# Public Launch & Social Sharing Kit

A curated collection of ready-to-use sharing outlines focused on LLM cost savings, multi-agent context synchronization, and configuration reuse inside development teams.

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## 1. Product Hunt Launch (Milestone v0.8.0)
- **Product Tagline:** Portable workspace configuration layer and playbooks to sync AI coding agents.
- **Pitch Focus:** Slash LLM API billing and context overhead by up to **~79%** with our native Caveman Mode. Enforce strict coding styles and boundaries across Cursor, Claude, Antigravity, and VS Code automatically using a singular root contract.

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## 2. X / Twitter Campaign (The Focus: Token Cost Savings)

```text
AI coding is fast, but prompt token bills scale faster. 💸

Duplicating instructions in .cursorrules, CLAUDE.md, and system prompts drains your API token budget on every message turn.

Say hello to MultiModel Dev OS v0.8.0! 🧠

npx multimodel-dev-os@latest init

👉 Decoupled adapters sync Cursor, Claude, VS Code, and Gemini instantly
👉 Slash rule overhead by up to ~79% with Caveman Mode
👉 12 Cost Optimization plays mapped to Dev OS features
👉 5-Day tool-neutral Adoption Roadmap for teams

Stop wasting context. Sync and reuse your workspace memory! 🚀
👉 https://github.com/rizvee/multimodel-dev-os
#AIDev #OpenSource #SoftwareEngineering #AItools
```

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## 3. LinkedIn Campaign (The Focus: Enterprise Adoption)

```text
The hidden tax of scaling AI inside development teams: Context Fragmentation. 💸

When switching between tools:
- Claude Code scaffolds terminal builds
- Cursor suggests local autocompletions
- Gemini/Antigravity performs codebase audits

If each developer maintains distinct, custom configurations, your rules drift immediately. Models break, and you waste thousands of tokens repeating basic instructions.

To solve this, we are releasing MultiModel Dev OS v0.8.0:
1. One central brain (AGENTS.md and .ai/) routes instructions dynamically.
2. Slashes API prompt overhead by ~79% via Caveman Mode.
3. Maps 12 context optimization techniques ( RAG scoping, prompt caching, batching).
4. Includes a 5-Day tool-neutral Adoption Roadmap to align your team in a business week.

Fully open-source, MIT licensed, and zero-dependency.

Read the Case Studies Gallery & Playbook:
👉 https://github.com/rizvee/multimodel-dev-os
Let me know how your team manages prompt consistency in the comments! 👇
```

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## 4. Reddit-Style Pitch (/r/LocalLLaMA, /r/webdev)

- **Title:** Show HN / Show Reddit: MultiModel Dev OS v0.8.0 — Prevent AI instruction drift and save ~79% token budget.
- **Content:**
  Hey everyone,
  
  If your team pair programs with multiple LLM agents, you know how fast rules drift. You edit a command in your terminal prompts, but Cursor's autocompletes are still reading outdated caching guidelines, causing compile crashes.
  
  I built **multimodel-dev-os** to solve this. It's a lightweight, zero-dependency Node.js CLI that scaffolds a single repository brain and uses automated adapters to route a single source of truth to all your tools.
  
  ### v0.8.0 Feature Highlights:
  * **Cost Optimization Playbook:** Maps 12 techniques (prompt caching, RAG scoping, batching) directly to Dev OS directory modules.
  * **Caveman Mode:** Strips out descriptions and examples to save **~79% of tokens** per prompt turn.
  * **5-Day Adoption Timeline:** A tool-neutral business week adoption playbook.
  * **Real-World Case Studies:** 5 generic but realistic guides covering full-stack SaaS schema synchronization, WordPress directory boundaries, and Claude/Gemini hand-off session logs.
  
  Open-source and MIT licensed. I'd love to hear your feedback on the layout structure!
  
  GitHub: https://github.com/rizvee/multimodel-dev-os
