# Style Guide: Industry Retrospectives

_For decade pieces, evolution articles, trend analysis_

## Purpose

This guide covers writing retrospective analyses that weave personal journey with industry evolution. These pieces help readers understand how we got here, what's changing, and where we're going by combining data analysis, personal experience, and pattern recognition.

## Voice Calibration

### The Witness-Participant

- Position yourself in the story: "I was there when..."
- Show evolution through your eyes: "When I started, we were writing MapReduce..."
- Acknowledge your vantage point: "From my position at Elementl..."
- Blend personal and industry timelines: "As I moved from Facebook to founding a company..."

### The Data Storyteller

- Let visualizations carry weight: "The chart tells the real story..."
- Be transparent about methodology: "I analyzed 500 job postings..."
- Acknowledge bias: "This skews toward venture-backed companies..."
- Find surprising patterns: "Notice how the peak was actually in 2019, not 2021..."

### The Pattern Recognizer

- Connect past to future: "We've seen this movie before..."
- Identify rhyming history: "The UNIX wars are playing out again..."
- Call out inflection points: "2018 was when everything changed..."
- Make non-obvious connections: "This mirrors what happened in the auto industry..."

## Document Structure

### 1. The Then-vs-Now Hook

Start with dramatic change:

```
"Two years ago, sitting down to write 'The Decade of Data Engineering'
would have been easy. The arc was clear: from chaos to order,
from scripts to platforms. But now? Everything has changed."
```

### 2. The Personal Thread

Weave your journey throughout:

```
"I joined Facebook in 2012, just as we were moving from
Hadoop to Spark. I didn't know it then, but I was witnessing
the birth of modern data engineering..."
```

### 3. The Timeline Reconstruction

Build the narrative chronologically:

- **The Before Times**: Set the baseline
- **The Catalyst**: What changed everything
- **The Gold Rush**: Everyone piles in
- **The Reckoning**: Reality sets in
- **The New Normal**: Where we stabilize

### 4. The Data Interlude

Let charts tell their story:

```
[Include compelling visualization]

"Look at that spike in 2019. Everyone assumed the peak was
during COVID, but the real growth happened earlier. This tells
us something important about..."
```

### 5. The Key Insights

What the pattern means:

```
## What This Actually Tells Us

1. **The cycle is accelerating**: What took 10 years now takes 3
2. **The old rules still apply**: Conway's Law hasn't gone anywhere
3. **But the parameters changed**: Scale is no longer the constraint
```

### 6. The Forward Projection

Where this leads:

```
## The Next Five Years

Based on these patterns, I believe we'll see:
- Consolidation around 3-4 major platforms
- A return to [historical pattern]
- Something nobody's expecting: [contrarian prediction]
```

## Language Patterns

### Temporal Anchoring

- "In 2012, nobody would have believed..."
- "By 2018, it was clear that..."
- "Looking back from 2024..."
- "Five years from now, we'll wonder why..."

### The Personal-Universal Bridge

- "My experience at Facebook taught me..." → "This industry-wide pattern shows..."
- "When our startup hit this wall..." → "Every company eventually faces..."
- "I learned the hard way..." → "The market learned collectively..."

### Data-Driven Narrative

- "The numbers tell a different story than the headlines"
- "What's surprising is not the trend but the timing"
- "If you adjust for [factor], the pattern reverses"
- "The outliers are actually the interesting part"

### Historical Echoes

- "This is the client-server debate all over again"
- "We're repeating the ERP consolidation of the 90s"
- "The same forces that drove [X] are now driving [Y]"

## Content Templates

### Decade Retrospective

```markdown
# The Decade of [Topic]: [Subtitle]

[Opening that acknowledges how perspective has changed]

## Where We Started (20XX)

[Set the scene - what was the world like?]

- Personal context: Where I was
- Industry context: What everyone believed
- Technical context: What tools we had

## The Journey

### Phase 1: [Name] (20XX-20XX)

[What happened and why]
[Personal anecdote illustrating the change]

### Phase 2: [Name] (20XX-20XX)

[Evolution and complications]
[Data visualization showing the trend]

### Phase 3: [Name] (20XX-Present)

[Current state]
[What surprised everyone]

## The Hidden Pattern

[Non-obvious insight from looking at the whole]

## What's Next

[Projection based on patterns]

## The Real Lesson

[Deeper wisdom beyond the specific trend]
```

### Trend Analysis with Data

```markdown
# [Surprising Claim About Trend]

[Hook challenging conventional wisdom]

## The Data

### Methodology

[How you gathered and analyzed]

### The Findings

[Key charts and what they show]

### The Surprise

[What contradicts common belief]

## The Why

[Explanation connecting to broader forces]

## Personal Journey Through This

[Your experience validates/illustrates the data]

## Implications

[What this means for different stakeholders]
```

## Retrospective-Specific Elements

### Multi-Scale Analysis

Connect three levels in every piece:

1. **Micro**: Individual engineer/team experience
2. **Meso**: Company and organizational patterns
3. **Macro**: Industry and economic forces

### The Methodology Box

Be transparent about analysis:

```
## How I Analyzed This
- Data sources: [List sources]
- Time period: [Specific dates]
- Sample size: [Number of data points]
- Limitations: [What's missing or biased]
- Code/queries: [Link if available]
```

### Generational Perspectives

Acknowledge different experiences:

- "If you joined the industry after 2018, you might not know..."
- "Veterans of the dot-com era will recognize..."
- "For those who lived through the NoSQL wars..."

### The Counternarrative

Always include what doesn't fit:

- "Not everyone followed this pattern..."
- "Company X succeeded by doing the opposite..."
- "The outliers tell us something important..."

## Quality Checklist

- [ ] Opens with perspective shift or surprise
- [ ] Weaves personal journey through industry narrative
- [ ] Includes original data analysis or visualization
- [ ] Identifies non-obvious patterns or connections
- [ ] Acknowledges multiple perspectives/experiences
- [ ] Makes specific, testable predictions
- [ ] Connects past patterns to future implications
- [ ] Provides deeper wisdom beyond specific trends

## Examples of Strong Patterns

### The Perspective Shift

"I wrote about this two years ago and got it completely wrong. Here's what I missed and what it teaches us..."

### The Generational Divide

"There are now two distinct generations of data engineers: those who remember before Spark, and those who don't. This divide explains why..."

### The Hidden Variable

"Everyone focuses on the technology change, but the real driver was the business model shift. When SaaS margins became..."

### The Rhyming History

"The consolidation we're seeing in data tools mirrors exactly what happened in databases in the 1980s. Larry Ellison's playbook is being run again by..."

## What to Avoid

- Nostalgia without insight
- Data without narrative
- Personal story without universal relevance
- Predictions without evidence
- Analysis without acknowledging limitations
- Industry inside baseball without context

## The Retrospective Formula

Every retrospective should:

1. **Reconstruct** the timeline accurately
2. **Reveal** surprising patterns in data
3. **Relate** personal experience to industry trends
4. **Recognize** multiple valid perspectives
5. **Reason** from history to future
6. **Provide** wisdom beyond the specific

---

_End of Style Guide Series. Return to Core Guide for foundational principles._
