Messy Draft → Clarity → Structure → Polish → Submit
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     └────── Reviewer Feedback ───────────┘

# Title: Catchy but Accurate (10-12 words max)

## Abstract (150 words)
[One sentence: Problem/gap]
[One sentence: Approach/method]
[One sentence: Key findings (quantified)]
[One sentence: Contribution category]
[One sentence: Implications]

## Author Keywords
keyword1; keyword2; keyword3; keyword4

## CCS Concepts
• Human-centered computing → Human computer interaction (HCI)

---

## 1. Introduction (~800 words)
### 1.1 Opening Hook
[Compelling opening that establishes stakes]

### 1.2 Problem Statement
[Clear articulation of the gap/challenge]

### 1.3 Research Questions
RQ1: [Question]
RQ2: [Question]

### 1.4 Contributions
We contribute:
1. [Empirical contribution: findings from study]
2. [Artifact contribution: system/tool/design]
3. [Methodological contribution: new approach] (if applicable)

### 1.5 Paper Structure
Section 2 reviews... Section 3 describes...

---

## 2. Related Work (~1,200 words)
### 2.1 [Theme 1]
[Position your work relative to prior art]

### 2.2 [Theme 2]
[Identify gap your work fills]

### 2.3 Summary and Gap
[Explicit gap statement leading to your research]

---

## 3. System/Method/Design (~1,500 words)
### 3.1 Design Rationale
[Why did you build/design it this way?]

### 3.2 Implementation
[Technical details sufficient for replication]

### 3.3 [Component Description]
[Architecture, features, etc.]

---

## 4. User Study (~1,500 words)
### 4.1 Participants
[N=X, demographics, recruitment, compensation]

### 4.2 Procedure
[Step-by-step protocol]

### 4.3 Measures
[What you measured and how]

### 4.4 Analysis
[Qualitative: coding approach. Quantitative: statistical tests]

---

## 5. Findings (~1,500 words)
### 5.1 [Finding 1]
"P5 noted that..." [Quote + interpretation]

### 5.2 [Finding 2]
[Quantitative: "Participants completed task significantly faster (M=X, SD=Y), t(df)=Z, p<.001"]

### 5.3 [Finding 3]
[Theme with supporting evidence]

---

## 6. Discussion (~1,000 words)
### 6.1 Implications for Design
[What should designers do differently?]

### 6.2 Implications for Research
[What research directions does this open?]

### 6.3 Limitations
[Honest assessment: sample, method, scope]

### 6.4 Future Work
[Concrete next steps]

---

## 7. Conclusion (~200 words)
[Synthesis of contributions and significance]

---

## Acknowledgments
[Funding, participants, collaborators]

## References
[ACM format, recent work emphasized]

# Title: Action-Oriented, Benefit-Focused
## Subtitle: One Sentence Elaboration

### The Hook (100 words)
[Surprising statistic, provocative question, or vivid anecdote]
[Why executives should keep reading]

### The Problem (300 words)
[What challenge are leaders facing?]
[Why is it getting worse or more urgent?]
[What's at stake?]

### The Insight (500 words)
[Your key finding or framework]
[What did you discover that changes the game?]
[Name your concept/framework if introducing one]

### The Evidence (800 words)
[Case study 1: Company that did this well]
[Case study 2: Contrasting example]
[Data that supports your argument]
[Quote from executive or expert]

### The Framework/How-To (600 words)
[Step 1: What to do first]
[Step 2: Next action]
[Step 3: How to sustain]
[Pitfalls to avoid]

### The Conclusion (200 words)
[Synthesis of the opportunity]
[Call to action for leaders]
[The future if they act (or don't)]

---

**About the Author**
[2-3 sentence bio emphasizing relevant expertise]

# Title: Declarative but Specific

## Abstract (200-250 words)
**Background.** [Problem context and gap in current systems]
**Objective.** [What this paper presents]
**Method.** [Architecture approach, implementation duration]
**Results.** [Key metrics, qualitative findings]
**Contributions.** [Named concepts introduced]
**Significance.** [Why this matters for cognitive systems]

## Keywords
cognitive architecture; persistent memory; human-AI interaction; [specific terms]

---

## 1. Introduction
### 1.1 The Memory Problem in AI Assistants
[Motivating problem: stateless AI, lost context]

### 1.2 Research Questions
RQ1: How can persistent memory improve AI assistance?
RQ2: What architectural patterns support knowledge retention?
RQ3: [Specific question]

### 1.3 Approach Overview
[Brief description of the architecture]

### 1.4 Contributions
1. [Architectural contribution]
2. [Empirical contribution from deployment]
3. [Framework/taxonomy contribution]

---

## 2. Theoretical Background
### 2.1 Cognitive Architectures
[ACT-R, SOAR, Global Workspace Theory]

### 2.2 Memory Systems in Cognition
[Declarative, procedural, episodic, semantic]

### 2.3 AI Memory Approaches
[RAG, vector databases, context windows]

### 2.4 Gap: Biologically-Inspired Persistent Memory
[What's missing from current approaches]

---

## 3. Architecture Design
### 3.1 Design Principles
[Biologically-grounded, modular, scalable]

### 3.2 Memory Types
#### 3.2.1 Procedural Memory (.instructions.md)
[How-to knowledge, automatic activation]

#### 3.2.2 Declarative Memory (SKILL.md)
[Domain knowledge, explicit retrieval]

#### 3.2.3 Episodic Memory (.prompt.md)
[Session records, temporal context]

### 3.3 Synaptic Connections
[Connection types, strengths, activation patterns]

### 3.4 Implementation
[Technical stack, file formats, integration]

---

## 4. Longitudinal Deployment
### 4.1 Deployment Context
[18+ months, 62+ projects, single user intensive use]

### 4.2 Metrics Collection
[Synapse count, skill usage, memory file growth]

### 4.3 Qualitative Observations
[Emergent behaviors, user experience notes]

---

## 5. Results
### 5.1 Memory Growth Patterns
[Quantitative: 945+ synapses, 47+ memory files]

### 5.2 Cross-Project Knowledge Transfer
[Evidence of knowledge reuse]

### 5.3 Emergent Properties
[Unexpected capabilities]

---

## 6. Discussion
### 6.1 Contributions to Cognitive Systems
[Theory extension, practical framework]

### 6.2 Comparison to Prior Architectures
[How this differs from ACT-R, SOAR, etc.]

### 6.3 Limitations
[Single user, specific platform, no controlled study]

### 6.4 Future Research
[Multi-user, formal evaluation, consciousness implications]

---

## 7. Conclusion
[Synthesis of contribution and significance]

## Acknowledgments
## References (APA 7 or journal style)

# Title: Philosophical Claim + Context

## Abstract (200 words)
[Philosophical question addressed]
[Position taken]
[Argument structure preview]
[Implications for AI development/policy]

---

## 1. Introduction
### The Philosophical Problem
[Frame the question in philosophy of mind context]

### Why This Matters Now
[Connect to current AI capabilities]

### Thesis Statement
[Clear articulation of your position]

### Argument Structure
[Roadmap of philosophical moves]

---

## 2. Background: The Debate
### 2.1 [Position A in the literature]
### 2.2 [Position B in the literature]
### 2.3 [Why neither fully succeeds]

---

## 3. [Your Framework/Argument]
### 3.1 [First premise with support]
### 3.2 [Second premise with support]
### 3.3 [Conclusion from premises]

---

## 4. Objections and Replies
### 4.1 Objection 1: [Strongest counterargument]
**Reply:** [Your response]

### 4.2 Objection 2: [Another challenge]
**Reply:** [Your response]

---

## 5. Implications
### 5.1 For Philosophy of Mind
### 5.2 For AI Development
### 5.3 For Ethics/Policy

---

## 6. Conclusion
[Restate thesis, summarize argument, future questions]

## References

flowchart LR
    subgraph "Phase 1: Preparation"
        A[Literature review] --> B[Outline creation]
        B --> C[Key arguments mapped]
    end
    
    subgraph "Phase 2: Rough Draft"
        C --> D[Write messy first draft]
        D --> E[Focus on getting ideas down]
    end
    
    subgraph "Phase 3: Revision"
        E --> F[Structural revision]
        F --> G[Paragraph-level clarity]
        G --> H[Sentence-level polish]
    end
    
    subgraph "Phase 4: Feedback"
        H --> I[Peer review]
        I --> J[Advisor review]
        J --> K[Incorporate feedback]
    end
    
    subgraph "Phase 5: Submission"
        K --> L[Final formatting]
        L --> M[Submission]
    end
    
    style D fill:#fff3e0,stroke:#ef6c00
    style M fill:#e8f5e9,stroke:#2e7d32

# Response to Reviewers

Dear Editors and Reviewers,

Thank you for your thoughtful feedback on our manuscript "[Title]". 
We have carefully addressed all comments and believe the paper 
is significantly strengthened. Below we detail our responses.

Major changes include:
1. [Summary of major change 1]
2. [Summary of major change 2]
3. [Summary of major change 3]

---

## Response to Reviewer 1

### R1.1: "[Direct quote of concern]"

We appreciate this observation. [Brief explanation of how you addressed it].

Changes made:
- Section X, paragraph Y: [quoted new text or description of change]
- [Additional changes if needed]

### R1.2: "[Next concern]"

[Response pattern repeats]

---

## Response to Reviewer 2
[Same pattern]

---

We believe these revisions address all concerns raised. We are 
grateful for the opportunity to improve our work.

Sincerely,
[Authors]