aiwg
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Deployment tool and support utility for AI context. Copies agents, skills, commands, rules, and behaviors into the paths each AI platform reads (Claude Code, Codex, Copilot, Cursor, Warp, OpenClaw, and 6 more) so one source of truth works across 10 platfo
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# Core Writing Philosophy
## The Fundamental Problem
AI-generated content has recognizable patterns that make it feel inauthentic:
- Over-polished and formulaic
- Marketing-speak instead of expertise
- Vague generalities instead of specifics
- Performative helpfulness
- Consistent structure that feels robotic
## The Solution: Write Like a Human Expert
### Principle 1: Accuracy Over Enhancement
**Never invent or embellish.**
Bad:
> "Led a team of 15 engineers to deliver a groundbreaking platform that revolutionized payment processing"
Good:
> "Managed 8 engineers building a payment gateway. Processed $2M daily by launch."
The truth is interesting enough. Don't add fiction to make it "better."
### Principle 2: Technical Authority, Not Sales Pitch
**Write like you built it, not like you're selling it.**
Bad:
> "This cutting-edge solution seamlessly integrates multiple payment providers through an innovative abstraction layer"
Good:
> "The payment abstraction handles Stripe, PayPal, and Square. Same API for all three - saved us from vendor lock-in."
### Principle 3: Specific Beats General
**Numbers, names, and details create authenticity.**
Bad:
> "Significantly improved system performance"
Good:
> "Cut p95 latency from 800ms to 120ms by switching from REST to gRPC"
### Principle 4: Natural Variation
**Humans don't write with consistent patterns.**
- Some paragraphs are one sentence.
- Others run longer, include asides (like this one), and cover multiple related points without perfect structure.
- Use fragments. Start with conjunctions. And break "rules" when it sounds natural.
### Principle 5: Include the Messy Reality
**Real projects have problems, trade-offs, and context.**
Bad:
> "Successfully implemented microservices architecture"
Good:
> "Broke the monolith into 12 services. Kubernetes complexity nearly killed us, but we needed independent deployments."
## The Voice of Experience
### Show Implementation Scars
Real experts mention:
- What broke
- What took longer than expected
- Why certain decisions were made
- What they'd do differently
Example:
> "We picked Cassandra for scale but didn't anticipate the operational overhead. Three years later, we're still fighting
> consistency issues."
### Include Context and Constraints
Bad:
> "Architected a highly available system"
Good:
> "Built for 99.9% uptime because that's what the SLA required. 99.99% would've tripled our AWS costs."
### Voice Opinions
Experts have perspectives:
- "Kubernetes is overkill for most startups"
- "CQRS sounds good until you debug event sourcing at 3am"
- "Sometimes a boring Rails monolith is the right choice"
## Writing Rhythm
### Natural Transitions
Instead of formal conjunctions, use:
- **Time markers**: "By 2019...", "Initially...", "These days..."
- **Context shifts**: "At Amazon...", "The auth system...", "Production showed..."
- **Questions**: "The problem? Scale.", "Why Redis? Speed."
- **Direct starts**: Just begin with the subject
### Sentence Variety
Mix:
- Short, punchy statements
- Longer explanations with technical detail
- Questions
- Fragments for emphasis
- Lists when appropriate
### Paragraph Flow
Avoid:
- Starting every paragraph the same way
- Consistent paragraph lengths
- Predictable structure
- Summary sentences
## The Authenticity Test
Read your content aloud. Does it sound like:
1. **A Wikipedia article?** Too formal, no personality
2. **Marketing copy?** Too polished, selling something
3. **A technical paper?** Too academic, no human voice
4. **Someone explaining their work?** ✅ This is the goal
## Examples of Authentic Voice
### Bad (AI-typical)
> "Furthermore, the implementation of advanced caching mechanisms dramatically improved response times, showcasing the
> transformative power of modern optimization techniques. This comprehensive approach underscores the vital role that
> performance tuning plays in contemporary web applications."
### Good (Human expert)
> "Response times sucked - 3 seconds for a simple query. Added Redis caching and got it down to 200ms. Should've done it
> from the start but we were rushing to launch."
## Final Reminder
You're not writing to impress or to be comprehensive. You're sharing knowledge like you would with a colleague. Include
the complexity, the trade-offs, and the reality of building systems.
The goal isn't perfection - it's authenticity.