---
name: content-production
category: Content
description: >
  Interview-driven content production methodology for social posts, articles, carousels, and videos. Covers the 4-question interview framework, expert council critique pattern, anti-AI detection, platform-specific rules (LinkedIn fold points, character limits, aspect ratios), SEO + AI search optimization, and the 50% specificity rule. Built from producing hundreds of real posts — every pattern is field-tested.
---

# Content Production Methodology

## The Core Idea

Auto-generated content sounds auto-generated. The best content comes from real experiences. This methodology extracts those experiences through targeted questions, then uses AI to polish — not invent.

**The pipeline:**
```
INTERVIEW → DRAFT → CRITIQUE → REFINE → ART → PUBLISH
```

Every piece of content follows this arc. The interview is non-negotiable — it's the difference between generic advice and content that sounds like a real person wrote it.

## When to Use This Skill

- Writing social posts (LinkedIn, X/Twitter, Instagram, Threads)
- Creating LinkedIn carousels
- Writing long-form articles or blog posts
- Producing video scripts (short or long form)
- Any content that needs to sound human, not AI-generated

---

## The Interview (Start Here)

Never accept "write about X." Always interview first.

### The 4-Question Framework

Every format uses some variation of these 4 questions. Adapt wording to the format, but always cover these angles.

**Question 1 — The Hook**
"What's the one thing you'd tell someone about this in 10 seconds?"

Push for one of:
- A surprising result (something unexpected that happened)
- A contrarian take (something you believe that most disagree with)
- A specific number (a metric that tells the story)
- A vivid moment (a scene that captures the idea)

**Question 2 — The Story**
"Give me a specific moment or example that shows this."

Push for one of:
- A work situation (a meeting, decision, or failure)
- A conversation (something someone said)
- A before/after (how things were vs. now)
- A mistake you made (and what you learned)

**Question 3 — The Insight**
"What did you learn that most people get wrong about this?"

Push for one of:
- The common advice is wrong (everyone says X, actually Y)
- There's a hidden trade-off (choosing A means losing B)
- The real problem is different (people think X, it's actually Y)

**Question 4 — The Proof**
"What happened as a result? Any numbers, outcomes, or reactions?"

Push for one of:
- Hard metrics (revenue, time saved, conversion rate)
- Qualitative outcomes (team reactions, customer feedback)
- What you'd do differently (hindsight perspective)

### Follow-Up Probes

After each answer, check if it's specific enough:

| Vague answer | Follow-up |
|-------------|-----------|
| "It was really impactful" | "Can you give me a number? How much time/money?" |
| "My team liked it" | "Who specifically? What did they say?" |
| "We switched tools" | "From what to what? When?" |
| "It saved us a lot of time" | "How much per week/month? Compared to what?" |
| "Recently" | "What month? This year?" |
| "Someone told me" | "Who? What was the context?" |

### The 50% Rule

After the interview, verify you have enough material. At least 50% of the final content must contain:
- Specific personal details (names, dates, projects)
- Real numbers or metrics
- Named tools, technologies, or companies
- Opinions with conviction (not hedged advice)
- First-person experiences with specific context

If the interview answers are too vague, push for more specifics before writing. An extra minute in the interview = 10x better output.

### Format-Specific Variations

| Format | Questions | Additions |
|--------|-----------|-----------|
| Social post | Standard 4 | — |
| Carousel | 4 adapted | Topic, Audience, Takeaway, Tone |
| Article | 5 | Add SEO keyword question |
| Cover image | 3 | Subject, Content, Style |
| Thumbnail | 3 | Topic, Emotion, Text overlay |
| Video script | 4 | Topic, Hook, Format (teach/story/rant), CTA |

---

## The Production Pipeline

After the interview, content moves through stages. Each stage has a specific job.

### Stage 1: Writer

Takes the interview answers and produces a first draft. The key is passing the real details as the foundation:

```
INTERVIEW DATA (use as foundation — every claim must trace to these facts):

HOOK: [answer 1]
STORY: [answer 2]
INSIGHT: [answer 3]
PROOF: [answer 4]

RULES:
- Use the author's actual words, not generic advice
- If interview data includes specific numbers, use them exactly
- If NO specific numbers provided, write without numbers — use qualitative language
- NEVER use [X], [Y], [N] or any placeholder brackets
```

**Approval gate**: Read the draft. Does it sound like the person who answered the questions? If not, revise before continuing.

### Stage 2: Researcher

Fact-checks claims, adds citations where needed. For articles, ensures 3+ external sources from authoritative sources. For social posts, verifies any statistics mentioned.

### Stage 3: Expert Council (the quality engine)

This is the pattern that makes the content good. Instead of one AI pass, use multiple "expert" perspectives to critique and improve the draft.

**How it works:**
1. Define 3-5 expert personas with specific critique focuses
2. Each expert reviews the draft from their angle
3. A moderator synthesizes the critiques — what they agree on, where they disagree
4. The draft is rewritten incorporating the strongest critiques

**Example expert panel for copy:**

| Expert | Focus | What they critique |
|--------|-------|--------------------|
| Direct response writer | Hook strength, CTA clarity | "Does the first line stop the scroll?" |
| Brand voice specialist | Tone, authenticity | "Does this sound like a real person?" |
| SEO strategist | Keywords, structure | "Will this rank? Is it AI-search extractable?" |
| Audience advocate | Relevance, value | "Would the target reader actually care?" |
| Editor | Clarity, concision | "Can anything be cut without losing meaning?" |

**What to look for in the council output:**
- What all experts agreed on (high-confidence changes)
- Where they disagreed (the interesting tension — pick the side that serves the audience)
- Top 3 specific changes to the copy

**Approval gate**: This is the big one. Review the rewritten copy. If the council missed something or went in the wrong direction, send revision notes and re-run.

### Stage 4: Art

Generate a cover image, thumbnail, or carousel slides. For carousels, see the [carousel method](carousel-method.md).

Key principles:
- Copy is approved BEFORE image generation (never generate images for unapproved copy)
- Images should reinforce the message, not just decorate
- Platform-specific aspect ratios matter (see Platform Quick Reference below)

### Stage 5: Publish

Final validation against platform specs, then publish. Always validate:
- Character count within platform limits
- Hook completes before the fold point
- No banned words or AI structural tells
- Voice score passes threshold

---

## Platform Quick Reference

### Character Limits and Fold Points

| Platform | Max Chars | Fold Point | What Gets Cut |
|----------|----------|------------|---------------|
| LinkedIn | 3,000 | ~150 chars | Everything after "...see more" |
| X/Twitter | 280 (thread: 280/tweet) | None | Hard limit |
| Instagram | 2,200 | ~125 chars | Everything after "...more" |
| Facebook | 63,206 | ~480 chars | Everything after "See more" |
| Threads | 500 | None | Hard limit |

### Image Aspect Ratios

| Platform | Aspect Ratio | Pixels |
|----------|-------------|--------|
| LinkedIn | 1:1 | 1080x1080 |
| X/Twitter | 16:9 | 1600x900 |
| Instagram (post) | 4:5 | 1080x1350 |
| Instagram (story) | 9:16 | 1080x1920 |
| Facebook | 1.91:1 | 1200x630 |
| Threads | 1:1 | 1080x1080 |
| YouTube thumbnail | 16:9 | 1280x720 |

### Sweet Spot Lengths

| Platform | Sweet Spot | When to Go Long | When to Go Short |
|----------|-----------|-----------------|-----------------|
| LinkedIn | 800-1500 chars | Deep technical insight, story with arc | Quick observation, single takeaway |
| X/Twitter | 180-250 chars | Thread for multi-point argument | One sharp thought |
| Instagram | 500-1000 chars | Personal story, behind-the-scenes | Quick caption for visual |
| Facebook | 200-500 chars | Detailed update for niche group | Quick share or question |
| Threads | 200-400 chars | N/A (500 char limit) | Quick take |

---

## Hook Patterns

The hook is the first line. It must grab attention before the platform truncates it.

### Patterns That Work

| Pattern | Example |
|---------|---------|
| Specific number | "We cut deploy time from 45 minutes to 90 seconds." |
| Contrarian take | "Stop writing unit tests for your API layer." |
| Vivid scene | "The Slack message came in at 2am: 'prod is down.'" |
| Confession | "I mass-deleted 400 database columns last Tuesday." |
| Before/after | "6 months ago, every deploy was a prayer." |

### Patterns to Avoid

| Pattern | Why It Fails |
|---------|-------------|
| "Have you ever..." | Generic. Everyone skips rhetorical questions. |
| "I'm thrilled to share..." | Corporate AI slop. Instant scroll-past. |
| "In today's rapidly evolving..." | Banned phrase. |
| "Hot take:" / "Unpopular opinion:" | Overused format. Signals lazy writing. |
| Starting with a hashtag | Dead giveaway of automated posting. |

**Rule**: The hook must be COMPLETE before the fold. Don't start a sentence that gets cut off mid-thought. On LinkedIn, your entire hook lives in ~150 characters — roughly one sentence.

---

## Resource Files

| Need to... | Read this |
|------------|-----------|
| Check content for AI tells before publishing | [anti-ai-checklist.md](anti-ai-checklist.md) |
| Apply SEO + entity + anti-fluff rules | [quality-rules.md](quality-rules.md) |
| Build a LinkedIn carousel with ASCII storyboarding | [carousel-method.md](carousel-method.md) |

---

## Anti-Patterns

| Wrong | Right |
|-------|-------|
| Skip interview, just auto-generate | Always interview first — that's the whole point |
| Invent personal details AI doesn't know | Only use what the person actually told you |
| Accept vague answers ("it was great") | Push for names, dates, numbers, tools |
| Publish without explicit approval | Always ask before publishing |
| Generate 5 posts at once | One piece per session, quality over quantity |
| Use default prompts | Build custom prompts from interview answers |
| Generate images before approving copy | Copy first, images second |
| Use hashtags | Never. On any platform. They don't help anymore. |

# Anti-AI Checklist

Run every piece of content through this checklist before publishing. Zero tolerance — if any item is found, rewrite.

## Banned Words (40+)

### Corporate Buzzwords
leverage, game-changer, synergy, disrupt, paradigm shift, ecosystem, holistic, scalable, empower, harness, unleash, optimize, streamline, agile, pivot

### AI Filler Words
innovative, cutting-edge, groundbreaking, seamless, robust, transformative, revolutionize, exciting, passionate, journey, deep dive, dive into, unlock, supercharge

### Empty Intensifiers
incredibly, absolutely, truly, literally (when not literal), basically, essentially, fundamentally, exponentially

### Fake Enthusiasm
thrilled, delighted, blown away, mind-blowing, epic, crushing it, killing it, next-level

## Banned Phrases (20+)

- "In today's rapidly evolving..."
- "It's no secret that..."
- "The landscape of X is changing..."
- "Let's unpack this..."
- "Here's the thing..."
- "I'm excited to share..."
- "This is a game-changer..."
- "The future of X is here"
- "At the end of the day..."
- "It goes without saying..."
- "Needless to say..."
- "The bottom line is..."
- "In a nutshell..."
- "That being said..."
- "All things considered..."
- "Let me be clear..."
- "The reality is..."
- "What if I told you..."
- "Hot take:"
- "Unpopular opinion:"

## Structural Tells (AI Patterns to Avoid)

1. **The 5-point list with alliteration** — AI loves making every bullet start with the same letter or pattern
2. **The false anecdote** — "Last week I was at a conference and..." when no interview data supports this
3. **The manufactured statistic** — "73% of developers prefer..." without a real source
4. **The generic metaphor** — "like a Swiss Army knife" or "the GPS of business"
5. **The summary paragraph** — Restating everything said above in slightly different words
6. **The question opener** — "Have you ever wondered..." or "What if..."
7. **The triple parallel structure** — "It's faster, it's simpler, it's better" (fine occasionally, not every paragraph)
8. **The corporate sign-off** — "What are your thoughts? Drop a comment below!"
9. **The gratuitous emoji** — Using emojis as paragraph bullets or decoration
10. **The numbered thread format** — "1/ Here's a thread about..." (unless specifically requested)

## Anti-AI Detection Checklist

Content must read as expert-written, not AI-generated. Check for these tells:

- [ ] **No uniform sentence length** — vary between 5-word punches and 25-word explanations
- [ ] **No predictable structure** — not every section follows the same internal pattern
- [ ] **Includes specific opinions** — the author takes a stance, not "on one hand / on the other hand"
- [ ] **Contains unexpected examples** — not the most obvious illustration of each point
- [ ] **Uses concrete numbers** — "37% faster" not "significantly faster"
- [ ] **Has personality markers** — contractions, occasional informal phrasing, sentence fragments for emphasis
- [ ] **Includes caveats and limitations** — real experts know the edge cases
- [ ] **No perfect parallelism in every list** — real writing has slightly uneven list items
- [ ] **References specific experiences** — "we found that..." or "in practice..."
- [ ] **Avoids the word "delve"** — and "tapestry", "landscape", "paradigm shift", "game-changer", "revolutionize"

## The 50% Rule

At least 50% of the content should contain:
- Specific personal details from interviews
- Real numbers, dates, or project names
- Actual tools/technologies by name
- Opinions that could be disagreed with
- First-person experiences with specific context

If content is more than 50% generic advice anyone could give, it fails the checklist.

## How to Fix Flagged Content

1. Replace banned words with specific, concrete alternatives
2. Remove structural tells and rewrite naturally
3. Add real details from interviews
4. Read aloud — if it sounds like a press release, rewrite
5. Run through a voice matching pass to restore natural tone

# Carousel Method

LinkedIn carousels that teach, not sell. ASCII storyboard approval before any image generation.

## The 3 Steps

1. **Storyboard** — ASCII mockups of every slide. Get approval before anything gets generated.
2. **Generate** — Fire all slides in parallel with consistent style.
3. **Export** — Combine into PDF for LinkedIn upload.

Everything below supports these 3 steps.

---

## Step 1: Storyboard

Present ASCII mockups of ALL slides. This is mandatory. Nothing gets generated without approval.

### Format

```
SLIDE [N] — [purpose]
┌─────────────────────────┐
│                         │
│   [HEADLINE TEXT]       │
│                         │
│   [Body line 1]         │
│   [Body line 2]         │
│   [Body line 3]         │
│                         │
└─────────────────────────┘
```

### Slide Rules

- **One idea per slide.** If you need two sentences to explain what the slide is about, it's two slides.
- **25-50 words max per slide.** Headline + body. That's it.
- **No diagrams.** Text IS the slide. A tiny icon accent is ok. A flowchart is not.
- **Educational voice.** Explain how something works. No claims, no performance, no "I built."

### Narrative Arc (9-10 slides)

| Slide | Job |
|-------|-----|
| 1 | Cover — topic name, nothing else |
| 2-3 | Set up the concept — what are we talking about |
| 4-7 | Teach — one point per slide, build on each other |
| 8 | Examples — concrete things built with this |
| 9-10 | CTA — follow prompt or summary takeaway |

### Voice

Educational. Like explaining something to a smart person at a whiteboard. No:
- "I built" / "I discovered" / "Changed how I work"
- Rhetorical questions in quotes
- "That's it." as a mic drop
- Performative honesty ("The honest part is...")
- Listicle energy ("Here's 7 ways to...")

Just explain the thing.

### Content Source

Before writing slides, mine the author's transcripts, interviews, or notes for their actual educational explanations on the topic. Extract:
- Their exact phrases and metaphors
- How they explain concepts step by step to real people
- Concrete examples they give when teaching

Use their actual words in slide copy. The carousel should sound like the author at a whiteboard.

---

## Step 2: Generate

After storyboard approval, generate all slides in parallel.

### The Proven Composition (Text + Illustration)

Every slide follows this layout:
- **Upper third**: Bold serif headline + body text
- **Lower half**: Delicate black ink illustration that reinforces the headline's concept
- **No dead space**: The illustration fills the white space and adds meaning

The illustration is a **metaphor**, not a literal depiction. It should make the viewer "get it" faster.

| Headline | Illustration | Why It Works |
|----------|-------------|-------------|
| "APIs Are The Acid Test" | Beaker + pipette drop | Literal acid test — science metaphor |
| "Toss It To A Skill" | Hand releasing paper airplane | Delegation, letting go, launching |
| "It's Just Markdown" | Clean doc floating above messy paper pile | Simplification |
| "The Tight Loop" | Coiled spring | Iteration, momentum |
| "Edit The Markdown" | Hand with fountain pen writing | The act of editing |

### Illustration Rules

- **Metaphorical, not literal.** A beaker for "acid test", not a screenshot of a terminal.
- **One object.** Each illustration is one clean concept — a beaker, a hand, a pen. Not a scene.
- **Fine-tip Micron pen quality.** Precise architectural linework, consistent stroke weight.
- **No color.** Pure black ink on cream paper. No gray fills, no gradients.
- **Fills the space.** The illustration should occupy the lower 40-50% of the slide.

### Prompt Pattern

When generating slides with any image generation tool, use this structure:

```
A LinkedIn carousel slide on cream textured paper with a thin
black rectangular border inset from the edges.

In the upper third, large bold black serif headline: "[HEADLINE]".
Below in smaller serif: "[BODY TEXT]".

In the lower half, a beautiful delicate black ink line drawing of
[ILLUSTRATION DESCRIPTION]. The drawing has the quality of a fine-tip
Micron pen on premium cotton paper — precise architectural linework,
consistent stroke weight. Portrait 3:4 format. Editorial magazine style.
Pure black ink on cream paper only. No color, no gray fills.
```

Pass a reference image of the cream paper style to maintain consistency across slides.

### Prompt Rules

- Put the headline in the prompt as: `large bold black serif headline: "[TEXT]"`
- Put body text as: `Below in smaller serif: "[TEXT]"`
- Put illustration as: `In the lower half, a beautiful delicate black ink line drawing of [DESCRIPTION]`
- For cover slides: headline + subtitle + illustration centered
- For CTA slides: follow prompt, compass rose or pen accent
- NEVER ask for diagrams, flowcharts, architecture drawings, boxes with arrows
- Generate at low resolution first (1K). After approval, regenerate at 2K.

---

## Step 3: Export

LinkedIn carousels are PDFs. After all slides are approved:

1. Download all slide images in order
2. Combine into single PDF (one image per page, 1080x1350)
3. Upload PDF to LinkedIn as a document post

---

## Specs

| Spec | Value |
|------|-------|
| Dimensions | 1080x1350 px (3:4 portrait) |
| Format | PDF |
| Words per slide | 25-50 max |
| Font size | 40pt+ headline, 24pt+ body |
| Slide count | 8-10 |
| Style | Cream paper, black serif text, ink journal illustrations |
| Composition | Upper third: text. Lower half: ink illustration |
| Text/visual ratio | 60% text / 40% illustration |

---

## Anti-Patterns

| Don't | Do |
|-------|-----|
| Full-page architecture diagrams | Text + one metaphorical ink illustration |
| Boxes connected by arrows | "A → B → C" as text |
| Text-only slides with huge white space | Fill lower half with contextual ink drawing |
| Generic/literal illustrations | Metaphorical illustrations (beaker for "acid test") |
| Slides that require effort to parse | Slides absorbed in 2 seconds |
| Claims about what you built | Explain how something works |
| Generating before storyboard approval | ASCII first, always |

# Expert Council Method

The council is the quality engine. Instead of one AI pass, multiple expert personas critique and improve content from different angles across multiple rounds of debate. A moderator synthesizes the strongest points into the final output.

This is the single biggest improvement over "ask AI to write something." One pass produces generic content. Five experts debating it produces content that's been stress-tested from multiple angles.

---

## How It Works

```
DRAFT → EXPERTS CRITIQUE → DEBATE → MODERATOR SYNTHESIZES → REWRITE
              ↑                                                  │
              └──────── round 2, round 3 (configurable) ────────┘
```

Each round builds on the last. Experts don't just critique — they respond to each other's critiques, creating genuine intellectual tension that produces better output than any single perspective could.

---

## Expert Personas

Each expert in a panel has three attributes:

| Attribute | Purpose | Example |
|-----------|---------|---------|
| **Name** | The persona identity | "Ogilvy" |
| **Persona** | 1-2 sentences describing their POV and style | "Legendary ad man who insists on specifics over generalities. Every word must earn its place." |
| **Focus** | What they specifically critique | "Headlines, language specificity, use of numbers" |

### What Makes a Good Panel

A panel works when the experts **disagree productively**. You want tension between their perspectives:

- One expert demands clarity → another demands boldness
- One focuses on data → another focuses on emotion
- One cares about structure → another cares about voice

**Bad panel:** Five experts who all say the same thing. Agreement without tension produces no improvement.

**Good panel:** Five experts with overlapping but distinct concerns, who push the content in different — sometimes contradictory — directions. The moderator resolves the contradictions.

### Copy Council Example

| Expert | Focus | Persona |
|--------|-------|---------|
| Ogilvy | Headlines, language specificity, numbers | Legendary ad man. Every word must earn its place. Hates vague language. |
| Halbert | Voice authenticity, personal connection | Direct response copywriter. Reads copy aloud. If it doesn't sound like talking, rewrite it. |
| Schwartz | Audience awareness, positioning | Matches message sophistication to reader awareness level. Obsesses over what the reader already believes. |
| Handley | Authenticity, showing real failure | Content strategist. Spots when writing hides behind advice instead of showing real experience. |
| Lois | Bold concepts, differentiation | Hates safe. If the content could've been written by anyone, it fails. Pushes for a provocative angle. |

### Art Council Example

| Expert | Focus | Persona |
|--------|-------|---------|
| Niemann | Conceptual metaphor, visual wit | Transforms abstract ideas into single powerful images. Minimal elements, maximum meaning. |
| Steinberg | Line economy, surreal perspective | Fewer lines, more meaning. Finds the one visual angle that says everything. |
| Kalman | Typography as image, cultural commentary | Designs with text as a visual element. Bold, messy, human. |
| Scher | Scale, hierarchy, typographic impact | Large-scale thinking. Makes you feel the concept before you read the words. |

---

## The Debate Process

### Round Structure

**Default: 3 rounds.** Configurable per panel.

**Round 1 — Initial Critiques**
Each expert reads the draft and provides their critique through the lens of their focus area. They don't know what the other experts will say.

```
Ogilvy:   "The headline promises nothing specific. 'How I grew my business'
           could be anyone. Name the business, name the number."

Halbert:  "Read this aloud — it sounds like a press release, not a person.
           Where's the conversational rhythm?"

Schwartz: "This assumes the reader already cares about your framework.
           They don't. Start with their problem, not your solution."
```

**Round 2 — Cross-Critique**
Experts respond to each other. This is where the productive tension happens:

```
Halbert → Ogilvy:  "You're right about specifics, but don't kill the rhythm
                     chasing numbers. A specific story beats a specific stat."

Schwartz → Halbert: "Voice matters less than awareness matching. Write in any
                      voice you want — if you're talking past the reader,
                      they're gone."
```

**Round 3 — Convergence**
Experts settle on their strongest recommendations. Remaining disagreements are surfaced for the moderator.

### Moderator Synthesis

After all rounds, a moderator (separate from the experts) analyzes the debate and produces:

1. **Agreements** — What all experts agreed on (highest-confidence changes)
2. **Disagreements** — Where they split + which side the moderator chose and why
3. **Top 3 Changes** — The three most impactful changes to apply
4. **Rewritten Content** — The draft rewritten incorporating the top changes

The moderator is not another creative voice — it's a resolver. Its job is to identify the strongest critiques and apply them without losing the original intent.

---

## Council Output

The council produces a structured output used by the approval gate:

```
╭─ COUNCIL — 5 experts, 3 rounds ──────────────────────────╮
│                                                            │
│  Ogilvy     "[1-2 sentence critique summary]"              │
│  Halbert    "[1-2 sentence critique summary]"              │
│  Schwartz   "[1-2 sentence critique summary]"              │
│  Handley    "[1-2 sentence critique summary]"              │
│  Lois       "[1-2 sentence critique summary]"              │
│                                                            │
├─ Debate ──────────────────────────────────────────────────┤
│                                                            │
│  Agreed: [what all experts agreed on]                      │
│  Split:  [where they disagreed + which side won]           │
│  Top 3:  [top 3 changes applied to the copy]               │
│                                                            │
├─ Result ──────────────────────────────────────────────────┤
│                                                            │
│  [Full rewritten copy]                                     │
│                                                            │
│  Voice: [score]  │  Tokens: [n]  │  [duration]            │
╰────────────────────────────────────────────────────────────╯
```

**Progressive disclosure:** Show the summary panel by default. Offer "Show full critiques" to reveal the complete unabridged expert output. Most of the time, the summary + top 3 changes are enough to decide.

---

## Art Council (Visual Content)

The art council follows the same structure but produces visual direction instead of written critiques.

### What Changes

| Aspect | Copy Council | Art Council |
|--------|-------------|-------------|
| Expert output | Written critique of copy | Visual concept proposal |
| Debate focus | Messaging, tone, structure | Composition, style, visual metaphor |
| Moderator output | Rewritten copy | Winning direction (concept + mood + text placement) |
| Final artifact | Text content | Generated image |
| Winner | Implicit (best critiques applied) | Explicit (winning expert marked with ★) |

### Art Council Flow

```
COPY → ART EXPERTS PROPOSE CONCEPTS → DEBATE → WINNER DRIVES GENERATION
```

1. Each art expert proposes a visual concept for the content
2. Experts debate the concepts — which visual metaphor is strongest, clearest, most original
3. The moderator picks a winner and synthesizes the final direction
4. The winning direction drives image generation

### Art Council Output

```
🎨 ART COUNCIL — 4 experts, 3 rounds

  Niemann    "Single lightbulb with a crack — light leaks out as code"
  Steinberg  "Hands typing, but the keyboard keys are tiny people"      ★
  Kalman     "Giant POST-IT note wall with one idea circled"
  Scher      "The word SHIP in 200pt type, letter S is a rocket"

── Winner: Steinberg ──────────────────────────────────────
  Concept:  Hands typing on a keyboard where each key is a tiny person
  Text:     "Every keystroke is a decision"
  Mood:     surreal, contemplative
```

The ★ marks the winning expert whose concept drives the image generation.

---

## Panel Management

### Multiple Named Panels

Panels are named and stored independently. You can have several panels for different content types and swap between them.

**Examples:**
- `"default"` — general-purpose copy council
- `"strategy-experts"` — positioning and strategy focused
- `"dev-generosity"` — technical content with a giving-value voice
- `"art"` — default art direction panel
- `"art-photography"` — photo-realistic art direction

### Switching Active Panels

Each pipeline stage uses one active panel. The active panel is set in the stage configuration:

- Copy council defaults to the panel named `"default"`
- Art council defaults to the panel named `"art"`

To switch which panel a stage uses, update the stage configuration with the panel name. The pipeline resolves the active panel automatically at runtime.

### Creating Effective Panels

When building a new panel:

1. **Start with 3-5 experts** — fewer than 3 doesn't create enough tension, more than 5 creates noise
2. **Ensure distinct focus areas** — if two experts would say the same thing, merge them
3. **Include at least one contrarian** — someone who pushes against the default direction
4. **Match expertise to content type** — a copywriting panel for ads, a storytelling panel for case studies
5. **Test with real content** — run a piece through the panel and check if the critiques actually improve it

---

## Anti-Fabrication in Council

The council rounds enforce strict anti-fabrication rules at every stage:

- Experts cannot invent statistics the interview didn't provide
- If the interview data includes specific numbers, use them exactly
- If no numbers were provided, write without numbers — never use placeholders like [X] or [N]
- The 50% specificity rule applies to council output (at least half the content must contain specific personal details, real numbers, or named tools)

See [anti-ai-checklist.md](anti-ai-checklist.md) for the full list of banned patterns enforced during council.

---

## Why This Works

**Single AI pass:** "Write a LinkedIn post about scaling a startup." → Generic advice that could apply to anyone.

**Council method:** Five experts each critique the draft from their speciality. One says the headline is vague. Another says it reads like a press release. A third says it assumes too much reader awareness. The moderator synthesizes: add a specific number to the headline, rewrite the opening as a story beat, lower the assumed awareness level.

The result reads like someone who actually knows what they're talking about — because the council forces specificity from multiple angles simultaneously.

**The key insight:** Quality comes from productive disagreement, not consensus. When experts disagree, the moderator must choose — and the act of choosing produces stronger output than either expert's suggestion alone.

# Pipeline Architecture

The content production pipeline. This is the engine — how raw interview data becomes published content through multiple AI stages with human approval gates.

## The Pipeline

```
INTERVIEW → WRITER → RESEARCHER → COUNCIL → ART → POSTPROD → PUBLISH
               ↑         │            ↑        ↑
               │         │            │        │
            revise    enrich      approve   approve
```

Each stage has one job. The output of each stage feeds the next. Human approval gates sit after the two stages that matter most: **writer** (is this the right draft?) and **council** (did the experts improve it?).

---

## Stage Breakdown

### Writer

**Input:** Interview answers (hook, story, insight, proof) + format + platform
**Output:** First draft of the content
**Duration:** 5-10 seconds

The writer receives the raw interview data as a custom prompt:

```
INTERVIEW DATA (use as foundation — every claim must trace to these facts):

HOOK: [answer 1]
STORY: [answer 2]
INSIGHT: [answer 3]
PROOF: [answer 4]

VOICE: Direct, practitioner-level. No fluff. Short sentences.
NUMBERS: If interview data includes specific numbers, use them exactly.
IF NO SPECIFIC NUMBERS PROVIDED: write without numbers. Use qualitative
language. NEVER use [X], [Y], [N] or any placeholder brackets.
```

**Why the custom prompt matters:** Without interview data, the writer produces generic content and downstream stages invent specific numbers to fill the gaps. With interview data, every claim traces to something real. The anti-fabrication guardrails keep it honest.

**Approval gate:** Show the full draft. Ask: Continue or Revise?

### Researcher

**Input:** Writer's draft
**Output:** Enriched draft with verified facts, citations, or "passed unchanged"
**Duration:** 3-8 seconds

The researcher fact-checks claims, adds context where needed, and verifies any statistics. For articles, it ensures 3+ external sources from authoritative sources. For social posts, it verifies specific claims.

If the draft is already solid (common with good interview data), the researcher passes it through unchanged. This is fine — the stage exists as a safety net, not a mandatory transformation.

### Council (The Quality Engine)

**Input:** Researcher's output
**Output:** Rewritten content incorporating expert critiques
**Duration:** 30-60 seconds (the longest stage — multiple rounds of debate)

This is the stage that makes the content good. Instead of one AI pass, multiple "expert" personas critique and improve the draft from different angles.

See [expert-council-method.md](expert-council-method.md) for the full council methodology.

**Approval gate:** This is the big one. Show expert opinions, where they agreed, where they disagreed, the top changes, and the rewritten copy. Ask: Approve or Revise?

### Art

**Input:** Approved copy
**Output:** Generated image(s) matching the content
**Duration:** 20-45 seconds

The art stage runs its own separate council (art directors, not copywriters). Art experts propose visual concepts, debate approaches, and a winner drives the image generation.

For social posts: one image (1:1 for LinkedIn, 16:9 for Twitter).
For carousels: multiple slides (3:4 portrait, 1080x1350).

**Visual QC:** After generation, a vision model evaluates:
- Logical sense — do visual elements connect?
- Composition — clean layout, balanced, readable?
- Style match — does it match the target aesthetic?
- Text quality — is text legible and correctly placed?

If the overall score is below threshold, it regenerates with the current image as a reference (iterative refinement, not restart). This holds visual continuity while fixing issues.

### Postprod

**Input:** Approved copy + generated image(s)
**Output:** QC score + final copy adjustments
**Duration:** 3-5 seconds

Final quality check. Runs the anti-AI checklist, verifies voice consistency, checks platform-specific requirements (character count, fold point, no hashtags).

### Publish

**Input:** QC-passed content + images
**Output:** Saved to content library
**Duration:** 1-2 seconds

Saves the final content, images, and all metadata (scores, stage durations, expert critiques) to the content library.

---

## Approval Gates

Two mandatory gates. Everything else can auto-run.

### After Writer: "Is this the right draft?"

```
╭─ WRITER ──────────────────────────────────────────────────╮
│                                                            │
│  [Show the full draft copy]                                │
│                                                            │
├────────────────────────────────────────────────────────────┤
│  Words: [n]  │  Tokens: [n]  │  [duration]                │
╰────────────────────────────────────────────────────────────╯

Options: Continue | Revise | Run all remaining
```

If the user revises, collect their notes and re-run the writer stage with the notes appended to the custom prompt. The interview data stays — only direction changes.

### After Council: "Did the experts improve it?"

```
╭─ COUNCIL — [n] experts, [n] rounds ──────────────────────╮
│                                                            │
│  Expert 1    "[1-2 sentence critique summary]"             │
│  Expert 2    "[1-2 sentence critique summary]"             │
│  Expert 3    "[1-2 sentence critique summary]"             │
│                                                            │
├─ Debate ──────────────────────────────────────────────────┤
│                                                            │
│  Agreed: [what all experts agreed on]                      │
│  Split:  [where they disagreed + which side won]           │
│  Top changes: [top 3 changes applied to the copy]          │
│                                                            │
├─ Result ──────────────────────────────────────────────────┤
│                                                            │
│  [Show the full rewritten copy]                            │
│                                                            │
│  Voice: [score]  │  Tokens: [n]  │  [duration]            │
╰────────────────────────────────────────────────────────────╯

Options: Continue | Revise | Show full critiques
```

**Show the work, not the plumbing.** The user should see what each expert said, where they agreed, where they disagreed, and the rewritten result. Offering "Show full critiques" gives access to the complete expert output without cluttering the default view.

---

## Revision Loops

When the user rejects a stage output:

1. **Collect revision notes** — what should change
2. **Record feedback** — action: "revise", notes, optional dimensional scores
3. **Rewind to the target stage** — reset pipeline state
4. **Re-run with notes** — the notes are injected into the stage's prompt

Dimensional scores (optional, only if user wants to rate):
- clarity, voice_fit, brand_fit, originality, engagement, accuracy, structure

### Art Revisions (Special)

Art has more revision options than copy:

| Option | What happens |
|--------|-------------|
| Revise with notes | Re-run art council with current images + user notes as context |
| Add reference images | Upload refs, re-run art with refs as style guidance |
| Regenerate from scratch | Fresh generation, no carry-forward from previous attempt |
| Switch art panel | Swap to different art expert panel, re-run |

**"Revise with notes"** is key — the current generated images are passed back as references, so the next generation refines rather than restarts. This preserves what's working while fixing what isn't.

---

## Pipeline Complete View

After all stages finish, show the full run summary:

```
╭─ RUN COMPLETE ────────────────────────────────────────────╮
│  Topic: [topic]                                            │
│  Format: [format]  │  Platform: [platform]                 │
├────────────────────────────────────────────────────────────┤
│  Stage        Duration  Tokens  Status                     │
│  ───────────  ────────  ──────  ──────                     │
│  writer          8.7s     377  ✓                           │
│  researcher      3.7s     477  ✓                           │
│  council        43.2s   8,600  ✓ 5 experts, 3 rounds      │
│  art            41.6s       —  ✓ image generated           │
│  postprod        5.3s       —  ✓ score: 0.9               │
│  publish         1.1s       —  ✓ saved                    │
│  ───────────  ────────  ──────  ──────                     │
│  TOTAL        103.6s    9,454                              │
├────────────────────────────────────────────────────────────┤
│  Voice: 0.80  │  Postprod: 0.90                           │
╰────────────────────────────────────────────────────────────╯
```

A typical run takes 90-120 seconds total. The council stage dominates because it runs multiple rounds of expert debate. This is by design — the quality improvement justifies the time.

---

## Display Philosophy

**Show the work, not the plumbing.** Lead with substance, infrastructure in the footer.

- Stage completions show the actual output (full draft, expert critiques, generated image) — not just "done in 5s"
- Approval gates show the question only — the user already sees the context above
- Settings changes show only what changed — not the full dashboard again
- Each message is additive — never re-render what was just shown

**Cognitive load budget:** Each message should be readable in under 5 seconds without scrolling. If a stage output is long (council critiques, full draft), use progressive disclosure:
1. Show the summary panel (fits on screen)
2. Offer "Show full [copy/critiques]" as an option
3. Only expand when asked

---

## Anti-Patterns

| Wrong | Right |
|-------|-------|
| Skip the interview, auto-generate | Interview data is the foundation — without it, everything downstream is generic |
| Auto-approve all stages | Pause after writer and council — these are where human judgment matters |
| Show "stage complete" without output | Show the actual draft, critiques, image — the substance |
| Re-run the entire pipeline on revision | Rewind to the specific stage and re-run from there |
| One AI pass for content | Multiple expert personas debating produces better output than any single pass |
| Generate images before approving copy | Copy first, images second. Always. |
| Restart art from scratch on revision | Pass current images as refs for iterative refinement |

# Quality Rules

Every piece of content must pass these rules before publishing. No exceptions.

## Rule 1: Hook Before the Fold

The first line of every post is the hook. It must grab attention before the platform truncates it.

### Fold Points by Platform

| Platform | Chars Before Fold | What Gets Cut |
|----------|------------------|---------------|
| LinkedIn | ~150 chars | Everything after "...see more" |
| Instagram | ~125 chars | Everything after "...more" |
| Facebook | ~480 chars | Everything after "See more" |
| X/Twitter | 280 chars total | N/A (no fold, hard limit) |
| Threads | 500 chars total | N/A (no fold, hard limit) |

### Hook Rules

- The hook must be COMPLETE before the fold. Do not start a sentence that gets cut off mid-thought.
- LinkedIn: your entire hook lives in the first ~150 characters. That is roughly one sentence. Make it count.
- The hook should create a gap — something the reader needs to resolve by clicking "see more."
- Good hooks: a specific claim, a surprising number, a contrarian take, a vivid scene.
- Bad hooks: a question, a greeting, "I'm excited to announce", a vague setup.

## Rule 2: No Hashtags

Do not use hashtags. On any platform.

**Why:**
- LinkedIn's algorithm stopped rewarding hashtags in 2024. They add no discovery value.
- Instagram's algorithm treats hashtags as spam signals when overused. Discovery comes from Reels and Explore, not hashtag feeds.
- X/Twitter: hashtags in the body of a tweet look spammy. If something is trending, the platform picks it up organically.
- Threads: hashtags are not part of the platform's discovery model.

**The only exception:** If the user explicitly asks for hashtags and insists after being told they hurt more than they help.

## Rule 3: The 50% Specificity Rule

At least 50% of the content must contain specific, personal content that only the author could have written.

### What Counts as Specific

- Named tools or technologies: "We used Postgres, not DynamoDB"
- Real numbers: "Saved 3 hours per deploy" not "significant time savings"
- Named people: "My CTO Mark said..." not "someone once told me"
- Dates and timelines: "Last March" not "recently"
- Project names or company names
- Opinions with conviction: "ORMs are wrong for this" not "ORMs may not be ideal"
- First-person experiences with concrete context

### What Counts as Generic

- Advice anyone could give: "Always test your code"
- Restating common knowledge: "APIs are important for modern apps"
- Vague claims: "This changed everything" without saying what changed
- Lists of best practices pulled from documentation
- "In my experience" without specifying the experience

### How to Check

Read the content and highlight every sentence that contains a specific name, number, date, tool, or personal detail. If less than half the sentences are highlighted, the content needs more interview material.

## Rule 4: Platform-Appropriate Length

Respect the platform's natural content length. Do not write a 3000-char LinkedIn post when the idea fits in 800 chars.

### Length Guidelines

| Platform | Sweet Spot | When to Go Long | When to Go Short |
|----------|-----------|-----------------|-----------------|
| LinkedIn | 800-1500 chars | Deep technical insight, story with arc | Quick observation, single takeaway |
| X/Twitter | 180-250 chars (single) | Thread for multi-point argument | One sharp thought |
| Instagram | 500-1000 chars | Personal story, behind-the-scenes | Quick caption for visual content |
| Facebook | 200-500 chars | Detailed update for niche group | Quick share or question |
| Threads | 200-400 chars | N/A (500 char limit) | Quick take |

### The Padding Test

Read the final draft and ask: "Can I remove a paragraph without losing the core message?" If yes, remove it. Social posts reward density, not length.

---

## Dual Optimization: Google SEO + AI Search

For long-form content (articles, blog posts), optimize for both traditional search AND AI search engines (Perplexity, ChatGPT search, Google AI Overviews).

### Google SEO Requirements

- Primary keyword appears in: H1, first 100 words, one H2, meta description, last 100 words
- Secondary keywords appear naturally 2-3 times each throughout the body
- URL slug is short, keyword-rich, hyphenated
- Meta description is 150-160 characters with keyword and value prop
- Internal links: 3-8 contextual links with descriptive anchor text
- No keyword stuffing — if a keyword appears more than 1.5% of total word count, it's overused
- Headings follow proper H1 > H2 > H3 hierarchy (never skip levels)
- Content directly answers search intent within the first 2 paragraphs

### AI Search Optimization Requirements

AI search engines extract and cite content differently than Google. Optimize for retrieval:

- **Clear, direct answers in the first paragraph** — AI models pull the most concise answer early
- **Entity-rich content** — Name specific tools, companies, people, frameworks by their proper names (not "a popular framework" — say "React" or "Next.js")
- **Structured claims with evidence** — Every major claim must have a data point, citation, or concrete example within 2 sentences
- **Self-contained sections** — Each H2 section should make sense if extracted alone (AI search often pulls a single section as a citation)
- **Definition patterns** — When introducing a concept, use the "[Term] is [definition]" pattern in the first sentence of its section
- **Comparison and list structures** — AI search overweights structured comparisons and numbered/bulleted lists for citation
- **Freshness signals** — Include specific dates, version numbers, and "as of [date]" references where applicable

## Entity-Driven Writing

Entities are the backbone of both SEO and AI search ranking. An entity is any specific, named thing: a person, company, product, standard, concept, or place.

### Entity Rules

- **Minimum 10 unique entities per article** (for social posts, aim for 3-5)
- **First mention is full name** — "React Server Components" before "RSCs"
- **No vague references** — never write "a leading company" when you can write "Stripe" or "Shopify"
- **Entity context** — when mentioning an entity, include one qualifying detail (e.g., "Stripe, the payment infrastructure company" on first mention)
- **Entity density** — at least 2 specific entities per H2 section
- **Avoid generic category words** as subjects — "the platform" should be "Vercel" or whatever it actually is

### Entity Checklist

Before finalizing, verify the content includes entities from at least 3 of these categories:

- [ ] Companies or organizations
- [ ] People (founders, researchers, practitioners)
- [ ] Products or tools (specific names and versions)
- [ ] Technical standards or protocols
- [ ] Industry concepts with proper terminology
- [ ] Data points with sources

## Citation and Source Rules (Long-Form)

- **Every statistical claim needs a source** — "73% of developers" requires "[Source, Year]"
- **Link to primary sources** — not aggregator articles that reference the original
- **Cite within the same paragraph** as the claim, not in a footnote section
- **Minimum 3 external citations per article** from authoritative sources
- **No citation needed for:** widely known facts, the author's own experience (when clearly marked), or logical deductions from cited data
- **Acceptable sources:** peer-reviewed research, official documentation, company reports, reputable industry surveys (Stack Overflow, State of JS, etc.), named expert quotes
- **Unacceptable sources:** anonymous blog posts, undated content, content farms, AI-generated aggregation sites

## Anti-Fluff Rules

Zero tolerance for filler content. Every sentence must inform, argue, or advance the reader's understanding.

### Banned Patterns

| Pattern | Example | Why It Fails |
|---------|---------|-------------|
| Throat-clearing openers | "In today's fast-paced digital landscape..." | Says nothing specific |
| Tautologies | "It's important to note that this is important" | Circular, no information |
| Vague intensifiers | "This is extremely crucial and very significant" | Adjective stacking without evidence |
| Empty transitions | "With that being said, let's move on to..." | Wastes words, just start the next point |
| Restating the heading | H2: "Benefits of X" → "There are many benefits of X." | The heading already said that |
| Hedge stacking | "It might potentially be somewhat possible that..." | Commit to the claim or don't make it |
| AI slurry | "Dive into", "Unlock the power of", "Harness" | Overused AI-generated phrases |
| False comprehensiveness | "This is a comprehensive guide to everything about..." | Let the content prove its depth |

### Sentence-Level Rules

- Every sentence must pass the "so what?" test — if you remove it and nothing is lost, remove it
- No sentence should merely restate what the previous sentence said in different words
- Transition between paragraphs through logical connection, not transitional phrases
- If a paragraph's only job is to introduce the next paragraph, delete it

## Quality Gate Summary

### For Social Posts

| Gate | Check | Pass Condition |
|------|-------|---------------|
| Hook placement | First ~150 chars (LinkedIn) | Complete thought before fold |
| No hashtags | Scan for # symbols | Zero hashtags |
| Interview basis | Check for specific details | At least 4 interview answers used |
| 50% rule | Count specific vs generic sentences | 50%+ specific |
| Anti-AI checklist | Scan for banned words/phrases | Zero matches |
| Platform length | Character count | Within platform sweet spot |

### For Articles

| Gate | Check | Pass Condition |
|------|-------|---------------|
| Word count | Total words | 1,500-2,500 words |
| Heading hierarchy | H1 > H2 > H3 | Valid, no skips |
| Entity count | Unique named entities | 10+ |
| Citations | External sources with links | 3+ |
| Meta description | Character count + keyword | 150-160 chars with primary keyword |
| Fluff check | Banned patterns scan | Zero matches |
| Anti-AI checklist | Full checklist | All items pass |
| SEO | Keyword placement | H1, first 100 words, one H2, meta |
| AI search | Section self-containment | Each H2 stands alone |