explain why\n- If text is too short (&lt;10 words): Return \"insufficient_data\"\n- If contains personal info: Flag as \"contains_pii\" and redact\n\nFallback Response Format:\n{\n  \"status\": \"error_type\",\n  \"message\": \"explanation\",\n  \"partial_results\": \"any extractable data\",\n  \"recommended_action\": \"next steps\"\n}\n\nValidation Check:\nBefore responding, verify that all required fields are populated and make sense in context.\n<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Advanced Error Handling Example:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>Code debugging assistant with comprehensive error handling:\n\nPrimary Function: Debug Python code and suggest fixes\n\nInput Validation:\n- Check if input is valid Python syntax\n- Verify code completeness (no missing imports\/functions)\n- Identify if problem is runnable or theoretical\n\nError Categories:\n1. Syntax errors \u2192 Provide corrected syntax + explanation\n2. Logic errors \u2192 Trace execution + suggest fix\n3. Runtime errors \u2192 Identify cause + prevention\n4. Performance issues \u2192 Suggest optimizations\n5. Style violations \u2192 Recommend improvements\n\nFallback Responses:\n- Incomplete code: \"Need more context. Please provide &#91;specific missing elements]\"\n- Non-Python code: \"This appears to be &#91;language]. Would you like me to convert to Python or debug in original language?\"\n- Unclear requirements: \"I see multiple possible issues. Which are you most concerned about: &#91;list options]\"\n\nQuality Assurance:\n- Test suggested fixes for basic syntax validity\n- Provide working code examples when possible\n- Include explanation of why the fix works\n- Suggest related improvements when relevant\n<\/code><\/pre>\n\n\n\n<h2 class=\"wp-block-heading\">Measuring Prompt Effectiveness<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Key Performance Indicators (KPIs)<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Quality Metrics:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Relevance score (1-10 rating)<\/li>\n\n\n\n<li>Accuracy percentage<\/li>\n\n\n\n<li>Completeness assessment<\/li>\n\n\n\n<li>User satisfaction ratings<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Efficiency Metrics:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Token usage per task<\/li>\n\n\n\n<li>Response time<\/li>\n\n\n\n<li>Cost per output<\/li>\n\n\n\n<li>Success rate on first attempt<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Business Impact Metrics:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Time saved compared to manual processes<\/li>\n\n\n\n<li>Error reduction percentage<\/li>\n\n\n\n<li>User adoption rates<\/li>\n\n\n\n<li>Return on investment (ROI)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Future Trends and Emerging Techniques<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Adaptive Prompting Systems<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">AI systems that automatically adjust prompts based on:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>User behavior patterns<\/li>\n\n\n\n<li>Historical success rates<\/li>\n\n\n\n<li>Real-time feedback<\/li>\n\n\n\n<li>Contextual environment changes<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2. Multimodal Prompt Integration<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Emerging capabilities:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Video-to-text prompting<\/li>\n\n\n\n<li>Audio-enhanced instructions<\/li>\n\n\n\n<li>Interactive diagram integration<\/li>\n\n\n\n<li>Real-time sensor data incorporation<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">3. Collaborative AI Prompting<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Team-based prompt engineering:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Shared prompt libraries<\/li>\n\n\n\n<li>Collaborative editing environments<\/li>\n\n\n\n<li>Cross-functional prompt reviews<\/li>\n\n\n\n<li>Community-driven optimization<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">4. Ethical and Responsible Prompting<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Growing focus areas:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Bias detection and mitigation<\/li>\n\n\n\n<li>Privacy-preserving prompt design<\/li>\n\n\n\n<li>Transparency in AI decision-making<\/li>\n\n\n\n<li>Sustainable AI practices<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Building Your Prompt Engineering Toolkit<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Essential Skills for 2025<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Technical Competencies:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Understanding of transformer architectures<\/li>\n\n\n\n<li>Familiarity with multiple AI model APIs<\/li>\n\n\n\n<li>Basic programming skills for automation<\/li>\n\n\n\n<li>Data analysis capabilities for performance tracking<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Soft Skills:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Clear communication and writing ability<\/li>\n\n\n\n<li>Analytical thinking and problem decomposition<\/li>\n\n\n\n<li>Creativity in approach design<\/li>\n\n\n\n<li>Patience for iterative optimization<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Recommended Learning Path<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Foundation<\/strong>: Start with basic prompt engineering principles<\/li>\n\n\n\n<li><strong>Specialization<\/strong>: Focus on your industry or use case<\/li>\n\n\n\n<li><strong>Tool Mastery<\/strong>: Learn key platforms and frameworks<\/li>\n\n\n\n<li><strong>Community Engagement<\/strong>: Join prompt engineering communities<\/li>\n\n\n\n<li><strong>Continuous Learning<\/strong>: Stay updated with model developments<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Best Practices Checklist<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Before deploying any prompt in a production environment, ensure you&#8217;ve addressed:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u2713 Clarity and Specificity<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Clear task definition<\/li>\n\n\n\n<li>Specific output requirements<\/li>\n\n\n\n<li>Unambiguous instructions<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u2713 Efficiency Optimization<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Token usage minimization<\/li>\n\n\n\n<li>Response time considerations<\/li>\n\n\n\n<li>Cost-effectiveness validation<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u2713 Quality Assurance<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Multiple test scenarios<\/li>\n\n\n\n<li>Edge case handling<\/li>\n\n\n\n<li>Error recovery mechanisms<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u2713 Scalability Planning<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Volume handling capabilities<\/li>\n\n\n\n<li>Performance under load<\/li>\n\n\n\n<li>Maintenance requirements<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u2713 Ethical Considerations<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Bias detection and mitigation<\/li>\n\n\n\n<li>Privacy protection<\/li>\n\n\n\n<li>Responsible AI usage<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion: The Path Forward<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">As we progress through 2025, prompt engineering continues to evolve from an art to a science. The most successful practitioners combine technical expertise with creative problem-solving, always keeping the end user&#8217;s needs at the center of their design process.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The techniques and strategies outlined in this guide provide a solid foundation for creating efficient and smart prompts. However, the field&#8217;s rapid evolution means that continuous learning and adaptation remain essential. The key to success lies not just in mastering current best practices, but in developing the analytical skills and mindset needed to adapt to new models, tools, and challenges as they emerge.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Remember that effective prompt engineering is ultimately about building better human-AI collaboration. The goal isn&#8217;t just to get the AI to produce output\u2014it&#8217;s to create a seamless, efficient, and reliable partnership that amplifies human capabilities while respecting the unique strengths and limitations of both human and artificial intelligence.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Take Action: Join the Prompt Engineering Community<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Ready to implement these strategies in your own work? Start by:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Experimenting<\/strong> with the techniques outlined in this guide<\/li>\n\n\n\n<li><strong>Measuring<\/strong> your current prompt performance using the KPIs discussed<\/li>\n\n\n\n<li><strong>Joining<\/strong> prompt engineering communities and forums<\/li>\n\n\n\n<li><strong>Sharing<\/strong> your findings and learning from others&#8217; experiences<\/li>\n\n\n\n<li><strong>Staying updated<\/strong> with the latest model releases and capabilities<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What&#8217;s your biggest prompt engineering challenge in 2025?<\/strong> Share your thoughts in the comments below, and let&#8217;s continue the conversation about building better AI interactions.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>","protected":false},"excerpt":{"rendered":"<p>Introduction: The Evolution of Prompt Engineering The landscape of artificial intelligence has transformed dramatically since the early days of simple command-line interactions. As we navigate 2025, prompt engineering has evolved from a niche skill to a critical competency that determines the success of AI implementations across industries. Whether you&#8217;re working with large language models (LLMs) [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":3702,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_crdt_document":"","footnotes":""},"categories":[50],"tags":[119,88,398,112,272,60,385,339,132,620,347,349,108,97,622,125,130,623,113,388,321,18,214,624,621],"class_list":["post-3701","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-prompting-guides","tag-ai-best-practices","tag-ai-development","tag-ai-efficiency","tag-ai-productivity","tag-ai-prompting","tag-ai-tools","tag-ai-workflows","tag-artificial-intelligence","tag-chain-of-thought","tag-claude-sonnet","tag-conversational-ai","tag-enterprise-ai-2","tag-few-shot-learning","tag-gpt-4","tag-intelligent-prompting","tag-llm-optimization","tag-machine-learning","tag-machine-learning-engineering","tag-natural-language-processing","tag-prompt-automation","tag-prompt-design","tag-prompt-engineering","tag-prompt-templates","tag-promptops","tag-token-optimization"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/posts\/3701","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/comments?post=3701"}],"version-history":[{"count":1,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/posts\/3701\/revisions"}],"predecessor-version":[{"id":3703,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/posts\/3701\/revisions\/3703"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/media\/3702"}],"wp:attachment":[{"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/media?parent=3701"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/categories?post=3701"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/promptbestie.com\/es\/wp-json\/wp\/v2\/tags?post=3701"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}