# A3M Router Content Structure

## The Flow: Pain → Research → FREE → Other Points

### 1. PAIN (Lead with this - 30% of content)

**The Hook:**
- "I was paying $2,400/month for OpenAI API calls"
- "Our AI costs hit 40% of infrastructure budget"
- "CFO said: cut 50% or remove features"

**The Agitation:**
- "We were using GPT-4 for EVERYTHING"
- "Even 'What is 2+2?' went to GPT-4 at $0.03/query"
- "Using a Ferrari for grocery runs"

**The Analysis:**
- "I looked at our logs"
- "34% simple Q&A, 28% code, 22% summarization, 16% complex"
- "We were overpaying by 70% for 84% of queries"

---

### 2. RESEARCH (Show the insight - 20% of content)

**The Discovery:**
- "I benchmarked alternatives"
- "Groq is 50x cheaper and 5x faster for code"
- "Mistral is 15x cheaper with 90% quality"
- "Different queries need different models"

**The Insight:**
- "Simple Q&A → any model works"
- "Code generation → speed matters"
- "Complex reasoning → quality matters"
- "One size doesn't fit all"

**The Approach:**
- "Inspired by RouteLLM (arXiv paper)"
- "Learned routing based on query characteristics"
- "Match capability to requirements"

---

### 3. FREE (The CTA - 15% of content)

**The Offer:**
- "npm install adaptive-memory-multi-model-router"
- "npx a3m-router route 'Your query'"
- "Try it online - no signup needed"
- "Open source, MIT license"

**The Playground:**
- "https://codesandbox.io/... (playground link)"
- "Test routing without API keys"
- "See which provider gets selected"

**The CLI:**
```bash
npx a3m-router route "Your query"
npx a3m-router benchmark
npx a3m-router providers
```

---

### 4. OTHER POINTS (Supporting info - 35% of content)

**Results:**
- "70% cost reduction"
- "2x speed improvement"
- "94% quality retention"
- "872 weekly downloads"

**Features:**
- "12 providers configured"
- "Zero configuration"
- "Cost tracking"
- "Automatic fallback"

**Technical:**
- "Query analysis"
- "Provider profiles"
- "Routing algorithm"
- "Benchmarks"

---

## Content Distribution by Platform

### Hacker News

**Structure:**
1. **PAIN** (40%) - Personal story, numbers
2. **RESEARCH** (15%) - Brief insight
3. **FREE** (20%) - Code example, CLI
4. **OTHER** (25%) - Technical details

**Why:** HN loves personal stories + code

---

### Dev.to

**Structure:**
1. **PAIN** (30%) - Relatable story
2. **RESEARCH** (25%) - Deep dive into problem
3. **FREE** (15%) - Installation, playground
4. **OTHER** (30%) - Tutorial, examples

**Why:** Dev.to readers want to learn + implement

---

### Twitter

**Structure:**
1. **PAIN** (50%) - Hook tweets
2. **RESEARCH** (20%) - Insight tweets
3. **FREE** (20%) - CTA tweets
4. **OTHER** (10%) - Results tweet

**Why:** Twitter needs immediate hooks

---

### Reddit (r/MachineLearning)

**Structure:**
1. **PAIN** (20%) - Brief context
2. **RESEARCH** (40%) - Technical approach
3. **FREE** (15%) - Try it
4. **OTHER** (25%) - Results, discussion

**Why:** ML community wants methodology

---

## The Golden Ratio

### For Maximum Engagement:
- **40% Pain** - Make it relatable
- **20% Research** - Show you're smart
- **20% Free** - Remove friction
- **20% Other** - Support with facts

### For Technical Audiences:
- **20% Pain** - Brief context
- **40% Research** - Deep technical
- **15% Free** - Easy to try
- **25% Other** - Implementation details

### For Business Audiences:
- **50% Pain** - ROI focus
- **15% Research** - Trust building
- **20% Free** - Low risk trial
- **15% Other** - Case studies

---

## Example: HN Post (40/20/20/20)

```
[PAIN - 40%]
I was paying $2,400/month for OpenAI API calls.
We're 5 people, 1,000 queries/day.
Using GPT-4 for EVERYTHING.
Even "What is 2+2?" at $0.03/query.
CFO said cut 50% or remove features.

[RESEARCH - 20%]
I looked at logs: 34% simple, 28% code, 22% summary, 16% complex.
Different queries need different models.
Built learned routing inspired by RouteLLM paper.

[FREE - 20%]
npm install adaptive-memory-multi-model-router
npx a3m-router route "Your query"
Try online: [playground link]
Zero config, 12 providers, MIT license.

[OTHER - 20%]
Results: 70% savings, 2x speed, 94% quality.
Supports Groq, Cerebras, Mistral, OpenAI, etc.
GitHub: [link]
```

---

## Key Principles

### 1. Pain First, Always
- Start with the problem
- Make it personal
- Use specific numbers
- Create emotional connection

### 2. Research Validates
- Show you understand the problem
- Reference credible sources
- Demonstrate expertise
- Build trust

### 3. Free Removes Friction
- No signup required
- Immediate value
- Low risk trial
- Easy to share

### 4. Other Points Support
- Don't lead with features
- Use for credibility
- Keep it brief
- Support the main story

---

## Common Mistakes

### ❌ WRONG: Feature-First
```
A3M Router is an intelligent routing system with 12 providers,
cost tracking, automatic fallback, batch processing...

It can reduce costs by 70%.
```
**Why it fails:** No emotional connection, sounds like marketing

### ✅ RIGHT: Pain-First
```
I was paying $2,400/month for OpenAI API calls.
We were using GPT-4 for everything.
Built a router that cut it to $720.
```
**Why it works:** Relatable problem, personal story, specific result

---

### ❌ WRONG: Research-First
```
RouteLLM (arXiv:2404.06035) proposes learned routing...
We implemented this approach with provider profiles...
```
**Why it fails:** Too academic, no hook

### ✅ RIGHT: Pain → Research
```
I was paying $2,400/month (pain).
Then I discovered RouteLLM paper (research).
Applied it to build this router (solution).
```
**Why it works:** Context first, then credibility

---

### ❌ WRONG: Free-First
```
Try A3M Router free!
npm install adaptive-memory-multi-model-router
It has 12 providers and cost tracking...
```
**Why it fails:** No reason to care, sounds salesy

### ✅ RIGHT: Pain → Free
```
I was paying $2,400/month (pain).
Built this to fix it (solution).
Try it free: npm install... (CTA)
```
**Why it works:** Context creates desire, then easy action

---

## Summary

**The Formula:**

```
[PAIN] I had this expensive problem
[RESEARCH] I discovered this insight
[FREE] I built this solution (try it free)
[OTHER] Here are the results and details
```

**The Ratio:**
- Pain: 30-50% (depending on audience)
- Research: 15-40% (depending on audience)
- Free: 15-20% (always easy to try)
- Other: 15-35% (supporting info)

**The Goal:**
Make them feel the pain, trust your solution, try it immediately.
