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AI Pulse Article Writing Guidelines

Overview

This document provides guidelines for writing professional, informative articles for the AI Pulse publication. These guidelines were developed through iterative feedback to transform sensationalist, promotional content into analytical business writing suitable for executive audiences.

Core Principles

1. Informative Over Sensationalist

Do: - Present factual analysis with supporting data - Use measured, professional language - Focus on objective assessment and implications - Provide context and comparative analysis

Avoid: - Hyperbolic claims or superlatives ("revolutionary," "game-changing," "superhuman") - Exclamation marks and dramatic punctuation - Emotional appeals or urgency tactics - Unsupported promises of dramatic results

2. Professional Tone and Language

Preferred phrases: - "Analysis indicates..." instead of "This proves..." - "Approximately X% improvement" instead of "Massive X% gains" - "The system addresses limitations through..." instead of "This changes everything by..." - "Market data suggests..." instead of "Everyone knows..."

Academic/Business language: - "Implementation analysis" vs "opportunity" - "Performance impact assessment" vs "game-changing results" - "Technology maturity evaluation" vs "why this works now"

3. Realistic Cost and ROI Presentation

Do: - Present actual costs based on research - Include realistic implementation considerations - Provide conservative estimates with downside scenarios - Compare to market benchmarks and alternatives

Avoid: - Inflated cost comparisons without basis - Unrealistic ROI calculations (e.g., "78,000% returns") - Cherry-picked data points - Omitting implementation complexity or hidden costs

4. Credible Source Attribution

Requirements: - All claims must be supported by verifiable sources - Every number, percentage, dollar amount, and quote needs a traceable source - Use direct quotes with proper attribution - Link to primary sources when possible - Distinguish between similar approaches and identical approaches - Never invent company examples, statistics, or performance figures

Example of proper attribution: ✅ "Bridgewater's $2 billion fund uses multiple AI APIs including OpenAI, Anthropic, and Perplexity" [with source link] ❌ "Renaissance Technologies uses the same approach we're proposing" [unverified claim] ❌ "Studies show 78% improvement in efficiency" [without citing the actual study] ❌ "A Fortune 500 company saw 200% ROI" [invented example without real company name and source]

Article Structure

1. Header Format

# [Descriptive Title]: [Analysis Type]

**Date**: [Current Date]
**Author**: [Author Name]
**Tags**: [Relevant Categories]

**Sources**: 
- [Source 1 URL]: [Single sentence summary]
- [Source 2 URL]: [Single sentence summary]

---

2. Executive Summary

  • One paragraph describing the analysis purpose
  • Factual market context with specific examples
  • Objective assessment of the approach/technology
  • No promotional language or dramatic claims

3. Problem/Limitation Analysis

  • Describe current constraints objectively
  • Use industry benchmarks and standards
  • Quantify impacts where possible
  • Avoid characterizing competition negatively

4. Technical Solution Description

  • Explain methodology clearly but professionally
  • Include links to actual APIs/technologies referenced
  • Describe validation approaches
  • Provide concrete implementation examples

5. Cost Analysis

  • Present only verified costs
  • Include implementation considerations
  • Compare to realistic alternatives
  • Account for existing resources and capabilities

6. Performance Impact Assessment

  • Use conservative modeling approaches
  • Include risk assessment and downside scenarios
  • Reference academic studies where applicable
  • Avoid guaranteed outcomes or dramatic projections

7. Implementation Timeline

  • Realistic phasing based on organizational capacity
  • Clear success metrics and measurement approaches
  • Resource requirements and dependencies
  • Scalability considerations

8. Technology/Market Assessment

  • Current state of technology maturity
  • Industry adoption patterns and validation
  • Competitive landscape context
  • Regulatory or compliance considerations

9. Professional Conclusion

  • Summarize key findings objectively
  • Present balanced risk-reward assessment
  • Focus on strategic fit and implementation feasibility
  • Avoid emotional appeals or pressure tactics

Language Guidelines

Technical Terms

  • Define technical terms clearly on first use
  • Use business language over technical jargon where possible
  • Provide context for industry-specific concepts
  • Link to documentation for complex technologies

Numbers and Statistics

  • Always source quantitative claims
  • Use ranges rather than precise figures when appropriate
  • Include confidence intervals or uncertainty bounds
  • Distinguish between theoretical and actual results

Comparative Analysis

  • Only compare truly similar approaches
  • Distinguish between different methodologies
  • Avoid misleading benchmark comparisons
  • Include context for performance differences

Human-Like Writing Principles

Write Like You're Explaining Insights, Not Listing Facts

Good internal analysis explains what the information means and why it matters to the business, not just what happened.

Do: - Start with a clear analytical perspective on what you discovered - Connect findings to business implications throughout - Use examples and data to illustrate your analysis

Avoid: - Neutral, encyclopedia-style information dumps - Organizing by topic categories instead of logical analysis flow - Presenting facts without business context or significance

Create Natural Flow Instead of Rigid Structure

Bridge Sentences: End paragraphs by creating hooks for the next idea: - ✅ "While these supply chain disruptions are a logistical nightmare for manufacturers, their most immediate consequence is felt directly in consumers' wallets." - ❌ "This concludes the analysis of supply chain disruptions. Impact on Consumer Prices: Consumer prices have risen..."

Transitional Guidance: Use sophisticated phrases instead of subheadings: - ✅ "This trend, however, has an unexpected downside..." - ❌ Negative Consequences

Question and Answer Flow: Pose questions that the next paragraph answers: - ✅ "The company captured 10% market share in its first year. But can that rapid growth be sustained? The data suggests significant headwinds..."

Weave Data Into Narrative (No Bullet Lists)

The Data Sandwich: Never drop statistics alone - sandwich between context and interpretation: - ✅ "While the headline figure of $50M in Q3 revenue seems impressive, it masks a worrying trend. That 12% year-over-year growth represents a significant slowdown from the previous quarter's 30%. More alarmingly, customer acquisition costs have ballooned to $110, suggesting the company is paying a steep price for increasingly marginal gains." - ❌ Bullet lists of metrics without context

Personify Examples: Frame case studies around specific companies or people: - ✅ "For a mid-sized firm like ProLogistics, razor-thin shipping margins were becoming unsustainable. Their solution was a radical overhaul of routing algorithms, ultimately slashing fuel costs by 20%." - ❌ "One logistics company improved efficiency by 20%."

Sound Professional Yet Conversational

Active Voice: More direct and confident than passive voice: - ✅ "The committee decided to reduce the budget" - ❌ "It has been decided by the committee that the budget will be reduced"

Vary Sentence Length: Create rhythm by mixing long, complex sentences with short, punchy ones: - ✅ "While legacy systems present challenges related to data integration, security vulnerabilities, and skilled personnel scarcity, the biggest problem is simpler. They're too slow."

Be Specific, Not Generic: Use concrete details instead of business jargon: - ✅ "API costs total $3,564 annually across four platforms" - ❌ "This solution offers significant cost advantages and strategic value" - ✅ "The system processes 1,000 securities with weekly updates" - ❌ "The platform delivers scalable, enterprise-grade capabilities"

Avoid Business Clichés: Use plain language that executives can act on: - ✅ "Bridgewater's fund uses OpenAI, Anthropic, and Perplexity APIs" - ❌ "Bridgewater leverages best-in-class AI solutions for optimal synergies" - ✅ "Each API call costs $0.02 on average" - ❌ "The pricing model provides exceptional value propositions"

Structure Without Over-Organizing

Narrative Frameworks: Use story patterns instead of topic outlines: - Problem/Agitation/Solution: Define problem → explain why painful → present solution - Thesis/Antithesis/Synthesis: Common view → conflicting view → nuanced resolution

Provocative Subheadings (if needed): Make them compelling, not descriptive: - ✅ "The One Hurdle Everyone Forgets" - ❌ "Implementation Challenges"

Common Mistakes to Avoid

Content Issues

  • Claiming similar methods without verification
  • Overstating performance benefits or cost savings
  • Using outlier examples as representative cases
  • Ignoring implementation complexity or requirements

Structure Issues (NEW)

  • Over-reliance on bullet points and bolded subheadings
  • Rigid section breaks that interrupt narrative flow
  • Organizing by topic categories instead of logical argument progression
  • Uniform paragraph and sentence lengths that create monotonous rhythm

Style Issues

  • Sensationalist headlines or section titles
  • Promotional language disguised as analysis
  • Emotional manipulation or fear-based arguments
  • Oversimplification of complex technical systems
  • Robot-like formatting (excessive bullets, identical paragraph structure)
  • Passive voice overuse (sounds academic and evasive)
  • Data without context (dropping statistics without interpretation)
  • Business jargon and clichés ("synergies," "best-in-class," "scalable solutions")
  • Vague generalities ("significant value," "strategic advantages") instead of specific facts

Source Issues

  • Circular references or weak sourcing
  • Misattributing methodologies or results
  • Cherry-picking data to support conclusions
  • Failing to update claims when contradicted by research

Review Checklist

Before publishing, ensure:

Content Quality: - [ ] All factual claims are sourced and verifiable (no hallucinated facts) - [ ] Every number, statistic, and quote has a traceable source - [ ] Cost analysis is realistic and based on actual pricing from verified sources - [ ] Performance projections are conservative and risk-adjusted - [ ] Technology comparisons are accurate and fair - [ ] Sources are properly attributed with summary descriptions - [ ] No sensationalist language or unsupported claims remain - [ ] Company examples and case studies are real and accurately described

Human-Like Writing: - [ ] Article provides clear analysis and business context, not just lists information - [ ] Paragraphs flow naturally with bridge sentences and transitions - [ ] Data is woven into narrative with context and interpretation - [ ] Sentence length and structure varies to create rhythm - [ ] Uses active voice and conversational but professional tone - [ ] Minimal bullet points and bolded subheadings - [ ] No rigid section breaks that interrupt narrative flow

Examples

Good Executive Summary

"This analysis examines the business case for implementing a multi-API research system that leverages four AI research platforms to enhance investment analysis capabilities across our portfolio companies. Market context shows Bridgewater Associates launched a $2 billion fund in 2024 incorporating multiple AI research APIs. The analysis shows this approach can enhance existing research capabilities while requiring minimal additional infrastructure investment."

Poor Executive Summary

"We can build an AI research system for $60K that delivers $2.8M in annual value! This approach is already working with leading firms generating superhuman results. This isn't about replacing human expertise - it's about giving our teams game-changing research capabilities that will revolutionize our entire portfolio!"

The difference: The good version is measured, factual, and professional. The poor version uses hyperbolic language, unsupported claims, and promotional tactics.