# 🗺️ The Path to Fame & Fortune: ODGS Strategic Roadmap (2026-2027)

**Mission:** Transform ODGS from a "Swiss Army Knife" of JSONs into the **Operating System for Enterprise AI Context.**

**The Strategy:** The "Trojan Horse"
1.  **Enter** via Data Engineers (Open Metric) - *Free, Developer Experience*
2.  **Expand** via Data Stewards (Governance as Code) - *Workflow, Control*
3.  **Dominate** via AI Safety (Algorithmic Accountability) - *Enterprise Value, Compliance*

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## 📅 2026 H1: The "Open Metric" Standard (Adoption Phase)
**Goal:** Become the "Markdown for Metrics". Ubiquitous adoption by Data Engineers.
**Metric:** 1,000 GitHub Stars, 100+ Active Deployments.

### 🛠️ Technical Deliverables
1.  **CLI 2.0 Experience**
    *   Make `odgs` feel like `npm` or `cargo`.
    *   `odgs init`: Scaffolds a new project.
    *   `odgs add metric <name>`: Interactive wizard to create a metric.
    *   `odgs diff`: Show semantic differences between local and git.
2.  **Universal Adapter Pack**
    *   **Looker**: Generate `view.lkml` files.
    *   **Metabase**: Sync metric definitions to Metabase metadata.
    *   **Generic SQL**: Transpile metric logic to ANSI SQL, BigQuery, Snowflake, etc.
3.  **"Metric Market" (Documentation)**
    *   A "Tailwind UI" for Metrics. Copy-paste standard SaaS metrics (ARR, Churn, LTV) into your project.
    *   Lower the barrier to entry to zero.

### 📢 Marketing & Outreach
*   **"Kill the Excel Sheet" Campaign**: Target the pain point of "Metric Drift".
*   **Integration Partners**: Launch official plugins for dbt and Dagster.

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## 📅 2026 H2: Governance as Code (Retention Phase)
**Goal:** Embed ODGS into the daily workflow of the Enterprise. Make it painful to remove.
**Metric:** Daily Active Users (DAU) in the ecosystem.

### 🛠️ Technical Deliverables
1.  **The "Governance Action" (CI/CD)**
    *   A GitHub Action that runs on every PR.
    *   **Impact Analysis**: "Changing 'Gross Margin' will break 3 Power BI dashboards and 2 AI Agents."
    *   **Approval Workflow**: Require "Finance" approval for changes to `finance` domain metrics.
2.  **VS Code Extension**
    *   IntelliSense for Metric IDs.
    *   Hover over a metric ID in code to see its definition and owner.
    *   "Go to Definition" support.
3.  **Local-First Management UI**
    *   A lightweight web UI (run via `odgs ui`) to edit JSONs visually.
    *   For non-technical users (Data Stewards) to propose changes without touching JSON.

### 📢 Marketing & Outreach
*   **"Governance is Engineering"**: Appeal to CTOs and VPs of Engineering.
*   **Case Studies**: Publish "How Company X solved Metric Drift with ODGS".

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## 📅 2027: Algorithmic Accountability (Expansion Phase)
**Goal:** Become the "Gold Standard" for AI Safety and Compliance (EU AI Act).
**Metric:** Enterprise Contracts, $10M+ Valuation.

### 🛠️ Technical Deliverables
1.  **The "Context Engine" SDK**
    *   Python/Node.js SDK for LangChain / LlamaIndex / AutoGen.
    *   `chain.use_odgs_context(project_path)`: Automatically injects relevant metric definitions into the LLM context window.
    *   **RAG for Logic**: Retrieve *definitions*, not just *data*.
2.  **Hallucination Validator**
    *   A service that checks LLM outputs against ODGS logic.
    *   If AI says "Churn is 5%", but ODGS calculation yields "4.2%", flag it.
3.  **Regulatory Compliance Reports**
    *   Auto-generate "Data Lineage" and "Algorithm Logic" reports for auditors.
    *   "Click to Comply" for EU AI Act transparency requirements.

### 📢 Marketing & Outreach
*   **"Safe AI" Certification**: "Powered by ODGS" badge means the AI doesn't hallucinate business logic.
*   **Enterprise Sales**: Sell the "Enterprise Control Plane" (SaaS) that manages the Context Engine and Compliance.

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## 🚀 Immediate Next Steps (This Week)
1.  **Refine the Core**: Ensure `standard_metrics.json` and schemas are bulletproof.
2.  **Build the CLI**: The current `scripts/` are a good start, but we need a unified `odgs` CLI tool.
3.  **Documentation Overhaul**: Update README to reflect this roadmap and the "Trojan Horse" strategy more clearly.
